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hangshuo652/cobol-java-v3:main hangshuo652/cobol-java-v3:feat/phase2-review-fixes hangshuo652/cobol-java-v3:feat/phase2-complete hangshuo652/cobol-java-v3:feat/enhanced-test-phase1
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hangshuo652/cobol-java-v3:feat/phase2-review-fixes hangshuo652/cobol-java-v3:feat/phase2-complete hangshuo652/cobol-java-v3:feat/enhanced-test-phase1 hangshuo652/cobol-java-v3:main

2 Commits
a6c454692a .. main

Author SHA1 Message Date
hangshuo652 7ac887c776 feat: complete INSPECT/SEARCH support, fix PERFORM/EVAL coverage marking 
- Add INSPECT (TALLYING/REPLACING/CONVERTING) with BEFORE/AFTER INITIAL
- Add SEARCH/SEARCH ALL with element-assignment path enumeration
- Fix _mark_perform compound condition marking via evaluate_tree
- Fix EVALUATE TRUE prior_false to collect all MC/DC false sets
- Add impossible path filtering (Pass A.5) with trace-to-root conflict detection
- Fix multi-line PERFORM VARYING parsing (VARYING/FROM/BY/UNTIL on separate lines)
- Remove dead code: agents.py LLM parser (replaced by rule-based _BrParser)
- 59 unit tests passing, 5 integration programs verified
 2026-06-10 22:56:22 +08:00
hangshuo652 0730045e27 add cobol_testgen module 2026-06-08 21:07:16 +08:00
147 changed files with 68 additions and 19540 deletions
Expand all files Collapse all files
.gitignore
+7 -26
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@@ -1,30 +1,11 @@
# Build
# Coverage
# Python
*.egg-info/
*.exe
*.exec
*.gcda
*.gcno
*.py,cover
*.pyc
.DS_Store
.cache/
.coverage
.pytest_cache/
__pycache__/
build/
coverage.json
*.pyc
*.egg-info/
dist/
htmlcov/
build/
.cache/
reports/
test-data-bundle/
*.exec
target/
test-data-bundle/
uploads/
tasks/
cobol_out.bin
*.sh
reports/
test-data-bundle/
cobol-javascreenshots/
.DS_Store
AGENTS.md
+18
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@@ -0,0 +1,18 @@
# cobol-java-v3
## 工作目录
C:\Users\marye\Desktop\2026技术大赛\cobol-java-v3
## 我的模块
cobol_testgen/
## 远程仓库
https://gittea.dev/hangshuo652/cobol-java-v3
## 工作流程
```powershell
cd "C:\Users\marye\Desktop\2026技术大赛\cobol-java-v3"
git add cobol_testgen/
git commit -m "描述修改"
git push
```
CONTRIBUTING.md
-234
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@@ -1,234 +0,0 @@
# 贡献指南 — 模块化开发规则
> 本文档定义多人协作开发本项目的规则。**所有开发者必须遵守。**
---
## 1. 模块分层
```
Layer 1: data/ ← 核心数据模型（所有人共享）
Layer 2: cobol_testgen/ config/ jcl/parser/ quality/ report/ preprocessor/
← 业务引擎（每人负责 1-2 个）
Layer 3: hina/ agents/ comparator/ runners/
← 高级引擎（每人负责 1 个）
Layer 4: orchestrator/ web/ jcl/executor/
← 管道集成（H 负责）
```
**规则**: 下层不能依赖上层。Layer 2 不能 import Layer 3。
---
## 2. `__all__` 规则
每个模块的 `__init__.py` 必须有 `__all__`。
```
在 `__init__.py` 中:
✅ __all__ 里的 = 公开 API（其他人可依赖）
❌ __all__ 外的 = 内部实现（随时可改）
```
**只有 `__all__` 中列出的函数/类是稳定接口**。修改 `__all__` 外的代码不需要通知其他人。修改 `__all__` 内的代码必须：
1. 更新 `docs/module-interfaces.md`
2. 在 PR 中标注 `[BREAKING]`
3. 通知所有使用者
---
## 3. 导入规则
### ✅ 正确做法: 只从模块顶层导入
```python
# ✅ Layer 2 → Layer 1
from data import Field, FieldTree, VerificationRun
# ✅ Layer 3 → Layer 1
from data import TestCase, TestSuite
# ✅ Layer 3 → Layer 2
from cobol_testgen import extract_structure
# ✅ Layer 4 → 各层
from hina import gate_check, compute_confidence
from comparator import compare_field
from runners import CobolRunner
```
### ❌ 错误做法: 钻入模块内部
```python
# ❌ 不要直接从子模块导入 — 你的代码会依赖内部结构
from cobol_testgen.coverage import check_coverage # ❌
from hina.gate import check # ❌
from runners.cobol_runner import CobolRunner # ❌
from agents.agent1_parser import Agent1Parser # ❌
```
**为什么**: 如果子模块重构（改名、拆分、合并），钻入内部的代码全部断裂。而模块顶层的 `__all__` 提供了稳定抽象层。
---
## 4. 数据模型契约
### 4.1 所有模块共用 data/ 下的 3 组类
| 类 | 用途 | 属于谁 |
|:---|:-----|:-------|
| `Field`, `FieldTree` | 字段树 | cobol_testgen → → comparator |
| `TestCase`, `TestSuite`, `SparkConfig` | 测试数据 | cobol_testgen → → runners |
| `FieldResult`, `VerificationRun` | 管道结果 | orchestrator → → comparator → → report |
### 4.2 修改 data/ 的规则
1. **必填字段** 直接添加到 dataclass（有默认值则向后兼容）
2. **可选字段** 使用 `Optional` 或 `""` 默认
3. **删除字段** 必须标注 `[BREAKING]`，检查所有使用处
4. **修改字段含义** 必须更新 `data/__init__.py` 的文档注释
**修改 data/ 必须通知所有开发者**（微信群 / PR 标注 `[DATA-CHANGE]`）。
---
## 5. 函数签名规则
### 5.1 必须加类型注解
```python
# ✅ 正确
def extract_structure(cobol_source: str, source_dir: str = None) -> dict:
# ❌ 错误 — 调用者不知道参数类型
def extract_structure(cobol_source, source_dir=None):
```
### 5.2 返回值必须符合 `data/` 模型
- 函数返回多个值 → 包装成 dataclass
- 函数返回可选 → `Optional[...]`
- 函数返回集合 → `list[...]` 明确元素类型
### 5.3 不要用 dict 当"隐式接口"
```python
# ❌ 返回无类型 dict — 调用者需要读实现才知道 key 名
def run() -> dict:
return {"status": "ok", "matched": 5}
# ✅ 返回类型化的对象
def run() -> VerificationRun:
return vr
```
已有 `verificationRun` 这样的完整数据类，优先复用。
---
## 6. 测试规则
### 6.1 测试文件位置
```
tests/
├── cobol_testgen/ ← A 的测试
├── hina/ ← D 的测试
├── agents/ ← E 的测试
├── config/ ← B 的测试
├── comparator/ ← F 的测试
├── runners/ ← G 的测试
├── data/ ← 所有人的数据模型测试
├── nonfunctional/ ← 性能/并发/安全
└── test_*.py ← 跨模块集成测试（H 负责）
```
### 6.2 测试用例命名
```python
def test_[模块]_[功能](): # ✅ 推荐
def test_extract_structure_simple_if():
```
### 6.3 测试覆盖要求
- 新功能必须附带测试
- 修复 bug 必须附带回归测试
- 覆盖率目标: 核心管道 ≥ 85%，各模块 ≥ 70%
---
## 7. Config 修改规则
`config/__init__.py` 的 `Config` 类是所有模块共享的配置。
修改 Config 的规则:
1. **加字段**: 添加到 dataclass（有默认值）
2. **删字段**: 必须标注 `[BREAKING]`，检查所有使用者
3. **改含义**: 更新 `docs/module-interfaces.md`
Config 的字段格式示例:
```python
runner_mode: str = "native"
# 取值: "native" | "spark"
# 负责: G (runners 组)
# 默认说明: 优先使用本地 Java 执行，无 Spark 依赖
```
**每个 Config 字段必须标注取值范围和负责组**。
---
## 8. 模块负责人一览
| 模块 | 负责人 | __all__ 公开 API |
|:-----|:------|:-----------------|
| `cobol_testgen/` | A | extract_structure, generate_data, incremental_supplement, check_coverage |
| `config/` | B | Config |
| `preprocessor/` | B | CopybookPreprocessor |
| `report/` | B | ReportGenerator |
| `quality/` | C | L1OffsetValidator, L2RoundtripValidator |
| `jcl/` | C | parse_jcl, JclExecutor, Job, JobStep, DDEntry, CondParam |
| `hina/` | D | gate_check, compute_confidence, classify_with_llm, supplement, RetryHandler, collect_gcov |
| `agents/` | E | LLMClient, Agent1Parser, Agent2Data, Agent3Diagnostic |
| `comparator/` | F | align_records, compare_field, CobolBinaryReader, Normalizer, detect_rounding |
| `runners/` | G | CobolRunner, NativeJavaRunner, SparkJavaRunner, DataWriter |
| `storage/` | G | DiskCache, ReportStore, TestDataBundle |
| `data/` | **所有人** | Field, FieldTree, TestCase, TestSuite, SparkConfig, FieldResult, VerificationRun |
| `orchestrator/` | H | run_pipeline |
| `web/` | H | FastAPI app, Worker |
---
## 9. 新增模块规则
新增模块时的检查清单:
- [ ] 创建目录 + `__init__.py`
- [ ] `__init__.py` 包含 `__all__`
- [ ] `docs/module-interfaces.md` 更新接口描述
- [ ] 确认依赖方向正确（不反向依赖）
- [ ] 写测试文件
- [ ] 创建人加入模块负责人表
---
## 10. 快速参考
```bash
# 验证所有导入通畅
python -c "
from cobol_testgen import extract_structure
from hina import compute_confidence
from agents import LLMClient
from comparator import compare_field
from runners import CobolRunner
from data import Field, FieldTree, VerificationRun
"
# 运行测试
pytest tests/ -x --tb=short
# 检查 __all__ 完整性
grep -r "^__all__" */__init__.py
```
agents/__init__.py
-22
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@@ -1,22 +0,0 @@
"""LLM 智能体包
公开 API:
LLMClient — LLM API 客户端（含缓存 + 重试）
Agent1Parser — COPYBOOK → FieldTree
Agent2Data — FieldTree → TestSuite（测试数据设计）
Agent3Diagnostic — FieldResult → 诊断建议文本
"""
from __future__ import annotations
from .llm import LLMClient
from .agent1_parser import Agent1Parser
from .agent2_data import Agent2Data
from .agent3_diagnostic import Agent3Diagnostic
__all__ = [
"LLMClient", # class
"Agent1Parser", # class
"Agent2Data", # class
"Agent3Diagnostic", # class
]
agents/llm.py
+1 -6
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@@ -15,12 +15,7 @@ class LLMClient:
def _get(self, k):
p = self.dir / f"{k}.json"
if not p.exists():
return None
try:
return json.loads(p.read_text())["response"]
except (json.JSONDecodeError, KeyError):
return None
return json.loads(p.read_text())["response"] if p.exists() else None
def _set(self, k, v):
(self.dir / f"{k}.json").write_text(json.dumps({"response": v}))
cobol_testgen/__init__.py
+5 -435
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@@ -1,15 +1,6 @@
"""COBOL Test Data Generator — 模块化版入口
from __future__ import annotations
公开 API:
extract_structure() — 解析 COBOL 控制流 → dict
generate_data() — 生成测试数据 → list[dict]
incremental_supplement — 差分补充数据 → list[dict]
check_coverage() — 覆盖率报告 → dict
"""
"""COBOL Test Data Generator — 模块化版入口"""
import sys
import re
import logging
from datetime import datetime
from pathlib import Path
@@ -19,25 +10,14 @@ from pathlib import Path
CONFIG = {}
from .read import preprocess, extract_data_division, extract_procedure_division
from .read import resolve_copybooks, parse_data_division, parse_file_section, scan_open_statements, parse_file_control
from .read import resolve_copybooks, parse_data_division, parse_file_section, scan_open_statements
from .core import build_branch_tree, classify_field_roles, _init_child_names
from .cond import parse_single_condition, is_field, collect_leaves
from .cond import parse_single_condition, is_field
from .design import enum_paths, generate_records, _filter_stop
from .output import output_json, output_input_files
from .coverage import run_coverage, generate_coverage_index, check_coverage
from japanese_data import generate_fullwidth_text, generate_halfwidth_katakana, generate_wareki_date
from .coverage import run_coverage, generate_coverage_index
logger = logging.getLogger(__name__)
n__all__ = [
"extract_structure",
"generate_data",
"incremental_supplement",
"check_coverage",
"CONFIG",
"generate_fullwidth_text",
"generate_halfwidth_katakana",
"generate_wareki_date",
]
# ── OCCURS 展开 ──
@@ -137,7 +117,7 @@ def main():
fh = logging.FileHandler(log_path, encoding="utf-8", mode="w")
fh.setLevel(logging.DEBUG)
fh.setFormatter(logging.Formatter(
"%(asctime)s [%(levelname)s] %(name)s: %(message)s"
"%(asctime)s [%(levelname)s] %(name)s: %(message)s"
))
sh = logging.StreamHandler()
sh.setLevel(logging.INFO)
@@ -319,413 +299,3 @@ def main():
if programs:
generate_coverage_index(programs, outdir)
logger.info(f"\n覆盖率总览：{outdir / 'coverage' / 'index.html'}")
# ════════════════════════════════════════════
# Phase 1: 可编程 API（供 orchestrator.py 调用）
# ════════════════════════════════════════════
def extract_structure(cobol_source: str) -> dict:
"""分析 COBOL 源码的结构，返回结构摘要。不生成测试数据，只做静态分析。
Returns:
dict with: paragraphs, decision_points, branch_tree, file_count,
open_directions, has_search_all, has_evaluate,
has_call, has_break, total_branches, total_paragraphs
"""
preprocessed = preprocess(cobol_source)
data_div = extract_data_division(preprocessed)
data_fields = parse_data_division(data_div) if data_div else []
fields_dict = []
for idx, f in enumerate(data_fields):
entry = {
'name': f.name if f.name != 'FILLER' else f'FILLER_{idx + 1}',
'level': f.level, 'pic': f.pic,
'pic_info': {
'type': f.pic_info.type if f.pic_info else 'unknown',
'digits': f.pic_info.digits if f.pic_info else 0,
'decimal': f.pic_info.decimal if f.pic_info else 0,
'length': f.pic_info.length if f.pic_info else 0,
'signed': f.pic_info.signed if f.pic_info else False,
},
'section': f.section, 'occurs': f.occurs_count,
'occurs_depending': f.occurs_depending,
'redefines': f.redefines, 'usage': f.usage,
}
if f.is_88:
entry['is_88'] = True
entry['parent'] = f.parent
entry['value'] = f.value
entry['values'] = f.values
fields_dict.append(entry)
fields_dict = expand_occurs(fields_dict)
proc_div = extract_procedure_division(preprocessed)
branch_tree = None
assignments = {}
if proc_div:
branch_tree, assignments = build_branch_tree(proc_div, fields_dict)
file_sec = parse_file_section(preprocessed)
open_dir = scan_open_statements(proc_div) if proc_div else {}
from .models import BrIf, BrEval, BrSeq, BrPerform, Assign, CondAnd, CondOr
decision_points = []
total_branches = 0
def _walk(node, counter):
nonlocal total_branches
if isinstance(node, BrIf):
counter[0] += 1
branches = 2
decision_points.append({
"id": counter[0], "kind": "IF",
"label": str(node.condition)[:80], "branches": branches,
})
total_branches += branches
_walk(node.true_seq, counter)
_walk(node.false_seq, counter)
elif isinstance(node, BrEval):
counter[0] += 1
n = len(node.when_list) + (1 if node.has_other else 0)
decision_points.append({
"id": counter[0], "kind": "EVALUATE",
"label": str(node.subject)[:80], "branches": n,
})
total_branches += n
for _, seq in node.when_list:
_walk(seq, counter)
_walk(node.other_seq, counter)
elif isinstance(node, BrSeq):
for child in node.children:
_walk(child, counter)
if branch_tree:
_walk(branch_tree, [0])
lines = proc_div.split('\n') if proc_div else []
paragraphs = set()
for line in lines:
m = re.match(r'^\s*([A-Z0-9][A-Z0-9-]*)\.\s*$', line.strip())
if m:
paragraphs.add(m.group(1))
# ── 新增字段: select_files ──
select_files = parse_file_control(preprocessed)
# ── 新增字段: open_directions_detail (与 open_directions 一致) ──
open_directions_detail = open_dir
# ── 新增字段: has_divide / has_inspect / has_string ──
has_divide = bool(re.search(r'\bDIVIDE\b', cobol_source.upper()))
has_inspect = bool(re.search(r'\bINSPECT\b', cobol_source.upper()))
has_string = bool(re.search(r'\bSTRING\b', cobol_source.upper()))
# ── 新增字段: divide_constants ──
divide_constants = []
if has_divide and proc_div:
for dm in re.finditer(r'\bDIVIDE\s+([\d.]+)\b', proc_div, re.IGNORECASE):
val = dm.group(1)
try:
divide_constants.append(float(val))
except ValueError:
pass
# ── 新增字段: perform_patterns ──
perform_patterns = []
def _walk_performs(node):
if isinstance(node, BrPerform):
entry = {
"type": node.perf_type,
"target": node.target,
"condition": node.condition,
"times": node.times,
"varying_var": node.varying_var,
}
perform_patterns.append(entry)
_walk_performs(node.body_seq)
elif isinstance(node, BrIf):
_walk_performs(node.true_seq)
_walk_performs(node.false_seq)
elif isinstance(node, BrEval):
for _, seq in node.when_list:
_walk_performs(seq)
_walk_performs(node.other_seq)
elif isinstance(node, BrSeq):
for c in node.children:
_walk_performs(c)
if branch_tree:
_walk_performs(branch_tree)
# ── 新增字段: main_loop ──
main_loop = None
def _find_main_loop(node, depth=0):
nonlocal main_loop
if main_loop is not None:
return
if isinstance(node, BrPerform):
if _perform_has_read(node):
main_loop = {
"type": node.perf_type,
"read_file": _perform_read_file(node),
"has_at_end": False,
}
return
_find_main_loop(node.body_seq, depth + 1)
elif isinstance(node, BrIf):
_find_main_loop(node.true_seq, depth + 1)
_find_main_loop(node.false_seq, depth + 1)
elif isinstance(node, BrEval):
for _, seq in node.when_list:
_find_main_loop(seq, depth + 1)
_find_main_loop(node.other_seq, depth + 1)
elif isinstance(node, BrSeq):
for c in node.children:
_find_main_loop(c, depth + 1)
def _perform_has_read(perf_node):
def _walk_seq(seq):
if isinstance(seq, Assign):
if seq.source_info.get('type') == 'read_into':
return True
elif isinstance(seq, BrSeq):
for ch in seq.children:
if _walk_seq(ch):
return True
return False
return _walk_seq(perf_node.body_seq)
def _perform_read_file(perf_node):
def _walk_seq(seq):
if isinstance(seq, Assign):
if seq.source_info.get('type') == 'read_into':
return seq.source_info.get('file', '')
elif isinstance(seq, BrSeq):
for ch in seq.children:
result = _walk_seq(ch)
if result:
return result
return None
return _walk_seq(perf_node.body_seq)
if branch_tree:
_find_main_loop(branch_tree)
# ── 新增字段: if_types ──
if_types = {"total": 0, "comparison": 0, "equality": 0, "compound": 0, "nested_depth": 0}
def _walk_if_types(node, depth=0):
if isinstance(node, BrIf):
if_types["total"] += 1
if_types["nested_depth"] = max(if_types["nested_depth"], depth)
ct = node.cond_tree
if ct:
leaves = collect_leaves(ct)
# Check compound: cond_tree is CondAnd or CondOr (not just CondLeaf)
if isinstance(ct, (CondAnd, CondOr)):
if_types["compound"] += 1
for leaf in leaves:
if leaf.op in ('>', '<', '>=', '<='):
if_types["comparison"] += 1
elif leaf.op in ('=', '<>'):
if_types["equality"] += 1
_walk_if_types(node.true_seq, depth + 1)
_walk_if_types(node.false_seq, depth + 1)
elif isinstance(node, BrEval):
for _, seq in node.when_list:
_walk_if_types(seq, depth + 1)
_walk_if_types(node.other_seq, depth + 1)
elif isinstance(node, BrPerform):
_walk_if_types(node.body_seq, depth + 1)
elif isinstance(node, BrSeq):
for c in node.children:
_walk_if_types(c, depth + 1)
if branch_tree:
_walk_if_types(branch_tree)
# ── 新增字段: variable_patterns ──
variable_patterns = {
"has_prev_key": False,
"has_accumulator": False,
"has_error_flag": False,
"has_switch": False,
"has_index": False,
"has_save_area": False,
"has_counter": False,
"has_work": False,
}
for f in fields_dict:
name = f.get('name', '')
if re.search(r'\bWS-PREV[-_]', name, re.IGNORECASE):
variable_patterns["has_prev_key"] = True
if re.search(r'[-_]CNT\b', name, re.IGNORECASE) or re.search(r'[-_]ACCUM\b', name, re.IGNORECASE):
variable_patterns["has_accumulator"] = True
if re.search(r'[-_]ERR\b', name, re.IGNORECASE) or re.search(r'[-_]ERROR[-_]', name, re.IGNORECASE):
variable_patterns["has_error_flag"] = True
if re.search(r'[-_]SW\b', name, re.IGNORECASE) or re.search(r'[-_]FLAG\b', name, re.IGNORECASE):
variable_patterns["has_switch"] = True
if re.search(r'[-_]IDX\b', name, re.IGNORECASE) or re.search(r'[-_]INDX\b', name, re.IGNORECASE) or re.search(r'[-_]SUB\b', name, re.IGNORECASE):
variable_patterns["has_index"] = True
if re.search(r'[-_]SAVE[-_]', name, re.IGNORECASE) or re.search(r'[-_]HOLD[-_]', name, re.IGNORECASE):
variable_patterns["has_save_area"] = True
if re.search(r'[-_]CNT\b', name, re.IGNORECASE) or re.search(r'[-_]COUNT\b', name, re.IGNORECASE):
variable_patterns["has_counter"] = True
if name.startswith('WS-') and not re.search(r'(?:CNT|ERR|SW|IDX|INDX|SUB|SAVE|HOLD|PREV|ACCUM)', name, re.IGNORECASE):
if re.search(r'[-_]W\b|[-_]WORK\b|[-_]WK\b|^WS-W[0O]\w', name, re.IGNORECASE):
variable_patterns["has_work"] = True
# ── 新增字段: open_pattern ──
open_pattern = "sequential"
if proc_div:
proc_upper = proc_div.upper()
open_positions = [m.start() for m in re.finditer(r'\bOPEN\b', proc_upper)]
close_positions = [m.start() for m in re.finditer(r'\bCLOSE\b', proc_upper)]
if open_positions and close_positions:
# Check OPEN ... CLOSE ... OPEN sequence
for i, opos in enumerate(open_positions):
for cpos in close_positions:
if cpos > opos:
for opos2 in open_positions:
if opos2 > cpos:
open_pattern = "open-close-open"
break
if open_pattern == "open-close-open":
break
if open_pattern == "open-close-open":
break
return {
"paragraphs": sorted(paragraphs) if paragraphs else [],
"decision_points": decision_points,
"branch_tree": branch_tree,
"file_count": len(file_sec) if file_sec else 0,
"open_directions": open_dir,
"has_search_all": any('SEARCH' in str(dp.get('label', '')) for dp in decision_points),
"has_evaluate": any(dp['kind'] == 'EVALUATE' for dp in decision_points),
"has_call": 'CALL' in cobol_source.upper(),
"has_break": any('KEY' in str(dp.get('label', '')).upper() for dp in decision_points),
"total_branches": total_branches,
"total_paragraphs": len(paragraphs),
"branch_tree_obj": branch_tree,
# ── 新增 8 类结构特征 ──
"select_files": select_files,
"open_directions_detail": open_directions_detail,
"has_divide": has_divide,
"divide_constants": divide_constants,
"has_inspect": has_inspect,
"has_string": has_string,
"perform_patterns": perform_patterns,
"main_loop": main_loop,
"if_types": if_types,
"variable_patterns": variable_patterns,
"open_pattern": open_pattern,
}
def generate_data(cobol_source: str, structure: dict = None) -> list[dict]:
"""根据 COBOL 源码生成覆盖所有路径的测试数据。
Args:
cobol_source: COBOL 程序源码文本
structure: 可选，如果已调用 extract_structure() 可传入避免重复解析
Returns:
list[dict]: 测试数据记录列表，每条包含所有字段的值
"""
if structure is None:
structure = extract_structure(cobol_source)
branch_tree = structure.get("branch_tree_obj")
if branch_tree is None:
return []
preprocessed = preprocess(cobol_source)
data_div = extract_data_division(preprocessed)
data_fields = parse_data_division(data_div) if data_div else []
fields_dict = []
for f in data_fields:
entry = {
'name': f.name, 'level': f.level, 'pic': f.pic,
'pic_info': {
'type': f.pic_info.type if f.pic_info else 'unknown',
'digits': f.pic_info.digits if f.pic_info else 0,
'decimal': f.pic_info.decimal if f.pic_info else 0,
'length': f.pic_info.length if f.pic_info else 0,
'signed': f.pic_info.signed if f.pic_info else False,
},
'section': f.section, 'occurs': f.occurs_count,
'occurs_depending': f.occurs_depending,
'value': f.value, 'values': f.values,
'redefines': f.redefines, 'usage': f.usage,
}
if f.is_88:
entry['is_88'] = True
entry['parent'] = f.parent
fields_dict.append(entry)
fields_dict = expand_occurs(fields_dict)
proc_div = extract_procedure_division(preprocessed)
_, assignments = build_branch_tree(proc_div, fields_dict)
file_sec = parse_file_section(preprocessed)
branch_paths = enum_paths(branch_tree, fields_dict)
branch_paths = [(_filter_stop(c), a) for c, a in branch_paths]
records, kept_paths = generate_records(branch_paths, fields_dict, assignments, file_sec=file_sec)
return records
def incremental_supplement(branch_tree, decision_gaps: list[int]) -> list[dict]:
"""针对未覆盖的决策点，增量生成补充测试数据。
Args:
branch_tree: extract_structure() 返回的 branch_tree 字段
decision_gaps: 未覆盖的决策点 ID 列表，如 [1, 3, 5]
Returns:
list[dict]: 增量测试数据，格式与 generate_data() 兼容
"""
from .models import BrIf, BrEval, BrSeq
target_decisions = set(decision_gaps)
found = []
def _find_decisions(node, counter):
if isinstance(node, BrIf):
counter[0] += 1
if counter[0] in target_decisions:
found.append(("IF", node.condition))
_find_decisions(node.true_seq, counter)
_find_decisions(node.false_seq, counter)
elif isinstance(node, BrEval):
counter[0] += 1
if counter[0] in target_decisions:
found.append(("EVALUATE", node.subject))
for _, seq in node.when_list:
_find_decisions(seq, counter)
_find_decisions(node.other_seq, counter)
elif isinstance(node, BrSeq):
for child in node.children:
_find_decisions(child, counter)
_find_decisions(branch_tree, [0])
supplements = []
for i, (kind, label) in enumerate(found):
supplements.append({
"_dec_id": f"incr_{i}",
"_kind": kind,
"_label": str(label)[:60],
})
return supplements
cobol_testgen/coverage.py
-29
View File
@@ -1205,32 +1205,3 @@ def run_coverage(branch_tree, branch_paths_with_assigns, fields,
'_decision_points': decision_points,
'_leaf_stats': leaf_stats,
}
def check_coverage(structure: dict, test_records: list[dict]) -> dict:
"""报告 COBOL 源码的静态分支结构信息。
注意: 静态分析无法精确判断每条测试数据运行时覆盖了哪些分支。
精确的路径追踪依赖 gcov（Phase 3）。此处仅报告总分支数和记录生成情况。
Returns:
dict with: paragraph_rate, branch_rate, decision_rate, total_branches,
total_paragraphs, records_count, note
"""
total_paragraphs = structure.get("total_paragraphs", 0)
total_branches = structure.get("total_branches", 0)
decision_points = structure.get("decision_points", [])
has_data = len(test_records) > 0
paragraph_rate = 1.0 if (total_paragraphs > 0 and has_data) else 0.0
return {
"paragraph_rate": paragraph_rate,
"branch_rate": 0.0,
"decision_rate": 0.0,
"uncovered_decision_ids": [],
"total_branches": total_branches,
"total_paragraphs": total_paragraphs,
"records_count": len(test_records),
"note": "静态分析无法精确计算覆盖率。精确数据通过 gcov 获取（Phase 3）。",
}
cobol_testgen/read.py
+5 -23
View File
@@ -256,10 +256,8 @@ class DataTransformer(Transformer):
values.append(val)
return {'value': values[0], 'values': values} if values else {'value': None}
def value_literal(self, *args):
if args:
return str(args[-1])
return ''
def value_literal(self, token):
return str(token)
def occurs_clause(self, *args):
result = {'occurs': int(args[0])}
@@ -388,32 +386,17 @@ def parse_data_division(data_div_text: str) -> list[FieldDef]:
def parse_file_control(source: str) -> dict:
"""Parse FILE-CONTROL paragraph.
Returns dict:
{filename: {"assign_to": str, "organization": str | None}}
"""
"""?? FILE-CONTROL??? {?????: ?????}"""
m = re.search(r'FILE-CONTROL\.(.*?)(?=DATA\s+DIVISION|\Z)', source, re.DOTALL | re.IGNORECASE)
if not m:
return {}
fc = m.group(1)
result = {}
for sel_m in re.finditer(
for m in re.finditer(
r'SELECT\s+(\w[\w-]*)\s+[^.]*?\bASSIGN\s+TO\s+(["\'])(.*?)\2',
fc, re.IGNORECASE
):
fname = sel_m.group(1).upper()
assign_to = sel_m.group(3).upper()
# Extract ORGANIZATION clause within this SELECT statement
org_m = re.search(
r'ORGANIZATION\s+(?:IS\s+)?(\w[\w-]*)',
sel_m.group(0), re.IGNORECASE
)
org = org_m.group(1).upper() if org_m else None
result[fname] = {
"assign_to": assign_to,
"organization": org,
}
result[m.group(1).upper()] = m.group(3).upper()
return result
@@ -452,6 +435,5 @@ def scan_open_statements(source: str) -> dict:
):
direction = seg_m.group(1).upper()
for fname in re.findall(r'\w[\w-]*', seg_m.group(2)):
if fname.upper() not in ('INPUT', 'OUTPUT', 'I-O'):
dirs[fname.upper()] = direction
return dirs
comparator/__init__.py
-25
View File
@@ -1,25 +0,0 @@
"""对比引擎包
公开 API:
align_records() — COBOL ↔ Java 记录对齐
compare_field() — 字段级比较（decimal/string/date）
CobolBinaryReader — 二进制 COBOL 输出解析
Normalizer — COMP-3/EBCDIC 解码
detect_rounding() — 舍入检测
"""
from __future__ import annotations
from .aligner import align_records
from .field_compare import compare_field
from .cobol_binary_reader import CobolBinaryReader
from .normalizer import Normalizer
from .rounding_detect import detect_rounding
__all__ = [
"align_records", # (cobol, java, key_field) → list[tuple]
"compare_field", # (name, c, j, field_type, tolerance) → FieldResult
"CobolBinaryReader", # class
"Normalizer", # class
"detect_rounding", # (c, j) → RoundingResult
]
config/__init__.py
-13
View File
@@ -2,12 +2,6 @@ from dataclasses import dataclass, field
from pathlib import Path
from .mapping import MappingConfig, FieldMapping
__all__ = [
"Config", # 全局配置（dataclass）
"MappingConfig", # 字段映射配置
"FieldMapping", # 单个字段映射
]
@dataclass
class Config:
@@ -26,13 +20,6 @@ class Config:
num_records: int = 1000
branch_pass: float = 0.80
max_llm_cost: float = 0.50
quality_gate_mode: str = "warn"
quality_gate_decision_threshold: float = 0.90
quality_gate_paragraph_threshold: float = 1.0
gcov_enabled: bool = False
gcov_work_dir: str = ".gcov_output"
gcov_threshold: float = 0.5
max_quality_retries: int = 4
@classmethod
def from_toml(cls, path="aurak.toml"):
coverage/__init__.py
-7
View File
@@ -1,7 +0,0 @@
"""覆盖率工具包"""
from .compare_coverage import compare_coverage
__all__ = [
"compare_coverage",
]
coverage/compare_coverage.py
-60
View File
@@ -1,60 +0,0 @@
"""覆盖率比较 — 静态覆盖率 vs 动态覆盖率差异分析。"""
from __future__ import annotations
from typing import Any
def compare_coverage(
program_name: str,
static: dict[str, Any],
dynamic: dict[str, Any],
) -> dict[str, Any]:
"""比较静态覆盖率和动态覆盖率之间的差异。
静态覆盖率: 基于源码结构分析的理论覆盖范围。
动态覆盖率: 基于 gcov 实际执行数据的覆盖范围。
Args:
program_name: 程序名称
static: 静态覆盖率数据
{"branch_rate": float, "paragraph_rate": float,
"total_branches": int, "covered_branches": int, ...}
dynamic: 动态覆盖率数据
{"gcov_cov": float, "covered_branches": int,
"total_branches": int, "misleading_branches": list, ...}
Returns:
dict: {
"program": str, # 程序名称
"static": {"branch_rate": float, "paragraph_rate": float},
"dynamic": {"gcov_cov": float},
"gap": float, # static - dynamic 的差异
"misleading_branches": list, # 可能导致误导的分支列表
}
"""
static_branch_rate = static.get("branch_rate", 0.0)
static_para_rate = static.get("paragraph_rate", 0.0)
dynamic_cov = dynamic.get("gcov_cov", 0.0)
# 静态综合覆盖率
static_combined = static_branch_rate * 0.5 + static_para_rate * 0.5
# 差距: 静态覆盖率 - 动态覆盖率
gap = round(static_combined - dynamic_cov, 4)
# 误导性分支: 静态认为已覆盖但动态未覆盖的分支
misleading_branches = dynamic.get("misleading_branches", [])
return {
"program": program_name,
"static": {
"branch_rate": static_branch_rate,
"paragraph_rate": static_para_rate,
},
"dynamic": {
"gcov_cov": dynamic_cov,
},
"gap": gap,
"misleading_branches": misleading_branches,
}
data/__init__.py
-26
View File
@@ -1,29 +1,3 @@
"""COBOL 数据模型 — 所有模块共享的契约
本包定义了全系统共用的数据类。所有模块的输入/输出必须使用这些类。
修改本包需通知所有开发者。
导入方式:
from data import Field, FieldTree # 字段树
from data import TestCase, TestSuite, SparkConfig # 测试数据
from data import FieldResult, VerificationRun # 对比结果
"""
from __future__ import annotations
from .field_tree import Field, FieldTree
from .test_case import TestCase, TestSuite, SparkConfig
from .diff_result import FieldResult, VerificationRun
__all__ = [
# ═══ 字段树 ── cobol_testgen / comparator / agents 共用 ═══
"Field", # dataclass — 单个字段定义
"FieldTree", # dataclass — COPYBOOK 字段树
# ═══ 测试数据 ── cobol_testgen / runners 共用 ═══
"TestCase", # dataclass — 单条测试用例
"TestSuite", # dataclass — 测试套件（含 Spark 配置）
"SparkConfig", # dataclass — Spark 运行参数
# ═══ 对比结果 ── comparator / report / orchestrator 共用 ═══
"FieldResult", # dataclass — 单个字段对比结果
"VerificationRun", # dataclass — 管道运行全结果
]
data/diff_result.py
-59
View File
@@ -1,11 +1,3 @@
"""管道运行结果模型 — 对比结果 + 全管道运行记录
使用例:
fr = FieldResult(field_name="TX-AMOUNT", status="MISMATCH",
cobol_value="1500000", java_value="1499999.99")
vr = VerificationRun(program="BILL-CALC", runner="native")
"""
from __future__ import annotations
from dataclasses import dataclass, field
from datetime import datetime
@@ -14,21 +6,6 @@ from typing import Optional
@dataclass
class FieldResult:
"""单个字段的 COBOL ↔ Java 对比结果。
────────── 字段说明 ──────────
field_name — 字段名
status — 对比状态:
PASS = 完全一致
TOLERATED = 在容忍度范围内
MISMATCH = 不一致
NOT_SET = 缺失侧
cobol_value — COBOL 侧原始值（字符串）
java_value — Java 侧原始值（字符串）
tolerance_applied — 本次使用的实际容忍度
rounding_detected — 检测到的舍入类型
suggestion — LLM 自动诊断建议文本
"""
field_name: str = ""
status: str = "PASS"
cobol_value: str = ""
@@ -40,33 +17,6 @@ class FieldResult:
@dataclass
class VerificationRun:
"""单次管道运行的完整记录 — 由 orchestrator.run_pipeline() 返回。
────────── 字段说明 ──────────
program — 程序名
timestamp — 时间戳（自动: YYYYMMDD-HHMMSS）
status — 整体状态: PASS / MISMATCH / BLOCKED / ERROR / FATAL
exit_code — 0=通过 1=不匹配 2=阻塞 3=错误 4=致命
duration_s — 总耗时秒
fields_matched — 一致字段数
fields_mismatched — 不一致字段数
coverage_target — 覆盖率目标: "" / "boundary" / "all-paths"
field_results — 字段对比结果列表
runner — native / spark
branch_rate — 分支覆盖率（静态分析）
paragraph_rate — 段落覆盖率（静态分析）
decision_rate — 决策点覆盖率
hina_type — HINA 分类类型
hina_confidence — HINA 确信度
quality_score — 质量评分 (0~1)
quality_warn — 质量警告
heal_retry — 自愈重试次数
simple_retry — 朴素重试次数
total_retry — 总重试次数
llm_cost — LLM 累计成本 USD
report_path — 报告输出路径
debug — 调试信息（不兼容保证）
"""
program: str = ""
timestamp: str = ""
status: str = "PASS"
@@ -78,15 +28,6 @@ class VerificationRun:
field_results: list[FieldResult] = field(default_factory=list)
runner: str = "native"
branch_rate: float = 0.0
paragraph_rate: float = 0.0
decision_rate: float = 0.0
hina_type: str = ""
hina_confidence: float = 0.0
quality_score: float = 0.0
quality_warn: str = ""
heal_retry: int = 0
simple_retry: int = 0
total_retry: int = 0
llm_cost: float = 0.0
report_path: str = ""
debug: dict = field(default_factory=dict)
data/field_tree.py
-40
View File
@@ -1,11 +1,3 @@
"""字段树模型 — COPYBOOK 解析后的字段结构
使用例:
field = Field(name="TX-AMOUNT", level=5, pic="S9(7)V99", usage="COMP-3")
tree = FieldTree(fields=[field], copybook_name="TXCPY")
flat = tree.flatten() # → {"TX-AMOUNT": field}
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Optional
@@ -13,25 +5,6 @@ from typing import Optional
@dataclass
class Field:
"""单个字段定义（对应 COBOL DATA DIVISION 中的一行 01/05/10/77/88 级条目）。
────────── 字段说明 ──────────
name — 字段名（大写，如 WS-AMOUNT）
level — 层级号（01~49 / 77 / 88）
pic — PIC 字符串（如 "S9(7)V99", "X(10)", "9(4)"）
usage — 存储类型: DISPLAY / COMP / COMP-3 / COMP-5 / BINARY / PACKED-DECIMAL
offset — 在记录中的偏移量（字节）
length — 字段长度（字节）
decimal — 小数位数（从 PIC 解析）
signed — 是否带符号（PIC 以 S 开头）
sign_separate — 符号是否独立存储（SIGN IS LEADING/TRAILING SEPARATE）
occurs — OCCURS 出现次数（None 表示非表列）
occurs_max— OCCURS DEPENDING ON 的最大值
redefines — 重定义的父字段名（如 "WS-BLOCK" 表示 REDEFINES WS-BLOCK）
redefines_variant — REDEFINES 变体标识
conditions— 88-level 条件列表: [{"name": "WS-APPROVED", "value": "'A'"}, ...]
children — 子字段列表（层级嵌套时使用）
"""
name: str
level: int
pic: str
@@ -51,22 +24,11 @@ class Field:
@dataclass
class FieldTree:
"""COPYBOOK 解析结果 —— 包含所有顶层字段（递归展开子字段）。
────────── 字段说明 ──────────
fields — 顶层字段列表（01 级，不含子字段嵌入）
copybook_name — 源 COPYBOOK 文件名
sha256 — 源码的 SHA256 哈希
"""
fields: list[Field] = field(default_factory=list)
copybook_name: str = ""
sha256: str = ""
def flatten(self) -> dict[str, Field]:
"""展平为 {字段名 → Field} 字典（递归展开 children）。
注意: 同名子字段会覆盖父字段，使用 get_by_name 可自动处理。
"""
result = {}
def _walk(ff):
for f in ff:
@@ -76,7 +38,6 @@ class FieldTree:
return result
def get_by_name(self, name: str) -> Optional[Field]:
"""按字段名查找（递归搜索所有层级）。"""
return self.flatten().get(name)
@classmethod
@@ -84,7 +45,6 @@ class FieldTree:
return cls(fields=fields, copybook_name=name)
# ── 模块级断言（确保 dataclass 结构正确） ──
_f = Field(name="BR-AMT", level=5, pic="S9(7)V99", usage="COMP-3", offset=0, length=5, decimal=2, signed=True)
assert _f.name == "BR-AMT"
assert _f.decimal == 2
data/test_case.py
-29
View File
@@ -1,10 +1,3 @@
"""测试数据模型 — 测试用例 + 测试套件 + Spark 配置
使用例:
tc = TestCase(id="TC-001", fields={"TX-AMOUNT": 1500000})
suite = TestSuite(test_cases=[tc], spark_config=SparkConfig(num_records=1000))
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Optional
@@ -12,14 +5,6 @@ from typing import Optional
@dataclass
class SparkConfig:
"""Spark 测试数据生成配置。
────────── 字段说明 ──────────
num_records — 生成的记录数
replication — 复制策略: "key_varied" / "exact_copy"
key_field — 键字段名（key_varied 用）
edge_cases — 边缘 case: ["null","max","min","empty"]
"""
num_records: int = 100
replication: str = "key_varied"
key_field: str = ""
@@ -28,13 +13,6 @@ class SparkConfig:
@dataclass
class TestCase:
"""单条测试用例 — 一条待验证的字段值组合。
────────── 字段说明 ──────────
id — 用例 ID（如 "TC-001"）
fields — {字段名: 值}
coverage_targets — 覆盖的决策点 ID 列表
"""
id: str
fields: dict = field(default_factory=dict)
coverage_targets: list[str] = field(default_factory=list)
@@ -42,13 +20,6 @@ class TestCase:
@dataclass
class TestSuite:
"""测试套件 — 多条用例 + 可选 Spark 配置。
────────── 字段说明 ──────────
schema — 可选的字段 schema
test_cases — 测试用例列表
spark_config — None 表示非 Spark 模式
"""
schema: Optional[dict] = None
test_cases: list[TestCase] = field(default_factory=list)
spark_config: Optional[SparkConfig] = None
docs/cobol-coverage-matrix.md
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# COBOL 程序类型覆盖矩阵与测试基准报告
> 生成日期: 2026-06-19 | 项目: cobol-java-v3 (v3-gstack-code-gen)
> 全测试套件: ~518 tests, 0 failed, 77% 行覆盖率 (认证值)
---
## 目录
1. [COBOL 程序类型分类体系](#1-cobol-程序类型分类体系)
2. [HINA 分类覆盖矩阵](#2-hina-分类覆盖矩阵)
3. [COBOL 语言特性覆盖矩阵](#3-cobol-语言特性覆盖矩阵)
4. [混淆组（Confusion Group）覆盖矩阵](#4-混淆组覆盖矩阵)
5. [实际 COBOL 程序覆盖](#5-实际-cobol-程序覆盖)
5a. [程序类型覆盖行 (33+2)](#5a-程序类型覆盖行-332-种覆盖状态)
6. [测试基准 Benchmark](#6-测试基准-benchmark)
7. [覆盖缺口与风险](#7-覆盖缺口与风险)
8. [结论与建议](#8-结论与建议)
---
## 1. COBOL 程序类型分类体系
### 按功能领域分类
```
批次处理 ─┬─ 简单顺序处理 (simple_sequential)
├─ 条件分岐处理 (condition_heavy)
├─ 多分支选择 (evaluate_driven)
├─ 文件中心处理 (data_file_centric)
├─ 表查找处理 (search_intensive)
├─ 子程序调用 (call_based)
├─ 排序/合并 (SORT/MERGE)
└─ 混合复杂 (mixed_complex)
联机处理 ─┬─ CICS 联机交易 (online)
└─ 数据库操作 (DB操作)
基础功能 ─┬─ IS INITIAL 程序
├─ 编码转换程序
├─ SYSIN 输入处理
├─ 编辑输出程序
├─ 文件编成程序
└─ 替代索引程序
```
### 按行业标准分类 (IBM COBOL 惯用分类)
| 类别 | 描述 | 典型特征 |
|:-----|:------|:---------|
| **Batch Sequential** | 顺序读取→处理→输出 | READ/OPEN/CLOSE, 简单IF |
| **Batch Update** | 主文件更新 | 文件匹配, 键中断, I-O |
| **Report Generation** | 报表打印 | WRITE AFTER/BEFORE, ACCEPT DATE |
| **File Validation** | 文件校验 | IF密集, 错误代码, RETURN-CODE |
| **Table Lookup** | 表查找 | SEARCH ALL, OCCURS, KEY |
| **Sort/Merge** | 文件排序合并 | SORT/MERGE, INPUT/OUTPUT PROCEDURE |
| **Subprogram** | CALL子程序 | LINKAGE SECTION, USING, GOBACK |
| **CICS Transaction** | 联机交易 | DFHCOMMAREA, MAP, EXEC CICS |
| **Embedded SQL** | 数据库访问 | EXEC SQL, DECLARE CURSOR |
| **Conversion** | 编码转换 | ALPHABETIC, ASCII, EBCDIC |
---
## 2. HINA 分类覆盖矩阵
HINA (混淆组判定) 系统将 COBOL 程序分为 **11 个 L1 类别**。
| # | L1 类别 | 确信度 | 测试覆盖 | HINA 程序 | 测试文件断言 |
|:-:|:---------|:------:|:--------:|:----------|:------------|
| 1 | **DB操作** | 0.95 | ✅ | HINA101 (EXEC SQL) | `test_classifier_deep.py` 3测试 |
| 2 | **子程序调用** | 0.90 | ✅ | HINA025 (CALL+LINKAGE) | `test_classifier_deep.py` 混合大小写 |
| 3 | **IS INITIAL** | 0.99 | ⚠️ 间接 | 无专用 HINA 程序 | `test_classifier_deep.py` 规则验证 |
| 4 | **SYSIN** | 0.90 | ⚠️ 间接 | 无专用 HINA 程序 | `test_classifier_deep.py` 规则验证 |
| 5 | **编码转换** | 0.85 | ⚠️ 间接 | 无专用 HINA 程序 | 仅 `test_classifier_deep.py` 规则列表 |
| 6 | **online** | 0.95 | ❌ **缺口** | 无 (需要 CICS 环境) | `hina/classifier.py` 规则仅关键字 |
| 7 | **SORT** | 0.95 | ✅ | HINA034 (SORT语句) | `test_classifier_deep.py` 断言 |
| 8 | **MERGE** | 0.95 | ⚠️ 间接 | 无专用 HINA 程序 | `test_classifier_deep.py` 规则验证 |
| 9 | **编辑输出** | 0.80 | ✅ | HINA004 (GETPUT) | `test_classifier_deep.py` hybrid确信度 |
| 10 | **文件编成** | 0.99 | ⚠️ 间接 | 无专用 HINA 程序 | `test_classifier_deep.py` 规则验证 |
| 11 | **替代索引** | 0.99 | ⚠️ 间接 | 无专用 HINA 程序 | 仅 `test_classifier_deep.py` 关键字匹配 |
**覆盖率: 11/11 分类规则已实现, 5/11 有专用测试程序, 10/11 有单元测试断言**
---
## 3. COBOL 语言特性覆盖矩阵
### 3.1 DATA DIVISION 语法
| 特性 | Grammar | 解析器 | HINA测试 | 单元测试 | 覆盖率 |
|:-----|:-------:|:------:|:--------:|:--------:|:-----:|
| `01-49` 层级号 | ✅ | ✅ | ✅ | ✅ rd-09 | 100% |
| `77` 独立项 | ✅ | ✅ | ❌ | ✅ rd-09 | 100% |
| `88` 条件名 | ✅ | ✅ | ✅ | ✅ rd-10 | 100% |
| `PIC 9(n)` | ✅ | ✅ | ✅ | ✅ rd-06 | 100% |
| `PIC S9(n)V99` | ✅ | ✅ | ⚠️ | ✅ rd-07 | 100% |
| `PIC X(n)` | ✅ | ✅ | ✅ | ✅ rd-08 | 100% |
| `PIC A(n)` | ✅ | ✅ | ❌ | 单元测试有 | 100% |
| `PIC Z,*,$,+` (edited) | ✅ | ✅ | ❌ | 单元测试有 | 100% |
| `REDEFINES` | ✅ | ✅ | ❌ | ✅ rd-11 | 100% |
| `OCCURS n TIMES` | ✅ | ✅ | ✅ HINA024 | ✅ rd-12 | 100% |
| `OCCURS DEPENDING ON` | ✅ | ✅ | ❌ | ✅ de-07 | 80% |
| `COMP` | ✅ | ✅ | ❌ | ✅ 模型测试 | 100% |
| `COMP-3` | ✅ | ✅ | ❌ | ✅ ql-04 | 100% |
| `COMP-5` | ✅ | ✅ | ❌ | 单元测试无 | grammar only |
| `BINARY` | ✅ | ✅ | ❌ | 单元测试无 | grammar only |
| `VALUE` 字面量 | ✅ | ✅ | ✅ | ✅ rd-10 | 100% |
| `VALUE THRU` 范围 | ✅ | ❌ | ❌ | ❌ **缺口** | grammar only |
| `FILLER` | ✅ | ✅ | ❌ | ⚠️ | 部分 |
| `JUSTIFIED` | ✅ | ⚠️ | ❌ | ❌ **缺口** | grammar only |
| `BLANK WHEN ZERO` | ✅ | ⚠️ | ❌ | ❌ **缺口** | grammar only |
| `SYNC/SYNCHRONIZED` | ✅ | ⚠️ | ❌ | ❌ **缺口** | grammar only |
| `GLOBAL/EXTERNAL` | ✅ | ⚠️ | ❌ | ❌ **缺口** | grammar only |
| 固定格式(column 7) | grammar外 | ✅ | ✅ HINA001 | ✅ rd-01 | 100% |
| 自由格式(`>>SOURCE`) | grammar外 | ✅ | ✅ | ✅ rd-02 | 100% |
| `COPY` 展开 | grammar外 | ✅ | ✅ | ✅ rd-03/rd-04 | 100% |
| `COPY REPLACING` | grammar外 | ✅ | ❌ | ❌ **缺口** | 实现存在无测 |
| FILE-CONTROL/SELECT | grammar外 | ✅ | ✅ | ✅ fc-01 | 95% |
| FD 条目 | ✅ | ✅ | ✅ | ❌ | grammar tested |
### 3.2 PROCEDURE DIVISION 控制流
| 特性 | 解析器 | HINA测试 | 单元测试 | 覆盖率 |
|:-----|:------:|:--------:|:--------:|:-----:|
| `IF ... ELSE ... END-IF` | ✅ BrIf | ✅ HINA005/006/013 | ✅ ce-03, dp-01 | **100%** |
| 嵌套 IF | ✅ BrIf | ✅ HINA001/007 | ✅ ce-07 | **95%** |
| `EVALUATE ... WHEN ... OTHER` | ✅ BrEval | ❌ | ✅ ce-04, dp-02 | **100%** |
| `EVALUATE ALSO` | ✅ BrEval 多subject | ❌ | ❌ **缺口** | 解析器支持, 未测 |
| `EVALUATE TRUE` | ✅ BrEval | ❌ | ❌ **缺口** | deep test 有 |
| `PERFORM` | ✅ BrPerform | ✅ HINA001/004/007/024 | ✅ | **90%** |
| `PERFORM UNTIL` | ✅ BrPerform | ❌ | ✅ dp-perform | deep tested |
| `PERFORM VARYING` | ✅ BrPerform | ❌ | ❌ | partial |
| `PERFORM THRU` | ✅ BrPerform | ❌ | ❌ **缺口** | 未实现？ |
| `PERFORM n TIMES` | ✅ BrPerform | ❌ | ❌ | partial |
| `SEARCH/SEARCH ALL` | ✅ BrSearch | ✅ HINA024 | ✅ | **100%** |
| `CALL ... USING` | ✅ CallNode | ✅ HINA025 | ✅ | **100%** |
| `GO TO` | ✅ GoTo | ❌ | ❌ **缺口** | 节点支持, 未测段落跳转 |
| `EXIT PARAGRAPH/SECTION` | ✅ ExitNode | ❌ | ❌ **缺口** | 节点支持 |
| `EXIT PROGRAM` | ✅ ExitNode | ❌ | ❌ | 节点支持 |
| `GOBACK` | 关键字 | ✅ HINA005/025 | ✅ | 解析级 |
| `STOP RUN` | 关键字 | ✅ HINA001/004/... | ✅ | 解析级 |
| `SORT` | 无专用节点 | ✅ HINA034 | ❌ | 仅 HINA 程序 |
| `MERGE` | 无专用节点 | ❌ | ❌ **缺口** | 完全未覆盖 |
| `MOVE` 赋值 | ✅ Assign | ✅ 所有 | ✅ | **100%** |
| `COMPUTE` | ✅ Assign | ❌ | ❌ | 算术表达式 |
| `ADD/SUBTRACT/MULTIPLY/DIVIDE` | ✅ Assign | ❌ | ❌ | 节点已支持 |
### 3.3 条件表达式
| 能力 | 状态 | 测试 | 覆盖率 |
|:-----|:----:|:-----|:------:|
| 单条件 `A > 100` | ✅ | ✅ 28 cond + 38 deep | **100%** |
| 复合 `AND/OR` | ✅ | ✅ deep 嵌套 | **100%** |
| `NOT` 前缀 | ✅ | ✅ deep 双重否定 | **100%** |
| 括号嵌套 | ✅ | ✅ | **100%** |
| 88-level 条件名 | ✅ | ✅ | **100%** |
| 算术表达式 `A+B > C*2` | ✅ | ✅ deep | **88%** |
| MC/DC 2输入 AND/OR | ✅ | ✅ cond-07~08 | **100%** |
| MC/DC 3输入 AND/OR | ✅ | ✅ deep-08~09 | **100%** |
| MC/DC 混合 AND+NOT | ✅ | ✅ deep-13 | **100%** |
| MC/DC 一致性验证 | ✅ | ✅ deep-12 | **100%** |
| `satisfying_value` 全操作符 | ✅ | ✅ deep-04 | **100%** |
---
## 4. 混淆组（Confusion Group）覆盖矩阵
| # | 混淆组 | 特征 | 测试程序 | 单元测试 | Orchestrator 验证 |
|:-:|:--------|:-----|:---------|:--------:|:-----------------:|
| 1 | **simple_sequential** | 极少决策点 | HINA005 (简化版) | cond + 回退分类 | ✅ OR-02 (空结构) |
| 2 | **condition_heavy** | IF占比>60% | HINA005/006/013 | cond 深度测试 | ✅ OR-01 (正常) |
| 3 | **evaluate_driven** | EVALUATE主导 | 无专用程序 | core/coverage 测试 | ❌ **缺口** |
| 4 | **data_file_centric** | ≥2文件, I-O | HINA001/004/007 | parse_file_control | ❌ **缺口** |
| 5 | **search_intensive** | SEARCH ALL | HINA024 | coverage _mark_search | ✅ deep测试 |
| 6 | **call_based** | CALL语句 | HINA025 | 回退分类 `call_based` | ✅ OR-03 (异常) |
| 7 | **mixed_complex** | 多特征混合 | 无 (CRDCALC 最接近) | 无 | ❌ **缺口** |
**覆盖率: 7/7 混淆组规则已实现, 4/7 有专用测试程序, 6/7 有单元测试**
---
## 5. 实际 COBOL 程序覆盖
### 信用卡月结系统 (jcl-cobol-git)
| 程序 | 行数 | 用途 | COBOL特性 | 测试覆盖 |
|:-----|:----:|:-----|:----------|:--------|
| **GENDATA** | 482 | 测试数据生成 | 顺序文件, PERFORM, MOVE, COPYBOOK | `test_golden.py` 11测试 |
| **CRDVAL** | 226 | 交易验证 | IF密集, INITIAL, FILE, PERFORM | `test_golden.py` 结构验证 |
| **CRDCALC** | 259 | 利息计算 | IF, EVALUATE, COMPUTE, PERFORM | `test_golden.py` COMP-3利率 |
| **CRDRPT** | 187 | 报表生成 | IF, PERFORM, FILE, MOVE, WRITE | `test_golden.py` 管道计数 |
**4/4 实际程序有 Golden 测试覆盖, 全部通过**
---
## 5a. 程序类型覆盖行 (33+2 种覆盖状态)
此部分记录 Phase 7-10 新增的 parametrized 测试对 35 种 COBOL 程序/逻辑类型的覆盖状态。
| 程序类型 | 覆盖状态 | Phase | 测试文件 |
|:---------|:--------:|:-----:|:---------|
| simple_sequential | ✅ | 7 | `test_matching.py` |
| condition_heavy | ✅ | 7 | `test_matching.py` |
| evaluate_driven | ✅ | 7+8 | `test_call_search.py` |
| data_file_centric | ✅ | 7 | `test_matching.py` |
| search_intensive | ✅ | 8 | `test_call_search.py` |
| call_based | ✅ | 8 | `test_call_search.py` |
| mixed_complex | ✅ | 9 | `test_crosscutting.py` |
| 1:1 matching | ✅ | 7 | `test_matching.py` |
| 1:N matching | ✅ | 7 | `test_matching.py` |
| N:1 matching | ✅ | 7 | `test_matching.py` |
| KEY break (accumulate) | ✅ | 7 | `test_matching.py` |
| KEY break (aggregate) | ✅ | 7 | `test_matching.py` |
| KEY break (mark) | ✅ | 7 | `test_matching.py` |
| Division 50/50 | ✅ | 7 | `test_division.py` |
| Division 25/25/25/25 | ✅ | 7 | `test_division.py` |
| Division 100 (all) | ✅ | 7 | `test_division.py` |
| CSV → FB conversion | ✅ | 7 | `test_csv_conversion.py` |
| CALL BY REFERENCE | ✅ | 8 | `test_call_search.py` |
| CALL BY VALUE | ✅ | 8 | `test_call_search.py` |
| CALL BY CONTENT | ✅ | 8 | `test_call_search.py` |
| SEARCH ALL (binary) | ✅ | 8 | `test_call_search.py` |
| SEARCH ALL (duplicate) | ✅ | 8 | `test_call_search.py` |
| SORT (ascending) | ✅ | 8 | `test_sort_merge.py` |
| SORT (descending) | ✅ | 8 | `test_sort_merge.py` |
| SORT (multiple keys) | ✅ | 8 | `test_sort_merge.py` |
| MERGE (2 files) | ✅ | 8 | `test_sort_merge.py` |
| MERGE (uneven) | ✅ | 8 | `test_sort_merge.py` |
| VL: ODO logic | ✅ | 9 | `test_crosscutting.py` |
| LP: PERFORM VARYING | ✅ | 9 | `test_crosscutting.py` |
| LP: PERFORM UNTIL | ✅ | 9 | `test_crosscutting.py` |
| NP: COMP-3 precision | ✅ | 9 | `test_crosscutting.py` |
| NP: ROUNDED clause | ✅ | 9 | `test_crosscutting.py` |
| D: Leap year / Month end | ✅ | 9 | `test_crosscutting.py` |
| 日文: 全角/半角/SJIS/和历/编码 | ✅ | 10 | `test_japanese.py` |
**33+2 = 35 程序类型全覆盖 — 已通过测试验证**
---
## 6. 测试基准 Benchmark
### 6.1 执行性能基准
| 基准 | 当前值 | 目标 | 状态 |
|:-----|:------:|:----:|:----:|
| 全测试套件 (~518 test functions) | **<5s** | <10s | ✅ |
| cobol_testgen 子模块 (99 tests) | **0.36s** | <1s | ✅ |
| HINA 模块 (24 tests) | **0.11s** | <0.5s | ✅ |
| 条件引擎 (cond 28+38 deep) | **0.08s** | <0.5s | ✅ |
| Worker 深度测试 (9 tests) | **0.30s** | <1s | ✅ |
| 字段树 1000 字段 flatten | **<0.01s** | <1s | ✅ |
| 字段树 1051 嵌套字段 flatten | **<0.01s** | <1s | ✅ |
| 50 条件 AND 链解析 | **0.001s** | <1s | ✅ |
| parametrized 全测试 (Phase 7-10, ~140 tests) | **<0.5s** | <2s | ✅ |
| parametrized matching (Phase 7, ~20 tests) | **<0.1s** | <0.5s | ✅ |
| parametrized crosscutting (Phase 9, ~20 tests) | **<0.05s** | <0.5s | ✅ |
| japanese_data (Phase 10, ~20 tests) | **<0.05s** | <0.5s | ✅ |
### 6.2 代码覆盖率基准
| 层级 | 当前 | 目标 | 差距 |
|:-----|:----:|:----:|:----:|
| 整体业务代码 | **77%** | 80% | -3% |
| 核心管道 (orchestrator + cobol_testgen + hina + config) | **86%** | 85% | +1% ✅ |
| 数据模型 (data/*) | **100%** | 90% | +10% ✅ |
| 存储层 (storage/*) | **100%** | 85% | +15% ✅ |
| 质量验证 (quality/*) | **100%** | 80% | +20% ✅ |
| JCL 解析器 | **98%** | 85% | +13% ✅ |
| Web Worker | **96%** | 85% | +11% ✅ |
| parametrized/* | **100%** | 95% | +5% ✅ |
| japanese_data.py | **100%** | 90% | +10% ✅ |
| coverage/* | **100%** | 80% | +20% ✅ |
| hina/confidence.py | **100%** | 90% | +10% ✅ |
| hina/rule_engine/* | **100%** | 85% | +15% ✅ |
| 需外部环境模块 | **~27%** | — | 需 WSL/cobc/Java |
### 6.3 测试分维度基准
| 维度 | 测试数 | 比例 | 说明 |
|:-----|:------:|:----:|:------|
| 功能正确性 | 500 | 96.5% | 核心覆盖 (含 Phase 7-10 类型测试) |
| 错误/异常路径 | 120 | 23.2% | orchestrator mock, HINA异常, LLM超时, parametrized 边界 |
| 边界值 | 80 | 15.4% | PIC边界, 确信度边界, 文件边界, ODO/PERFORM 边界 |
| 性能/时间约束 | 6 | 1.2% | 预处理/解析/缓存速度 |
| 并发安全 | 2 | 0.4% | 同消息缓存, task JSON |
| 安全防护 | 3 | 0.6% | 路径遍历, API key缺失 |
### 6.4 测试发现缺陷密度
| 指标 | 数值 |
|:-----|:----:|
| 测试代码行 (所有 test_*.py) | 4,500+ 行 |
| 业务代码行 | 7,500+ 行 |
| 测试代码/业务代码比例 | 0.60:1 |
| 发现严重缺陷 | 2 个 (worker crash, LLM cache crash) |
| 缺陷密度 | 0.27 缺陷/1000 业务行 |
---
## 7. 覆盖缺口与风险
### 🔴 高风险缺口
| 缺口 | 类型 | 影响 | 填补难度 |
|:-----|:-----|:------|:---------|
| **EVALUATE ALSO** | 语言特性 | EVALUATE 多主体分支解析未验证 | 低 — 添加测试程序 |
| **GO TO 段落跳转** | 语言特性 | GoTo 节点已实现，控制流图未验证 | 中 — 需要跨段落测试 |
| **online (CICS) 分类** | 程序类型 | DFHCOMMAREA/MAP 关键字匹配已实现，无实际程序 | 高 — 需要 CICS 环境 |
| **PERFORM THRU** | 语言特性 | 跨段落串行调用 | 中 — 需要 _BrParser 验证 |
### 🟠 中风险缺口
| 缺口 | 类型 | 影响 | 填补难度 |
|:-----|:-----|:------|:---------|
| **mixed_complex 混淆组** | 程序类型 | 多特征混合程序（如 CRDCALC）的分类准确率 | 低 — 添加 CRDCALC 到 test-data |
| **data_file_centric 混淆组** | 程序类型 | 文件密集程序的分类验证 | 低 |
| **evaluate_driven 混淆组** | 程序类型 | EVALUATE 主导程序的分类验证 | 低 |
| **VALUE THRU 范围值** | 语言特性 | `VALUE 1 THRU 10` 解析未适配 | 低 |
| **COPY REPLACING** | 语言特性 | 伪文本替换展开未测试 | 低 — 添加 fixture |
### 🟢 低风险缺口
| 缺口 | 类型 | 影响 | 填补难度 |
|:-----|:-----|:------|:---------|
| MERGE 语句 | 语言特性 | 无专用节点，但 SORT 类似 | 低 |
| JUSTIFIED/BLANK/SYNC | 语言特性 | metadata 子句，不影响逻辑 | 低 |
| 测试代码/业务代码比例 | 质量指标 | 0.54:1 偏低 | 中 |
| 并发测试 | 非功能 | 仅 2 个并发测试 | 高 — 需要多线程架构 |
---
## 8. 结论与建议
### 8.1 覆盖成熟度
```
测试覆盖成熟度: ████████████░░░░░░ 63% (对标行业标准)
等级划分:
L1 - 基础覆盖 (功能正确性) ████████████████████ 100% ✅
L2 - 边界覆盖 (错误/异常) ████████████████░░░ 82% ✅
L3 - 程序类型覆盖 ███████████░░░░░░░░ 58% ⚠️
L4 - 非功能覆盖 (性能/安全) ████░░░░░░░░░░░░░░ 22% ⚠️
L5 - 生产环境覆盖 (集成/E2E) ████████░░░░░░░░░░░ 38% ❌
```
### 8.2 建议优先级
1. **立即填补**: 添加 `EVALUATE ALSO`、`evaluate_driven`、`data_file_centric` 测试程序
2. **短期填补**: 补齐 5 个无专用 HINA 程序的 L1 类别（IS INITIAL, SYSIN, 编码转换, MERGE, 文件编成, 替代索引）
3. **中期填补**: CRDCALC 注册为 mixed_complex 测试用例
4. **环境依赖**: 配置 CI 中的 GnuCOBOL/Java/Spark 以激活 runner、gcov、web API 测试
### 8.3 最终统计
```
✅ 测试总数: ~518 passed / 0 failed
✅ 测试文件: 50+ 个
✅ 覆盖率: 77% 业务代码 / 86% 核心管道 (已认证)
✅ 程序类型: 7/7 混淆组 + 10/11 HINA 分类 + 33/35 类型覆盖
✅ 语言特性: 36/42 DATA DIVISION 特性 + 18/20 PROCEDURE DIVISION 特性
✅ 实际程序: 4/4 信用卡系统程序 (golden)
✅ parametrized: 8/8 公开函数 100% 覆盖
✅ japanese_data: 8/8 生成函数 100% 覆盖
✅ coverage: 1/1 公开函数 100% 覆盖
✅ hina/confidence: 1/1 公开函数 100% 覆盖
✅ hina/rule_engine: 11/11 公开函数 100% 覆盖
✅ 发现缺陷: 2 个严重缺陷已修复
⚠️ 缺口: 6 个已知可填补 (3低 + 2中 + 1高)
```
docs/module-interfaces.md
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# COBOL-Java 迁移验证平台 — 模块接口规范
> 目的：明确定义每个模块的边界、公开 API、数据契约，实现多人并行开发。
> 每个模块可以由不同开发者独立开发，只要遵循接口契约即可集成。
---
## 一、模块分层架构
```
┌──────────────────────────────────────────────────────────────────────────┐
│ Layer 4: 管道集成 │
│ │
│ orchestrator.py — 管道导演，编排全流程 │
│ web/ — FastAPI + Worker 网络层 │
│ jcl/executor.py — JCL 执行器 │
└───────────────────────────────────┬──────────────────────────────────────┘
│ 调用
▼
┌──────────────────────────────────────────────────────────────────────────┐
│ Layer 3: 业务引擎 │
│ │
│ agents/ — LLM 智能体（解析/设计/诊断） │
│ hina/ — 程序分类（关键字/规则/LLM） │
│ comparator/— 对比引擎（对齐/比较/舍入） │
│ runners/ — 编译运行引擎（COBOL/Java/Spark） │
└───────────────────────────────────┬──────────────────────────────────────┘
│ 调用
▼
┌──────────────────────────────────────────────────────────────────────────┐
│ Layer 2: 核心引擎 │
│ │
│ cobol_testgen/ — COBOL 解析 + 测试数据生成 │
│ report/ — 报告生成器 │
│ jcl/parser.py — JCL 解析器 │
│ config/ — 配置管理 │
│ quality/ — 质量验证 │
│ preprocessor.py — COPYBOOK 预处理 │
└───────────────────────────────────┬──────────────────────────────────────┘
│ 使用
▼
┌──────────────────────────────────────────────────────────────────────────┐
│ Layer 1: 数据模型 + 存储 │
│ │
│ data/ — 核心数据模型（所有层共享） │
│ storage/ — 持久化存储（缓存/报告库） │
└──────────────────────────────────────────────────────────────────────────┘
```
---
## 二、数据模型层 (Layer 1) — 所有层的契约
### `data/field_tree.py` — 字段树
```python
@dataclass
class Field:
name: str
level: int
pic: str
usage: str = "DISPLAY" # COMP / COMP-3 / DISPLAY / ...
offset: int = 0
length: int = 0
decimal: int = 0
signed: bool = False
sign_separate: bool = False
occurs: Optional[int] = None
occurs_max: Optional[int] = None
redefines: Optional[str] = None
redefines_variant: Optional[str] = None
conditions: list[dict] = field(default_factory=list)
children: list["Field"] = field(default_factory=list)
@dataclass
class FieldTree:
fields: list[Field] = field(default_factory=list)
copybook_name: str = ""
sha256: str = ""
def flatten(self) -> dict[str, Field]: ...
def get_by_name(self, name: str) -> Optional[Field]: ...
@classmethod
def from_list(cls, fields, name="") -> "FieldTree": ...
```
### `data/test_case.py` — 测试用例
```python
@dataclass
class TestCase:
id: str
fields: dict = field(default_factory=dict) # {字段名: 值}
coverage_targets: list[str] = field(default_factory=list)
@dataclass
class TestSuite:
test_cases: list[TestCase] = field(default_factory=list)
spark_config: Optional[SparkConfig] = None
@property
def has_spark(self) -> bool: ...
@dataclass
class SparkConfig:
num_records: int = 100
replication: str = "key_varied"
key_field: str = ""
edge_cases: list[str] = field(default_factory=list)
```
### `data/diff_result.py` — 对比结果
```python
@dataclass
class FieldResult:
field_name: str = ""
status: str = "PASS" # PASS / TOLERATED / MISMATCH / NOT_SET
cobol_value: str = ""
java_value: str = ""
tolerance_applied: float = 0.0
rounding_detected: str = ""
suggestion: str = ""
@dataclass
class VerificationRun:
program: str = ""
timestamp: str = ""
status: str = "PASS" # PASS / MISMATCH / BLOCKED / ERROR / FATAL
exit_code: int = 0
duration_s: float = 0.0
fields_matched: int = 0
fields_mismatched: int = 0
field_results: list[FieldResult] = field(default_factory=list)
runner: str = "native" # native / spark
branch_rate: float = 0.0
paragraph_rate: float = 0.0
decision_rate: float = 0.0
hina_type: str = ""
hina_confidence: float = 0.0
quality_score: float = 0.0
quality_warn: str = ""
heal_retry: int = 0
simple_retry: int = 0
total_retry: int = 0
llm_cost: float = 0.0
report_path: str = ""
debug: dict = field(default_factory=dict)
@property
def total_fields(self) -> int: ...
def verdict(self) -> str: ...
```
---
## 三、核心引擎层 (Layer 2) — 接口规范
### 模块 2-1: `cobol_testgen`（COBOL 解析 + 数据生成）
**负责人**: A
**依赖**: data/ (Field, FieldTree, PicInfo, FieldDef, BrSeq, ...)
```
公开函数:
┌─────────────────────────────────────────────────────────────────────────┐
│ extract_structure(cobol_source: str, source_dir: str = None) → dict │
│ │
│ 入力: COBOL 源码文本、可选的 COPYBOOK 搜索路径 │
│ 出力: { │
│ paragraphs: list[str], ← 段落名列表 │
│ total_paragraphs: int, ← 段落总数 │
│ decision_points: list[dict], ← [{id, kind, label, branches}, ...]│
│ total_branches: int, ← 分支总数 │
│ branch_tree: BrSeq, ← 控制流树 │
│ file_count: int, ← SELECT 文件数 │
│ open_directions: dict, ← {文件名: INPUT/OUTPUT/I-O} │
│ has_search_all: bool, ← 是否有 SEARCH ALL │
│ has_evaluate: bool, ← 是否有 EVALUATE │
│ has_call: bool, ← 是否有 CALL │
│ has_break: bool, ← 是否有 key 中断 │
│ branch_tree_obj: BrSeq, ← 原始分支树对象 │
│ } │
├─────────────────────────────────────────────────────────────────────────┤
│ generate_data(cobol_source: str, structure: dict, │
│ source_dir: str = None) → list[dict] │
│ │
│ 入力: COBOL源码, extract_structure 的输出, 搜索路径 │
│ 出力: [{字段名: 值, ...}, ...] ← 每条记录覆盖一条分支路径 │
├─────────────────────────────────────────────────────────────────────────┤
│ incremental_supplement(branch_tree, decision_gaps: list[int]) │
│ → list[dict] │
│ │
│ 入力: 分支树对象, 未覆盖决策点的 ID 列表 │
│ 出力: 补充的新测试记录 │
└─────────────────────────────────────────────────────────────────────────┘
子模块职责:
read.py — 预处理 + DATA DIVISION 解析 + PIC 解析 → FieldDef[]
core.py — PROCEDURE DIVISION 解析 → BrSeq 树 + assignments
cond.py — 条件表达式解析 + MC/DC 枚举 → CondLeaf/And/Or/Not
design.py — 路径枚举 + 值生成 + 约束应用 → generate_records()
coverage.py— 决策点收集 + 标记 + HTML报告 → check_coverage()
output.py — JSON/文件输出 → output_json/output_input_files
models.py — 数据模型 (共享)
```
---
### 模块 2-2: `config`（配置管理）
**负责人**: B
**依赖**: 无内部依赖
```
┌─────────────────────────────────────────────────────────────────────────┐
│ Config (dataclass) │
│ │
│ 字段: │
│ project_name: str = "" │
│ copybook_paths: list = ["./copybooks"] │
│ dialect: str = "ibm" # cobc -std 参数 │
│ llm_model: str = "gpt-4o-mini" # LLM 模型 │
│ llm_timeout: int = 15 │
│ llm_cache_dir: str = ".cache/llm" │
│ coverage_default: str = "boundary" │
│ rounding_mode: str = "TRUNCATE" │
│ tolerance: float = 0.01 # 比较容忍度 │
│ runner_mode: str = "native" # native / spark │
│ spark_master: str = "local[*]" │
│ num_records: int = 1000 │
│ branch_pass: float = 0.80 # 覆盖率通过阈值 │
│ max_llm_cost: float = 0.50 │
│ quality_gate_mode: str = "warn" # off / warn / strict │
│ quality_gate_decision_threshold: float = 0.90 │
│ quality_gate_paragraph_threshold: float = 1.0 │
│ gcov_enabled: bool = False │
│ max_quality_retries: int = 4 │
│ │
│ 类方法: │
│ @classmethod from_toml(path="aurak.toml") → Config │
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 2-3: `preprocessor`（COPYBOOK 预处理）
**负责人**: B
**依赖**: 无
```
┌─────────────────────────────────────────────────────────────────────────┐
│ CopybookPreprocessor │
│ │
│ __init__(paths: list = ["./copybooks"]) │
│ expand(text: str) → str # COPY 语句展开后的源码 │
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 2-4: `quality`（质量验证）
**负责人**: C
**依赖**: data/field_tree.py
```
┌─────────────────────────────────────────────────────────────────────────┐
│ L1OffsetValidator │
│ validate(tree: FieldTree, cpath: str) → dict {score, mismatches} │
│ │
│ L2RoundtripValidator │
│ validate(tree: FieldTree) → dict {pass, results} │
└─────────────────────────────────────────────────────────────────────────┘
```
### 模块 2-5: `jcl/parser.py`（JCL 解析）
**负责人**: C
**依赖**: 无
```
┌─────────────────────────────────────────────────────────────────────────┐
│ parse_jcl(filepath: str) → Optional[Job] │
│ │
│ Job { job_name: str, steps: list[JobStep] } │
│ JobStep { step_name: str, program: str, │
│ dd_entries: list[DDEntry], cond: Optional[CondParam] } │
│ DDEntry { dd_name: str, dsn: Optional[str], disp: Optional[str], │
│ sysout: Optional[str], inline_data: list[str] } │
│ CondParam { code: int, operator: str, step_name: Optional[str] } │
└─────────────────────────────────────────────────────────────────────────┘
```
### 模块 2-6: `report`（报告生成）
**负责人**: B
**依赖**: data/diff_result.py
```
┌─────────────────────────────────────────────────────────────────────────┐
│ ReportGenerator │
│ generate_json(vr: VerificationRun, path: Path) │
│ generate_html(vr: VerificationRun, path: Path) │
│ generate_machine_json(vr: VerificationRun, path: Path) │
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 2-7: `parametrized`（测试数据生成器）
**负责人**: I (新增)
**依赖**: 无
```
公开函数（8 个）:
┌─────────────────────────────────────────────────────────────────────────┐
│ matching.py — 匹配系数据生成 │
│ │
│ generate_matching_data(matching_type="1:1", │
│ record_count_r01=10, │
│ record_count_r02=10, │
│ key_match_ratio=1.0) → tuple[list, list] │
│ 出力: (主文件记录列表, 从文件记录列表) │
│ 匹配模式: "1:1" / "1:N" / "N:1" │
├─────────────────────────────────────────────────────────────────────────┤
│ matching.py — KEY 切中断数据生成 │
│ │
│ generate_keybreak_data(group_count=3, │
│ records_per_group=2, │
│ sum_type="accumulate") → list[dict] │
│ 出力: [{KEY, FIELD, GROUP, SEQ}, ...] │
│ sum_type: "accumulate" / "aggregate" / "mark" │
├─────────────────────────────────────────────────────────────────────────┤
│ division.py — 分割系数据生成 │
│ │
│ generate_division_data(division_type=50, │
│ record_count=50) → list[list[dict]] │
│ 出力: [[文件1记录], [文件2记录], ...] │
│ division_type: 50(对半) / 25(四等分) / 100(全量) │
├─────────────────────────────────────────────────────────────────────────┤
│ common.py — 通用数据生成工具 │
│ │
│ generate_zero_byte_file(path: str) → None │
│ 写入 0 字节空文件 │
│ │
│ generate_minimal_records(fields: list[dict]) → list[dict] │
│ 出力: 1 条类型合理默认值的记录 │
│ │
│ generate_sorted_records(record_count=10, key_field="KEY") → list[dict] │
│ 出力: 已按 KEY 升序排列的记录列表 │
│ │
│ generate_duplicate_keys(records: list[dict], key_field="KEY") │
│ → list[dict] │
│ 出力: 原记录 + 同键值重复记录（用于 SORT MERGE / 去重测试） │
│ │
│ generate_boundary_values(pic: str) → dict │
│ 出力: {max, min, overflow, zero, pic_info} │
│ 从 PIC 子句解析出最大值 / 最小值 / 溢出值 │
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 2-8: `japanese_data.py`（日文测试数据生成）
**负责人**: I (新增)
**依赖**: 无
```
公开函数（8 个生成函数 + 常量表）:
┌─────────────────────────────────────────────────────────────────────────┐
│ 查找表常量 │
│ FULLWIDTH_KATAKANA — 全角片假名字符串 │
│ FULLWIDTH_HIRAGANA — 全角平假名字符串 │
│ FULLWIDTH_DIGITS — 全角数字 │
│ FULLWIDTH_ALPHA — 全角字母 │
│ HALFWIDTH_KATAKANA — 半角片假名字符串 │
│ SJIS_5C_PROBLEM — Shift-JIS 第2字节 0x5C 问题文字 │
│ SJIS_7C_PROBLEM — Shift-JIS 第2字节 0x7C 问题文字 │
│ WAREKI_BOUNDARIES — 和历边界对照表 │
├─────────────────────────────────────────────────────────────────────────┤
│ 生成函数 │
│ │
│ generate_fullwidth_text(field: dict) → str │
│ 全角片假名填充 PIC N 字段 │
│ │
│ generate_halfwidth_katakana(field: dict) → str │
│ 半角片假名填充 PIC X 字段 │
│ │
│ generate_sjis_5c_problem(field: dict) → str │
│ 含 Shift-JIS 0x5C 问题文字的字符串 │
│ │
│ generate_sjis_7c_problem(field: dict) → str │
│ 含 Shift-JIS 0x7C 问题文字的字符串 │
│ │
│ generate_wareki_date(wareki_type="R") → str │
│ 和历日期字符串（格式: R050101） │
│ │
│ generate_wareki_boundary(era="平成") → tuple[str, str] │
│ 和历边界日期对（前代末日, 新代初日） │
│ │
│ generate_encoding_test_data(from_enc="shift_jis", to_enc="utf-8") │
│ → tuple[bytes, bytes] │
│ Shift-JIS ↔ UTF-8 编码回环验证数据 │
│ │
│ select_data_type(field: dict) → str │
│ 字段类型判断: "japanese" / "numeric" / "halfwidth" │
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 2-9: `coverage/compare_coverage.py`（覆盖率比较）
**负责人**: D
**依赖**: 无
```
┌─────────────────────────────────────────────────────────────────────────┐
│ compare_coverage(program_name: str, │
│ static: dict, │
│ dynamic: dict) → dict │
│ │
│ 入力: │
│ program_name — 程序名称 │
│ static — 静态覆盖率: {branch_rate, paragraph_rate, ...} │
│ dynamic — 动态覆盖率: {gcov_cov, covered_branches, ...} │
│ │
│ 出力: { │
│ program: str, ← 程序名称 │
│ static: {branch_rate, paragraph_rate}, │
│ dynamic: {gcov_cov}, │
│ gap: float, ← static - dynamic 差异 │
│ misleading_branches: list, ← 静态覆盖但动态未覆盖的分支 │
│ } │
│ │
│ 用途: 识别 gcov 实际运行与静态分析之间的偏离 │
└─────────────────────────────────────────────────────────────────────────┘
```
---
## 四、业务引擎层 (Layer 3) — 接口规范
### 模块 3-1: `hina`（程序分类 + 质量门禁 + 类型判定管道）
**负责人**: D
**依赖**: data/diff_result.py (VerificationRun)
```
├── 公开 API ────────────────────────────────────────────────────────────┤
│ pipeline/（类型判定管道 — 唯一入口） │
│ │
│ classify_program(cobol_source: str) → dict │
│ 出力: {category, confidence, subtype, strategy_params, │
│ resolved_type, needs_review, ...} │
│ │
│ 流程: │
│ 1. 并行执行关键字识别 + 结构提取 │
│ 2. 确信度 ≥ 90% → 直接输出 │
│ 3. 确信度 50-89% → 混淆组判定 + 4因子确信度 + 矛盾检测 + 回溯 │
│ 4. 确信度 < 50% → 标记需人工处理 │
├─────────────────────────────────────────────────────────────────────────┤
│ confidence.py │
│ │
│ compute_confidence_v2(keyword_result, structure_features, │
│ contradictions=None, resolution=None) → dict │
│ 出力: {confidence, base, context_factor, consistency_factor, │
│ structure_factor, judgment, needs_review} │
│ │
│ 4 因子确信度公式: │
│ confidence = base × context_factor × consistency_factor │
│ × structure_factor │
│ │
│ 判定标准: │
│ >= 0.90 auto — 自动通过 │
│ 0.70-0.89 review — 需要人工审核 │
│ 0.50-0.69 manual — 需要人工介入 │
│ < 0.50 impossible — 无法判定 │
├─────────────────────────────────────────────────────────────────────────┤
│ classifier.py │
│ │
│ L1_RULES: list[tuple[str, list[str], float]] ← 11类关键字规则 │
│ │
│ detect_keyword(source: str) → list[tuple[str, float, str]] │
│ 出力: [(分类名, 确信度, 匹配关键字), ...] │
├─────────────────────────────────────────────────────────────────────────┤
│ hina_agent.py │
│ │
│ classify_with_llm(structure: dict, llm) → dict │
│ 出力: {category, subtype, confidence, strategy_params} │
│ │
│ _parse_llm_response(raw: str) → dict │
│ _validate_result(parsed: dict) → dict │
│ _fallback_classification(structure: dict) → dict ← 7混淆组规则 │
├─────────────────────────────────────────────────────────────────────────┤
│ gate.py │
│ compute_quality_score(branch_rate, paragraph_rate) → float │
│ check(tests, hina_result, coverage, thresholds...) → dict │
│ 出力: {passed: bool, score: float, issues: dict} │
├─────────────────────────────────────────────────────────────────────────┤
│ strategy.py │
│ get_strategy(hina_type: str) → dict ← 5类型策略模板 │
│ supplement(base_tests, hina_result) → list[dict] │
│ supplement_only(base_tests, gaps) → list[dict] │
├─────────────────────────────────────────────────────────────────────────┤
│ retry.py │
│ RetryHandler(max_heal=2, max_simple=3) │
│ run(pipeline_fn: Callable[[], VerificationRun]) → VerificationRun │
├─────────────────────────────────────────────────────────────────────────┤
│ gcov_collector.py │
│ collect_gcov(cobol_src: Path, work_dir: Path) → dict │
│ 出力: {available, line_rate, total_lines, executed_lines} │
├─────────────────────────────────────────────────────────────────────────┤
├── 内部实现（不公开）───────────────────────────────────────────────────┤
│ rule_engine/（混淆组规则引擎 — 非公开，由 pipeline 内部调用） │
│ │
│ confusion_groups.py — 8 个混淆组判定函数 │
│ resolve_matching_vs_keybreak(features) → dict │
│ resolve_dedup_vs_nodedup(features) → dict │
│ resolve_validation_vs_keybreak(features) → dict │
│ resolve_csv_merge_vs_split(features) → dict │
│ resolve_simple_vs_two_stage(features) → dict │
│ resolve_pure_vs_mixed(features) → dict │
│ resolve_division_50_25_100(features) → dict │
│ resolve_mn_output_mode(features) → dict │
│ │
│ contradiction.py — 矛盾检测与解决 │
│ CONTRADICTION_PAIRS: list[tuple[str, str]] │
│ detect_contradictions(types: list[str]) → list[dict] │
│ resolve_contradiction(type_a, type_b, features) → str │
│ │
│ backtrack.py — 多轮回溯判定 │
│ BacktrackResolver(max_iterations=3, fallback_type="unknown") │
│ resolve(features, initial_types, contradictions) → dict │
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 3-2: `agents`（LLM 智能体）
**负责人**: E
**依赖**: data/field_tree.py, data/test_case.py, data/diff_result.py
```
┌─────────────────────────────────────────────────────────────────────────┐
│ LLMClient(model="gpt-4o-mini", timeout=15, cache_dir=".cache/llm") │
│ call(messages: list[dict], retries=1) → str │
│ │
│ 通信契约: POST {base}/chat/completions │
│ Header: Authorization: Bearer $LLM_API_KEY │
│ Body: {model, messages} │
│ 成功: {choices: [{message: {content: "..."}}]} │
│ │
│ 缓存: SHA256(消息)→ 磁盘文件 .cache/llm/{hash}.json │
├─────────────────────────────────────────────────────────────────────────┤
│ Agent1Parser(llm: LLMClient) │
│ parse(text: str) → FieldTree ← COPYBOOK 文本 → 字段树 │
│ │
│ 提示词: 解析 COBOL COPYBOOK → JSON {fields: [...]} │
├─────────────────────────────────────────────────────────────────────────┤
│ Agent2Data(llm: LLMClient) │
│ design(tree: FieldTree, target="boundary", spark_mode=False) │
│ → TestSuite │
│ │
│ 提示词: 根据 FieldTree 设计测试用例 → JSON {test_cases: [...]} │
├─────────────────────────────────────────────────────────────────────────┤
│ Agent3Diagnostic(llm: LLMClient) │
│ analyze(fr: FieldResult) → str ← 差异诊断 → 建议文本 │
│ │
│ 提示词: 分析 COBOL-Java 字段差异原因 → JSON {issue_type, suggestion}│
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 3-3: `comparator`（对比引擎）
**负责人**: F
**依赖**: data/field_tree.py, data/diff_result.py
```
┌─────────────────────────────────────────────────────────────────────────┐
│ align_records(cobol_records, java_records, key_field) → list[tuple] │
│ 入力: COBOL记录列表, Java记录列表, 键字段名 │
│ 出力: [(cobol_dict, java_dict, 'MATCHED'), ...] │
│ (cobol_dict, None, 'MISSING_IN_SPARK') │
│ (None, java_dict, 'EXTRA_IN_SPARK') │
├─────────────────────────────────────────────────────────────────────────┤
│ compare_field(name, c, j, field_type='decimal', tolerance=0.01) │
│ → FieldResult │
│ │
│ field_type 取值: 'decimal' / 'string' / 'date' │
│ status 取值: PASS / TOLERATED / MISMATCH │
├─────────────────────────────────────────────────────────────────────────┤
│ CobolBinaryReader │
│ read(binary_path: str, tree: FieldTree) → list[dict] │
│ 按 FieldTree 的 offset/length 解析二进制 → [{字段: 值}] │
├─────────────────────────────────────────────────────────────────────────┤
│ Normalizer │
│ normalize_comp3(data: bytes) → str ← COMP-3 解码 │
├─────────────────────────────────────────────────────────────────────────┤
│ detect_rounding(c: str, j: str) → RoundingResult │
└─────────────────────────────────────────────────────────────────────────┘
```
---
### 模块 3-4: `runners`（编译运行引擎）
**负责人**: G
**依赖**: data/test_case.py, data/diff_result.py
```python
@dataclass
class BuildResult:
success: bool
artifact_path: str = ""
log: str = ""
@dataclass
class RunResult:
success: bool
records: list[dict] = field(default_factory=list)
log: str = ""
coverage_exec: str = ""
@dataclass
class CoverageReport:
branch_rate: float = 0.0
covered_branches: int = 0
total_branches: int = 0
verdict: str = "PASS"
class Runner(ABC):
@abstractmethod
def compile(self, source_dir: str) -> BuildResult: ...
@abstractmethod
def run(self, artifact: str, input_path: str, output_path: str) -> RunResult: ...
@abstractmethod
def get_coverage(self, artifact: str, run_id: str) -> CoverageReport: ...
class CobolRunner:
def compile(self, src: str, dialect="ibm", gcov=False) -> BuildResult: ...
def run(self, binary: str, input_path: str, output_path: str) -> RunResult: ...
class NativeJavaRunner(Runner): ... # mvn + java -jar
class SparkJavaRunner(Runner): ... # spark-submit
class DataWriter:
def write_cobol_binary(tests: list[TestCase], path: Path): ...
def write_native_json(tests: list[TestCase], path: Path): ...
def write_spark_json(tests: list[TestCase], config: SparkConfig, outdir: Path): ...
```
---
## 五、管道集成层 (Layer 4) — 接口规范
### 模块 4-1: `orchestrator`（管道导演）
**负责人**: H (@所有人 集成)
**依赖**: Layer 2 + Layer 3 的所有模块
```
┌─────────────────────────────────────────────────────────────────────────┐
│ run_pipeline(cfg: Config, │
│ cpath: str, ← copybook 路径 │
│ cbl: str, ← COBOL 源码路径 │
│ java: str, ← Java 源码路径 │
│ map_path: str) ← mapping 路径 │
│ → VerificationRun │
│ │
│ 内部流程（各步骤可独立替换）: │
│ │
│ Step 1: Agent1Parser(llm).parse(cpath) → FieldTree │
│ Step 2: extract_structure(cbl) → structure dict │
│ Step 3: generate_data(cbl, structure) → TestCase[] │
│ Step 4: compute_confidence(cbl, structure) → HINA result │
│ classify_with_llm(structure, llm) │
│ Step 5: strategy_supplement(tests, hina) → 补充 TestCase[] │
│ Step 6: gate_check(tests, hina, cov, ...) → 质量门禁 │
│ Step 7: Agent2Data(llm).design(tree) → TestSuite │
│ Step 8: DataWriter -> cobol_binary + json → 输入文件 │
│ Step 9: CobolRunner.compile(cbl) → BuildResult │
│ Step 10: CobolRunner.run(binary, input) → RunResult │
│ Step 11: Runner.compile(java) → BuildResult │
│ Step 12: Runner.run(jar, input) → RunResult │
│ Step 13: CobolBinaryReader.read(co_out, tree) → COBOL records │
│ Step 14: align_records(cobol, java, key) → aligned tuples │
│ Step 15: compare_field(field, c, j, type, tol) → FieldResult[] │
│ Step 16: Agent3Diagnostic.analyze(mismatch) → suggestions │
│ Step 17: ReportGenerator → JSON + HTML → 报告文件 │
│ │
│ 返回: VerificationRun (全结果聚合) │
└─────────────────────────────────────────────────────────────────────────┘
```
---
## 六、模块耦合关系矩阵
```
depends_on → L1 L2-1 L2-2 L2-3 L2-4 L2-5 L2-6 L2-7 L2-8 L2-9 L3-1 L3-2 L3-3 L3-4
module ↓ data cbl_t conf prepr qual jcl rpt para jp cov hina agnt comp runr
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
L2-1 cobol_testgen ● ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-2 config ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-3 preprocessor ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-4 quality ● ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-5 jcl/parser ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-6 report ● ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-7 parametrized ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-8 japanese_data ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L2-9 coverage ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ● ─ ─ ─
L3-1 hina ● ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L3-2 agents ● ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L3-3 comparator ● ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L3-4 runners ● ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
L4 orchestrator ● ● ● ─ ─ ─ ● ─ ─ ─ ● ● ● ●
L4 web/L4 jcl exec ● ─ ● ─ ─ ● ─ ─ ─ ─ ─ ─ ─ ●
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
```
---
## 七、模块依赖图（协作视图）
```
┌───────────┐
│ data/ │ ← 所有模块共享的数据契约
└─────┬─────┘
│
┌────┬────┬────┬────┼────┬────┬────┬────┬────┬────┬────┐
│ │ │ │ │ │ │ │ │ │ │ │
▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼
cobol_t para jp cov conf qual hina agnt comp runr rpt
│ │ │ │ │ │ │ │ │ │ │
└────┴─────┴────┴────┴─────┴─────┴────┴────┴────┴────┘
│
▼
orchestrator.py
│
┌────┴────┐
│ │
▼ ▼
web/ jcl/exec
```
---
## 八、多人协作分工方案
| 开发者 | 模块 | 需知接口 | 独立程度 |
|:-------|:-----|:---------|:---------|
| **A** | `cobol_testgen/` (read/core/cond/design/coverage/output) | data/ 数据模型 | ✅ 完全独立 |
| **B** | `config/` + `preprocessor/` + `report/` | data/diff_result.py | ✅ 完全独立 |
| **C** | `quality/` + `jcl/parser/` | data/field_tree.py | ✅ 完全独立 |
| **D** | `hina/` (pipeline/classifier/gate/agent/strategy/retry/gcov/rule_engine) + `coverage/` | data/diff_result.py | ✅ 完全独立 |
| **E** | `agents/` (LLM/parser/data/diagnostic) | data/ 全部 3 个模型 | ✅ 完全独立 |
| **F** | `comparator/` (align/compare/reader/normalize/round) | data/全部 | ✅ 完全独立 |
| **G** | `runners/` (cobol/java/spark/datawriter) | data/test_case.py | ✅ 完全独立 |
| **I** | `parametrized/` + `japanese_data.py` | 无 | ✅ 完全独立 |
| **H** | `orchestrator.py` (集成)+ `web/` + `jcl/exec` | 所有模块 API | ⛓️ 需要所有人 |
**各 Layer 3 模块只有 1 个统一约束**: 接收的输入必须是 data/ 中的数据类实例，返回的也必须是 data/ 中的数据类实例。只要遵守这个契约，模块开发者不需要知道其他模块的内部实现。
---
## 九、当前系统问题 & 改进项
| 问题 | 影响 | 解决方案 |
|:-----|:-----|:---------|
| **`cobol_testgen/__init__.py` 混用公开和私有符号** (如 `_add_subscript`/`_init_child_names`) | 外部不清楚哪些是稳定接口 | 添加 `__all__` 明确定义公开 API |
| **多数模块没有 `__all__`** | 无法区分公开/内部函数 | 每个模块根文件添加 `__all__` |
| **orchestrator 直接 import 内部子模块** (如 `cobol_testgen.coverage.check_coverage`) | Layer 越界，管道依赖了引擎内部 | orchestrator 只应 import 各模块的顶层公开函数 |
| **Config 字段没有验证/文档** | 修改 Config 可能破坏其他模块 | 添加字段校验 + 注释 |
| **函数签名缺少类型注解** (部分历史代码) | 接口不明确 | 补全所有公开函数的类型注解 |
| **没有模块版本号/变更记录** | 无法追踪接口变更 | 添加 `__version__` 到每个模块 |
docs/phase2-design.md
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@@ -1,1239 +0,0 @@
# COBOL 迁移验证平台 第二阶段设计书
> 版本: v2.0 | 日期: 2026-06-19
> 基于: cobol-test-benchmark.md 的 33+2 程序类型分类体系
> 范围: 12 个 Phase，从类型判定引擎完善到完整测试基准实现
---
## 目录
1. [设计总则](#1-设计总则)
2. [Phase 1: extract_structure 输出扩展](#2-phase-1-extract_structure-输出扩展)
3. [Phase 2: 混淆组判定规则引擎](#3-phase-2-混淆组判定规则引擎)
4. [Phase 3: 确信度 4 因子计算](#4-phase-3-确信度-4-因子计算)
5. [Phase 4: 33+2 种程序类型 COBOL 测试样本](#5-phase-4-332-种程序类型-cobol-测试样本)
6. [Phase 5: 参数化测试数据生成引擎](#6-phase-5-参数化测试数据生成引擎)
7. [Phase 6: 日文测试数据生成查找表](#7-phase-6-日文测试数据生成查找表)
8. [Phase 7-10: 类型别测试套件](#8-phase-7-10-类型别测试套件)
9. [Phase 11: 完整类型判定管道](#9-phase-11-完整类型判定管道)
10. [Phase 12: 文档更新](#10-phase-12-文档更新)
11. [依赖关系与分工矩阵](#11-依赖关系与分工矩阵)
12. [接口变更一览](#12-接口变更一览)
13. [COBOL 覆盖率测试体系](#13-cobol-覆盖率测试体系)
14. [架构审核决议汇总](#14-架构审核决议汇总)
---
## 1. 设计总则
### 1.1 新增 Phase 0.6: gcov 基础设施
> 在 Phase 1 之前完成，为所有类型测试提供 gcov 能力。
> 负责: F | 工作量: 3h
为覆盖率测试体系提供可自动化运行的基础设施。Phase 7-10 中所有 gcov 测试的前置条件。
| 步骤 | 内容 | 工作量 |
|:-----|:-----|:------|
| 1 | `cobc --coverage` 环境验证自动化 | 0.5h |
| 2 | `collect_gcov()` 路径修复（含中文目录兼容）| 1h |
| 3 | `Config` 追加 gcov_enabled / gcov_work_dir / gcov_threshold | 0.5h |
| 4 | `test_gcov_basic.py` — gcov 全链路验证测试 | 1h |
**验收**: cobc --coverage 编译 → 运行 → .gcda 生成 → collect_gcov() line_rate > 0
```python
# config/__init__.py — Config 新增字段
gcov_enabled: bool = False
gcov_work_dir: str = ".gcov_output"
gcov_threshold: float = 0.5
```
### 1.3 分层原则
```
Layer 1: data/ — 所有模块共享的数据契约
Layer 2: 核心引擎 — cobol_testgen/ config/ jcl/ quality/ report/ preprocessor/
Layer 3: 业务引擎 — hina/ agents/ comparator/ runners/
Layer 4: 管道集成 — orchestrator/ web/
依赖方向: Layer 1 ← Layer 2 ← Layer 3 ← Layer 4
禁止逆向依赖。
```
### 1.4 模块通信规则
- 所有模块间通信通过 `data/` 层的数据类进行
- 每个模块的公开 API 由 `__init__.py` 的 `__all__` 定义
- 禁止钻入模块内部（如 `from cobol_testgen.coverage import ...`）
- 详见 `CONTRIBUTING.md`
### 1.5 最终模块布局（经架构审核确认）
```
项目根目录/
├── cobol_testgen/ ← COBOL 解析引擎 (P1扩展)
│
├── hina/
│ ├── rule_engine/ ← 混淆组规则引擎 (P2)
│ ├── confidence.py ← 确信度 4 因子计算 (P3)
│ └── pipeline/ ← 完整类型判定管道 (P11)
│
├── parametrized/ ← 独立模块！参数化测试数据生成引擎 (P5)
│ ├── __init__.py
│ ├── matching.py
│ ├── division.py
│ └── common.py
│
├── japanese_data.py ← 独立文件！日文测试数据查找表 (P6)
│
├── test-data/cobol/ ← 新增 33+2 种 COBOL 样本 (P4)
│
├── tests/
│ └── parametrized/ ← 类型别测试套件 (P7-10)
│
└── docs/ ← 文档更新 (P12)
重要决策:
✅ classification_pipeline/ → 合并到 hina/pipeline/
✅ parametrized/ → 独立模块（项目根目录）
✅ japanese_data.py → 独立文件（项目根目录）
```
---
## 2. Phase 1: extract_structure 输出扩展
### 2.1 目的
当前 `extract_structure()` 输出的结构特征不足以判定 33+2 种程序类型。需要增加以下字段。
### 2.2 新增输出字段
在 `cobol_testgen/__init__.py` 的 `extract_structure()` 返回字典中追加：
```python
# 新增字段（原有字段不变）
{
# ── 文件相关 ──
"select_files": { # SELECT 语句列表
"INFILE": {"assign_to": "INPUT.DAT", "organization": "SEQUENTIAL"},
"OUTFILE": {"assign_to": "OUTPUT.DAT", "organization": "SEQUENTIAL"},
},
"open_directions_detail": { # OPEN 方向详情
"INFILE": "INPUT",
"OUTFILE": "OUTPUT",
"WORKFILE": "I-O",
},
# ── DIVIDE 语句检测 ──
"has_divide": False, # 是否有 DIVIDE 语句
"divide_constants": [], # DIVIDE 的被除数列表: [50, 25, 100]
# ── INSPECT/STRING 语句检测 ──
"has_inspect": False, # 是否有 INSPECT 语句
"has_string": False, # 是否有 STRING 语句
# ── PERFORM 模式分类 ──
"perform_patterns": [ # 每个 PERFORM 的模式
{"type": "inline", "target": None, "condition": None}, # inline / paragraph / thru / varying / times
{"type": "varying", "target": "WS-I", "condition": "WS-I > 100"},
{"type": "times", "times": 50},
{"type": "until", "condition": "WS-A > 5"},
{"type": "thru", "target": "PARA-A", "thru": "PARA-C"},
],
# ── 主循环定位（含 READ 语句的 PERFORM 块）──
"main_loop": { # 主循环信息（None=无循环）
"type": "perform_until", # perform_until / perform_varying / read_loop
"read_file": "INFILE", # 在该循环中 READ 的文件
"has_at_end": True, # 是否有 AT END 处理
"at_end_action": "MOVE 'Y' TO WS-EOF", # AT END 处理内容
},
# ── IF 分支类型统计 ──
"if_types": {
"total": 3, # IF 总数
"comparison": 2, # 比较型 (>, <, >=, <=)
"equality": 1, # 等值型 (=)
"compound": 1, # 复合型 (AND/OR)
"nested_depth": 2, # 最大嵌套深度
},
# ── 变量命名模式检测 ──
"variable_patterns": {
"has_prev_key": True, # WS-PREV-* 模式变量
"has_accumulator": True, # WS-*CNT / WS-*SUM 模式变量
"has_error_field": False, # WS-ERR* / WS-MSG* 模式变量
"has_key_field": True, # WS-*KEY 模式变量
"prev_key_fields": ["WS-PREV-KEY"], # 具体的前键值字段名
"accumulator_fields": ["WS-REC-CNT"], # 具体的累加器字段名
},
# ── OPEN 模式 ──
"open_pattern": "sequential", # sequential / reopen(OPEN→CLOSE→再OPEN)
}
```
### 2.3 实现位置
| 新增特征 | 实现文件 | 实现方法 |
|:---------|:---------|:---------|
| SELECT 文件详情 | `read.py` 的 `parse_file_control()` 扩展 | 追加 organization 字段 |
| DIVIDE/INSPECT/STRING | `core.py` `_BrParser` | 添加 IF 语句解析 |
| PERFORM 模式分类 | `core.py` `_BrParser` | BrPerform 属性已存在 |
| 主循环定位 | `core.py` 新函数 `locate_main_loop()` | 搜索含 READ 的 PERFORM 块 |
| IF 类型统计 | `core.py` 新函数 `stat_if_types()` | 遍历 BrIf 的 condition |
| 变量命名模式 | `core.py` 新函数 `detect_variable_patterns()` | 正则匹配字段名 |
| OPEN 模式 | `read.py` 新函数 `detect_open_pattern()` | 检查 OPEN→CLOSE→OPEN |
### 2.4 接口变更
```python
# cobol_testgen/__init__.py — __all__ 不变
# extract_structure() 签名不变，返回字典追加新字段
# 现有调用者不受影响（dict.get() 返回 None 获得默认值）
```
---
## 3. Phase 2: 混淆组判定规则引擎
### 3.1 新模块 `hina/rule_engine/`
创建独立子模块，与现有的 `classifier.py` 互补：
```
hina/
├── __init__.py # 导出 rule_engine 的 API
├── classifier.py # 现有（不变）
├── rule_engine/ # 新增
│ ├── __init__.py
│ ├── confusion_groups.py # 8 混淆组的规则实现
│ ├── contradiction.py # 矛盾检测
│ └── backtrack.py # 回溯机制
```
### 3.2 8 混淆组规则
```python
# hina/rule_engine/confusion_groups.py
def resolve_confusion_pair(features: dict, pair_name: str) -> dict:
"""解决一对混淆组，返回判定结果。
参数:
features — extract_structure() 输出的结构特征
pair_name — 混淆对名称:
"matching_vs_keybreak"
"dedup_vs_nodedup"
"validation_vs_keybreak"
"csv_merge_vs_split"
"simple_vs_two_stage"
"pure_vs_mixed"
"division_50_25_100"
"mn_output_mode"
返回:
{"resolved_type": str, "confidence": float, "evidence": list}
"""
# 规则实现示例 ── "matching_vs_keybreak"
def _matching_vs_keybreak(features: dict) -> dict:
"""匹配 vs key切
判定逻辑:
1. SELECT 文件数 < 2 → 排除匹配 → key切
2. IF 类型统计中 3 路 IF(comparison) 占比 > 50% → 匹配
3. 2 路 IF(equality) 为主 + WS-PREV-KEY 存在 → key切
4. 有累加器(WS-*CNT) + WS-PREV-KEY + 2 路 IF → key切
5. 输入文件 ≥ 2 + 3 路 IF → 匹配
6. 无法确定 → 回退到 conflict_score
"""
file_count = len(features.get("select_files", {}))
if_types = features.get("if_types", {})
var_patterns = features.get("variable_patterns", {})
evidence = []
if file_count >= 2:
evidence.append("file_count>=2 → possible matching")
comp_ratio = if_types.get("comparison", 0) / max(if_types.get("total", 1), 1)
if comp_ratio > 0.5:
evidence.append("comparison IF ratio > 50% → matching signature")
if var_patterns.get("has_prev_key") and var_patterns.get("has_accumulator"):
evidence.append("WS-PREV-KEY + accumulator → keybreak signature")
# 综合判断
matching_score = sum(1 for e in evidence if "matching" in e)
keybreak_score = sum(1 for e in evidence if "keybreak" in e)
if matching_score > keybreak_score:
return {"resolved_type": "マッチング", "confidence": 0.7 + matching_score * 0.1,
"evidence": evidence}
elif keybreak_score > matching_score:
return {"resolved_type": "キーブレイク", "confidence": 0.7 + keybreak_score * 0.1,
"evidence": evidence}
else:
return {"resolved_type": "unknown", "confidence": 0.5, "evidence": evidence}
```
### 3.3 矛盾检测
```python
# hina/rule_engine/contradiction.py
# 7 个矛盾对
CONTRADICTION_PAIRS = [
("matching_vs_keybreak", {
"type_a": "マッチング",
"type_b": "キーブレイク",
"rule": lambda f: f.get("variable_patterns", {}).get("has_prev_key"),
"tiebreaker": "file_count", # file_count ≥ 2 → matching wins
}),
("dedup_vs_nodedup", {
"type_a": "項目チェック(重複含む)",
"type_b": "項目チェック(重複含まず)",
"rule": lambda f: f.get("variable_patterns", {}).get("has_prev_key"),
"tiebreaker": "prev_key_exists", # WS-PREV-KEY → 含重复 wins
}),
("validation_vs_keybreak", {
"type_a": "項目チェック",
"type_b": "キーブレイク",
"rule": lambda f: f.get("variable_patterns", {}).get("has_error_field"),
"tiebreaker": "has_error_field", # WS-ERR* → 校验 wins; WS-*CNT → key切 wins
}),
# ... 其余 4 个
]
def detect_contradictions(features: dict, candidates: list[str]) -> list[dict]:
"""检测候选类型中的矛盾对，返回矛盾列表。"""
def resolve_contradiction(features: dict, contradiction: dict) -> str:
"""使用 tiebreaker 规则解决单个矛盾。"""
```
### 3.4 回溯机制
```python
# hina/rule_engine/backtrack.py
class BacktrackResolver:
"""当混淆组判定进入死胡同时，回溯到 extract_structure 重新提取特征。"""
def __init__(self, structure_extractor: callable):
self.extract = structure_extractor
self.max_rounds = 3
def resolve(self, cobol_source: str, initial_features: dict) -> dict:
"""多轮判定。每轮检测矛盾→回溯→重新提取→重新判定。"""
features = initial_features
for round_num in range(self.max_rounds):
# Step 1: 检测矛盾
contradictions = detect_contradictions(features, candidates)
if not contradictions:
# 无矛盾，返回最终结果
return self._finalize(features)
# Step 2: 解析矛盾
for c in contradictions:
resolution = resolve_contradiction(features, c)
# Step 3: 如果需要更多信息，回溯重新提取
if self._needs_backtrack(contradictions):
refined_source = self._refine_extraction(cobol_source, contradictions)
features = self.extract(refined_source)
return self._finalize_with_warning(features)
```
### 3.5 接口变更
```python
# hina/__init__.py — __all__ 追加
"resolve_confusion_pair", # (features, pair_name) → dict
"detect_contradictions", # (features, candidates) → list[dict]
"BacktrackResolver", # class — 多轮判定
```
---
## 4. Phase 3: 确信度 4 因子计算
### 4.1 新函数
在 `hina/classifier.py` 中新增确信度计算函数，或者创建 `hina/confidence.py`：
```python
# hina/confidence.py — 新增文件
def compute_confidence_v2(
keyword_result: dict, # detect_keyword() 的输出
structure_features: dict, # extract_structure() 的输出
contradictions: list[dict], # contradiction.detect_contradictions() 的输出
resolution: dict # confusion_groups 的输出
) -> dict:
"""四因子确信度计算。
公式:
confidence = base × context_factor × consistency_factor × structure_factor
参数:
keyword_result — {matches: [(category, confidence, keyword)], ...}
structure_features — extract_structure 输出的完整字典
contradictions — 矛盾列表
resolution — 混淆组解决结果
返回:
{
"confidence": float, # 最终确信度 (0~1)
"base": float, # 基础确信度
"context_factor": float, # 上下文因子
"consistency_factor": float, # 一致性因子
"structure_factor": float, # 结构一致性因子
"judgment": str, # "auto" / "review" / "manual" / "impossible"
"needs_review": bool,
}
"""
```
### 4.2 因子定义
```
基础确信度:
L1 关键字规则对应的基准确信度 (0.70~0.99)
DB操作=0.95, SORT=0.95, CALL=0.90, 编辑输出=0.80, ...
上下文因子:
关键字匹配数 ≥ 3 → 1.0
关键字匹配数 = 2 → 0.95
关键字匹配数 = 1 → 0.90
需要上下文确认 → 0.50
一致性因子:
无矛盾 → 1.0
有矛盾已解决 → 0.90
有矛盾未解决 → 0.80
多重矛盾 (≥3) → 0.50
结构一致性因子:
结构完全匹配 (5/5 特征一致) → 1.0
部分一致 (3-4/5) → 0.7
少量一致 (1-2/5) → 0.5
无法确定 → 0.3
综合判定:
≥ 90% → 自动判定 ("auto")
70-89% → 自动判定 + 建议 Review ("review")
50-69% → Agent 提案 + 人工确认 ("manual")
< 50% → 判定不可，全部人工 ("impossible")
```
### 4.3 接口变更
```python
# hina/__init__.py — __all__ 追加
"compute_confidence_v2", # 四因子确信度计算
"compute_confidence", # 已有函数保持不动（旧版调用者不受影响）
```
### 4.4 质量门禁公式更新（gcov 集成）
Phase 0.6 完成后，`hina/gate.py` 的评分公式改为双模式：
```
当前（gcov 未启用）:
quality_score = branch_rate×0.5 + paragraph_rate×0.5 + confidence×0.4
新增 quality_score_v2（gcov 启用时）:
quality_score_v2 = static_cov×0.3 + gcov_cov×0.4 + confidence×0.3
```
- 静态覆盖率 30% — 快速参考，验证数据生成完整性
- gcov 动态覆盖率 **40%** — 权重最高，代表真实执行结果
- HINA 确信度 30%
**新增文件**: `coverage/compare_coverage.py` — 对比静态与 gcov 覆盖率，定位虚假覆盖
```python
def compare_coverage(program_name: str) -> dict:
"""返回 {static, dynamic, gap, misleading_branches}"""
```
---
## 5. Phase 4: 33+2 种程序类型 COBOL 测试样本
### 5.1 目录结构
```
test-data/cobol/ # 已有 HINA001~101 保留
├── HINA001.cbl # 已有
├── ...
├── HINA101.cbl # 已有
│
├── category_matching/ # 匹配系 (10种)
│ ├── MT01_1TO1.cbl
│ ├── MT02_1TON.cbl
│ ├── MT03_NTO1.cbl
│ ├── MT16_TWO_STAGE_1TO1.cbl
│ ├── MT17_TWO_STAGE_NTO1.cbl
│ ├── MT18_MN_TO_M.cbl
│ ├── MT19_MN_TO_N.cbl
│ ├── MT20_MN_TO_MXN.cbl
│ ├── MT32_MIXED_SAME_KEY.cbl
│ └── MT33_MIXED_DIFF_KEY.cbl
│
├── category_sort/ # SORT/ MERGE (2种)
│ ├── ST01_SORT.cbl
│ └── ST02_MERGE.cbl
│
├── category_division/ # 分割系 (3种)
│ ├── DV01_DIVIDE_50.cbl
│ ├── DV02_DIVIDE_25.cbl
│ └── DV03_DIVIDE_100.cbl
│
├── category_validation/ # 校验 (1种，补充)
│ ├── VL01_CHECK_WITH_DUP.cbl
│ └── VL02_CHECK_NO_DUP.cbl
│
├── category_csv/ # 文件转换 (3种)
│ ├── CV01_CSV_NO_NEWLINE.cbl
│ ├── CV02_CSV_WITH_NEWLINE.cbl
│ └── CV03_ASCII_EBCDIC.cbl
│
├── category_cics/ # online (1种)
│ └── CI01_CICS.cbl
│
└── category_db/ # DB操作 (1种，补充)
└── DB01_SELECT_UPDATE.cbl
```
### 5.2 样本规范
每个 COBOL 测试样本必须：
1. **可编译** — 用 `cobc -x -std=ibm-strict` 编译通过
2. **10-50 行** — 足够表达类型特征，不要过大
3. **包含关键特征** — 每种类型独有的关键字和结构模式
4. **有注释** — 开头的星号注释说明类型编号和名称
5. **HEADER 注释**:
```cobol
* ==== TYPE: MT01 マッチング(1:1) ====
* 特征: 2 输入文件 SELECT, IF KEY = 比较, 3路 IF, 无累加器
* BRANCHES: 4 (2 IFs), DECISIONS: 2
* SELECT COUNT: 2, OPEN COUNT: 2
```
### 5.3 实现顺序
按依赖关系分 3 批创建：
```
第一批 (Phase 4a): 匹配系 10 种 + SORT/MERGE 2 种
依赖: 这 12 个样本是 Phase 7-8 测试的基础
第二批 (Phase 4b): 分割系 3 种 + 校验 2 种 + 文件转换 3 种
依赖: 这 8 个样本是 Phase 7 测试的基础
第三批 (Phase 4c): CICS 1 种 + DB 1 种
依赖: 需要模拟器环境，可先做代码样本，延迟测试
```
---
## 6. Phase 5: 参数化测试数据生成引擎
### 6.1 独立模块 `parametrized/`（项目根目录）
```
项目根目录/
├── parametrized/ ← 独立！不是 cobol_testgen 的子模块
│ ├── __init__.py
│ ├── matching.py # 匹配系数据生成
│ ├── sort.py # SORT 数据生成
│ ├── division.py # 分割系数据生成
│ ├── validation.py # 校验系数据生成
│ ├── csv_conversion.py # CSV→FB 数据生成
│ └── common.py # 通用工具
依赖方向:
parametrized/ → cobol_testgen (需要 PIC 解析算边界值)
parametrized/ → data/ (构造 Field/TestCase 对象)
cobol_testgen → parametrized ❌ 禁止
```
**理由**：parametrized/ 的输入是数值参数（记录数、匹配率、不平衡比），不是 COBOL 源码。放在 cobol_testgen/ 下会使 COBOL 解析引擎依赖测试工具。独立模块保持分层干净。
### 6.2 类型专属参数化
```python
# cobol_testgen/parametrized/matching.py
def generate_matching_data(
matching_type: str, # "1:1" / "1:N" / "N:1"
record_count_r01: int,
record_count_r02: int,
key_match_ratio: float = 1.0, # 匹配率（用于剩余件测试）
imbalance_ratio: float = 1.0, # 不平衡比
) -> tuple[list[dict], list[dict]]:
"""生成匹配系测试数据。
返回:
(主文件记录列表, 从件记录列表)
文件间通过 KEY 字段关联。
"""
def generate_keybreak_data(
group_count: int, # key 组数
records_per_group: int, # 每组件数
sum_type: str = "accumulate", # "accumulate" / "aggregate" / "mark"
) -> list[dict]:
"""生成 key 切测试数据。
返回:
按 KEY 分组的数据，组间 KEY 值变化触发中断。
"""
# cobol_testgen/parametrized/division.py
def generate_division_data(
division_type: int, # 50 / 25 / 100
record_count: int, # 总件数（整数倍/余数/不足）
) -> list[list[dict]]:
"""生成分割系测试数据。
返回:
按分割文件分组的记录列表:
[[文件1的记录], [文件2的记录], ...]
文件数 = ceil(record_count / division_type)
"""
```
### 6.3 通用数据生成工具
```python
# cobol_testgen/parametrized/common.py
def generate_zero_byte_file(path: str):
"""生成 0 字节空文件（VSAM 空 cluster 或顺序 0 字节）。"""
def generate_status_35_scenario(path: str):
"""STATUS 35 场景：不生成文件，让 OPEN 找不到 DD。"""
def generate_minimal_records(fields: list[Field]) -> list[dict]:
"""各文件生成 1 条正常记录。"""
def generate_boundary_values(field: Field) -> dict:
"""从 PIC 解析 S9(7)V99 → 生成 max/min/溢出值。"""
def generate_sorted_records(fields: list[Field], record_count: int) -> list[dict]:
"""按 ASCENDING/DESCENDING KEY 生成已排序序列。"""
def generate_duplicate_keys(records: list[dict], key_field: str) -> list[dict]:
"""同键值追加 ≥2 件。"""
```
### 6.4 接口变更
```python
# cobol_testgen/__init__.py — __all__ 追加（parametrized 是独立模块，非子包）
from parametrized import (
generate_matching_data, # 匹配系数据
generate_keybreak_data, # key切数据
generate_division_data, # 分割系数据
generate_zero_byte_file, # 空文件
generate_boundary_values, # 边界值
)
```
---
## 7. Phase 6: 日文测试数据生成查找表
### 7.1 新文件 `japanese_data.py`（项目根目录，独立文件）
```python
# japanese_data.py
# ── 查找表 ──
FULLWIDTH_KATAKANA = "アイウエオカキクケコサシスセソタチツテト..."
FULLWIDTH_HIRAGANA = "あいうえおかきくけこさしすせそたちつてと..."
FULLWIDTH_DIGITS = "０１２３４５６７８９"
FULLWIDTH_ALPHA = "ＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺ"
HALFWIDTH_KATAKANA = "ｱｲｳｴｵｶｷｸｹｺｻｼｽｾｿﾀﾁﾂﾃﾄ..."
SJIS_5C_PROBLEM = ["ソ", "噂", "能"] # Shift-JIS 第2字节 0x5C
SJIS_7C_PROBLEM = ["本", "問"] # Shift-JIS 第2字节 0x7C
WAREKI_BOUNDARIES = [
# (元号, 西历开始年, 和历开始, 西历最后日, 和历最后日)
("令和", 2019, "R010501", None, None),
("平成", 1989, "H010108", "2019/04/30", "H310430"),
("昭和", 1926, "S611231", "1989/01/07", "S640107"),
("大正", 1912, "T011231", "1926/12/25", "T151225"),
("明治", 1868, "M451229", "1912/01/29", "M450129"),
]
# ── 生成函数 ──
def generate_fullwidth_text(field: Field) -> str:
"""PIC N 字段 → 全角文字填充。"""
def generate_halfwidth_katakana(field: Field) -> str:
"""PIC X 字段 → 半角假名填充。"""
def generate_sjis_5c_problem(field: Field) -> str:
"""生成含 5C 问题文字的字符串。"""
def generate_sjis_7c_problem(field: Field) -> str:
"""生成含 7C 问题文字的字符串。"""
def generate_wareki_date(wareki_type: str) -> str:
"""生成和历日期字符串。"""
def generate_wareki_boundary(era: str) -> tuple[str, str]:
"""生成指定元号的边界日期对（末日 → 初日）。"""
def generate_encoding_test_data(
from_encoding: str,
to_encoding: str,
) -> tuple[bytes, bytes]:
"""生成编码转换测试数据（EBCDIC→SJIS→UTF-8 三段）。"""
def select_data_type(field: Field) -> str:
"""选择数据类型: PIC N → 日文 / PIC 9 → 数值 / PIC X → 半角"""
```
### 7.2 接口变更
```python
# cobol_testgen/__init__.py — __all__ 追加
"generate_fullwidth_text",
"generate_halfwidth_katakana",
"generate_wareki_date",
```
---
## 8. Phase 7-10: 类型别测试套件
### 8.1 测试文件清单
```
tests/
├── parametrized/
│ ├── test_matching.py # 匹配系 ~15 测试 (Phase 7)
│ ├── test_division.py # 分割系 ~9 测试 (Phase 7)
│ ├── test_csv_conversion.py # 文件转换 ~8 测试 (Phase 7)
│ ├── test_sort_merge.py # SORT/MERGE ~16 测试 (Phase 8)
│ ├── test_call_search.py # CALL/SEARCH ~20 测试 (Phase 8)
│ ├── test_crosscutting.py # 横跨功能 ~70 测试 (Phase 9)
│ └── test_japanese.py # 日文处理 ~31 测试 (Phase 10)
```
### 8.2 测试模板
```python
# tests/parametrized/test_matching.py
"""匹配系深度测试 — 基于 cobol-test-benchmark.md Type 01-03, 16-20, 32-33"""
import pytest
from cobol_testgen.parametrized import generate_matching_data
@pytest.mark.parametrize("r01,r02,match_ratio", [
(10, 10, 1.0), # MT-N001: 1:1 完全匹配
(1, 100, 0.0), # MT-N009: 1:N 极端不平衡
(100, 1, 0.0), # MT-N010: N:1 极端不平衡
])
def test_matching_basic(r01, r02, match_ratio):
"""MT-N001~003: 1:1 / 1:N / N:1 基本匹配"""
main_recs, sub_recs = generate_matching_data(
matching_type="1:1",
record_count_r01=r01,
record_count_r02=r02,
key_match_ratio=match_ratio,
)
assert len(main_recs) == r01
assert len(sub_recs) == r02
```
### 8.3 Phase 7 测试矩阵
| 测试文件 | 覆盖内容 | 测试项数 | 对应文档 |
|:---------|:---------|:--------:|:---------|
| `test_matching.py` | 1:1/1:N/N:1 + 不平衡 + 键重复 + 未排序 + 高级匹配 | 20 | MT-N001~012, AM-N001~008 |
| `test_division.py` | 50/25/100 分割 + 余数 + 不足 + OPEN失败 + 命名 | 9 | S-N001~007, S-A001~002 |
| `test_csv_conversion.py` | 无换行/有换行/引用符/空項目/超长 | 8 | CF-N001~006, CF-A001~002 |
### 8.4 Phase 8 测试矩阵
| 测试文件 | 覆盖内容 | 测试项数 | 对应文档 |
|:---------|:---------|:--------:|:---------|
| `test_sort_merge.py` | SORT升/降/多键/稳定/INPUT/OUTPUT PROCESS + MERGE | 16 | SR-N001~010, MR-N001~003 |
| `test_call_search.py` | CALL字面量/动态/USING/IS INITIAL/嵌套 + SEARCH ALL | 20 | C-N001~009, T-N001~007 |
### 8.5 Phase 9 测试矩阵 (横跨功能)
| 测试文件 | 覆盖内容 | 测试项数 | 对应文档 |
|:---------|:---------|:--------:|:---------|
| `test_crosscutting.py` | 可变长入出力(11) + 循环处理(10) + 数值精度(12) + 日期(18) + 排他(4) + RERUN(4) + 性能(4) | 63 | VL/LP/NP/D/EX/RR/PV |
### 8.6 Phase 10 测试矩阵 (日文)
| 测试文件 | 覆盖内容 | 测试项数 | 对应文档 |
|:---------|:---------|:--------:|:---------|
| `test_japanese.py` | PIC N全角(5) + 半角假名(5) + 外字(6) + 5C/7C(4) + 编码转换(8) + 全角空格(3) | 31 | J-N/K/G/D/X/S |
---
## 9. Phase 11: 完整类型判定管道
### 9.1 新模块 `hina/pipeline/`
```
hina/
├── rule_engine/ # 混淆组规则 (P2)
├── confidence.py # 确信度计算 (P3)
├── pipeline/ # 完整类型判定管道 (合并自 classification_pipeline/)
│ ├── __init__.py
│ └── pipeline.py # 管道编排
```
### 9.2 管道流程
```python
# hina/pipeline/pipeline.py
def classify_program(cobol_source: str) -> dict:
"""完整程序类型判定管道。
流程:
1. 并行执行:
a. 关键字识别 (detect_keyword) — 11 类 L1 关键字
b. 结构提取 (extract_structure) — 全部特征
2. 关键字确信度 ≥ 90% → 直接输出类型
（DB操作/SORT/MERGE/online 等高确信度独占类型）
3. 关键字 50-89% → 进入混淆组判定
a. 结构解析 (PERFORM模式/主循环/IF分支)
b. 8 混淆组规则引擎
c. 4 因子确信度计算
d. 矛盾检测 → 有矛盾则回溯
4. 关键字 < 50% → Agent 辅助判定
a. classify_with_llm() 调用
b. LLM 返回建议类型
c. 规则引擎验证 LLM 结果
5. 输出最终判定 JSON
"""
```
### 9.3 输出格式
```python
{
"program_name": "HINA005",
"category": "condition_heavy", # 混淆组
"subtype": "simple_if", # 具体类型
"type_code": "05", # 33+2 中的编号
"method": "keyword", # keyword / rule_engine / agent
# ── 确信度详情 ──
"confidence": 0.92,
"confidence_detail": {
"base": 0.95,
"context_factor": 1.0,
"consistency_factor": 0.9,
"structure_factor": 1.0,
},
# ── 判定依据 ──
"evidence": [
"EXEC SQL → DB操作 (keyword, 95%)",
"SELECT count=1, OPEN count=1",
"IF branches=2, decisions=1",
"No contradictions detected",
],
# ── 是否需要 Review ──
"needs_review": False,
# ── 测试策略建议 ──
"testing_strategy": {
"required_tests": 5,
"coverage_target": "branch",
"supplement_strategy": "incremental",
},
}
```
### 9.4 集成到 orchestrator
```python
# orchestrator.py — 替换现有的 HINA 分类步骤
def run_pipeline(cfg: Config, ...) -> VerificationRun:
# ... 现有代码 ...
# ── 类型判定（替换现有 HINA 步骤） ──
from hina/pipeline import classify_program
classification = classify_program(cobol_src_text)
vr.hina_type = classification["category"]
vr.hina_confidence = classification["confidence"]
vr.debug["classification"] = classification
# 如果确信度 < 50%，标记为人工处理
if classification["confidence"] < 0.5 and classification["needs_review"]:
vr.quality_warn = f"类型判定确信度过低({classification['confidence']:.0%})，建议人工确认"
# ... 后续代码不变 ...
```
---
## 10. Phase 12: 文档更新
### 10.1 更新文件
| 文件 | 更新内容 |
|:-----|:---------|
| `docs/module-interfaces.md` | 追加 hina/pipeline 模块接口；追加 parametrized 子模块接口；更新 hina 模块接口（rule_engine, confidence_v2） |
| `docs/test-plan.md` → v3.0 | 追加 33+2 程序类型覆盖行；追加类型别测试矩阵；追加横跨功能测试行；追加日文测试行；更新总测试数预期（412 → 600+） |
| `docs/cobol-coverage-matrix.md` | 追加程序类型覆盖行；追加测试基准覆盖行；更新覆盖率目标 |
### 10.2 测试计划 v3.0 更新内容
```markdown
## 测试预期（更新版）
| 维度 | v2.0 | v3.0 追加 | v3.0 总计 |
|:-----|:----:|:---------:|:---------:|
| L0 单元测试 | 280 | +50 (参数化引擎) | 330 |
| L1 类型测试 | 0 | +80 (Phase 7-8) | 80 |
| 横跨功能测试 | 0 | +70 (Phase 9) | 70 |
| 日文测试 | 0 | +31 (Phase 10) | 31 |
| 非功能测试 | 6 | +10 | 16 |
| 已有回归 | 112 | — | 112 |
| **总计** | **412** | **+241** | **~653** |
```
---
## 11. 依赖关系与分工矩阵
### 11.1 Phase 依赖图
```
Phase 1 (特征提取) ──→ Phase 2 (规则引擎) ──→ Phase 3 (确信度)
│ │ │
│ └────────┬───────────────┘
│ │
│ ▼
│ Phase 11 (hina/pipeline)
│ │
▼ ▼
Phase 5 (parametrized/) Phase 4 (COBOL样本)
│ │
└────────┬──────────────────┘
│
▼
Phase 7-10 (测试套件)
│
▼
Phase 12 (文档)
```
### 11.2 并行执行阶段
```
可以完全并行:
Phase 1 (A) + Phase 4 (C) + Phase 5 (A) + Phase 6 (B)
Phase 2 (D) + Phase 4b (C)
Phase 7-8 (F/G) + Phase 9 (F/G) + Phase 10 (B)
测试执行阶段 (所有人可并行写自己的测试)
需要串行:
Phase 1 → Phase 2 → Phase 3 → Phase 11 (D 负责全链路)
Phase 4 → Phase 7-8 (需要样本才能测试)
Phase 5 → Phase 7-10 (需要参数化引擎才能生成测试数据)
```
### 11.3 分工矩阵
| 开发者 | Phase | 模块 | 工作量 |
|:-------|:------|:-----|:-------|
| **A** | 1, 5 | cobol_testgen 扩展 + parametrized | 3 天 |
| **B** | 6, 10, 12 | japanese_data + 日文测试 + 文档 | 2 天 |
| **C** | 4, 7 | 33+2 COBOL 样本 + 匹配/分割测试 | 3 天 |
| **D** | 2, 3, 11 | rule_engine + confidence + pipeline | 4 天 |
| **E** | 6, 10 | japanese_data + 日文测试、LLM 提示词优化 | 2 天 |
| **F** | 8, 9 | SORT/MERGE/CALL/SEARCH + 横跨功能 | 3 天 |
| **G** | 0.6, 8 | gcov 基础设施 + SORT/MERGE/SEARCH 测试 | 3 天 |
| **H** | 4c, 11 集成 | CICS/DB 样本 + orchestrator 集成 | 2 天 |
### 11.4 总工时估算
| Phase | 内容 | 人日 |
|:------|:-----|:----:|
| P1 | extract_structure 扩展 | 1.5 |
| P2 | 混淆组规则引擎 | 2.0 |
| P3 | 确信度 4 因子 | 1.0 |
| P4 | 33+2 COBOL 样本 | 2.0 |
| P5 | 参数化数据生成 | 2.0 |
| P6 | 日文数据生成 | 1.0 |
| P7 | 匹配/分割/CSV 测试 | 1.5 |
| P8 | SORT/MERGE/CALL/SEARCH 测试 | 1.5 |
| P9 | 横跨功能测试 | 2.5 |
| P10 | 日文测试 | 1.5 |
| P11 | 类型判定管道 | 2.0 |
| P12 | 文档 | 1.0 |
| | **总计** | **~19.5 人日** |
---
## 12. 接口变更一览
### 12.1 向后兼容（现有代码不受影响）
| 变更 | 类型 | 说明 |
|:-----|:-----|:------|
| `extract_structure()` 返回追加字段 | ✅ 兼容 | 现有调用用 `dict.get()`，新字段不出现时返回 None |
| `compute_confidence()` 保留 | ✅ 兼容 | 新增 `compute_confidence_v2()` 并行存在 |
| `orchestrator.py` 导入路径修改 | ✅ 兼容 | 已改为模块顶层导入 |
| `__init__.py` 加 `__all__` | ✅ 兼容 | 只是显式声明已有接口 |
### 12.2 非兼容（需同步更新调用者）
| 变更 | 类型 | 如何处理 |
|:-----|:-----|:---------|
| `hina/__init__.py` 新增 `__all__` | ⚠️ 通知 | 仅影响 `from hina import *` 用户（无此类代码）|
| `cobol_testgen/__init__.py` 新增 `__all__` | ⚠️ 通知 | 仅影响 `from cobol_testgen import *` 用户（无此类代码）|
| `orchestrator.py` 导入从 `from x.y import z` 改为 `from x import z` | ⚠️ 通知 | 已在本次修改中同步更新 |
### 12.3 新增公开 API 汇总
```python
# parametrized/ __all__（新增独立模块）:
"generate_matching_data" # Phase 5
"generate_keybreak_data" # Phase 5
"generate_division_data" # Phase 5
"generate_boundary_values" # Phase 5
# japanese_data.py（新增独立文件）:
from japanese_data import generate_fullwidth_text, generate_halfwidth_katakana, generate_wareki_date
# hina __all__ 追加:
"resolve_confusion_pair" # Phase 2
"detect_contradictions" # Phase 2
"BacktrackResolver" # Phase 2
"compute_confidence_v2" # Phase 3
"classify_program" # Phase 11 — hina.pipeline.pipeline.classify_program
```
---
## 附录：快速开始指南
### 对于 A（cobol_testgen 扩展）
```bash
# 1. 扩展 read.py — 添加 SELECT organization 和 OPEN 模式检测
# 2. 扩展 core.py — 添加 DIVIDE/INSPECT/STRING 检测、PERFORM 分类、IF 统计、变量模式、主循环
# 3. 更新 __init__.py __all__
```
### 对于 D（规则引擎 + 确信度 + 管道）
```bash
# 1. 创建 hina/rule_engine/ — 8 混淆组规则（独立命名函数）
# 2. 创建 hina/confidence.py — 四因子计算
# 3. 创建 hina/pipeline/ — 完整管道编排
# 4. 修改 orchestrator.py — 替换 HINA 分类步骤
```
### 对于 C（COBOL 样本 + 测试）
```bash
# 1. 创建 test-data/cobol/category_matching/ — 10 个匹配系样本
# 2. 创建 test-data/cobol/category_sort/ — SORT/MERGE 样本
# 3. 创建 tests/parametrized/test_matching.py
# 4. 驱动测试: python -m pytest tests/parametrized/test_matching.py
```
### 对于 B（日文处理 + 文档）
```bash
# 1. 创建 japanese_data.py（项目根目录）— 查找表 + 生成函数
# 2. 创建 tests/parametrized/test_japanese.py
# 3. 更新 docs/module-interfaces.md
# 4. 更新 docs/test-plan.md → v3.0
```
---
## 13. COBOL 覆盖率测试体系 — 与各 Phase 的集成
> 覆盖率测试不是独立章节，而是贯穿多个 Phase 的基础设施。
> 已在 Phase 1.1（Phase 0.6）中新增 gcov 基础设施。
> 以下列出覆盖率的其他部分的分布位置：
| 覆盖率内容 | 所在 Phase | 说明 |
|:-----------|:----------|:------|
| gcov 基础设施（环境验证 + collect_gcov 修复 + Config 字段 + 全链路测试）| **Phase 0.6** (1.1节) | F 负责，3h |
| 质量门禁公式更新（quality_score_v2）+ 静态 vs 动态对比报告 | **Phase 3** (4.4节) | 新增 gcov 权重 40% |
| 各类型 gcov 验证测试（约 15 个） | **Phase 7-10** | 每个类型群至少 1 条 gcov 测试 |
| orchestrator gcov_enabled 集成 | **Phase 11** (9.5节) | 连接 Config → orchestrator → gate.py |
### 13.1 覆盖率目标
**模块覆盖率（pytest --cov）:**
| 模块 | 目标 |
|:-----|:----:|
| cobol_testgen/* | ≥ 90% |
| hina/* | ≥ 85% |
| comparator/* | ≥ 85% |
| runners/* | ≥ 70% |
| orchestrator.py | ≥ 85% |
**程序覆盖率（gcov 验证，各类型群最低 line_rate）:**
| 类型群 | 门槛 | 理由 |
|:-------|:----:|:------|
| 条件分支(IF/EVALUATE) | ≥ 70% | 分支密集，应高覆盖 |
| 匹配系 | ≥ 60% | 至少覆盖关键 IF 分支 |
| SEARCH ALL | ≥ 60% | 命中/未命中均需覆盖 |
| CALL | ≥ 60% | 主程序 + 子程序 |
| SORT | ≥ 50% | 大量 I/O，代码行不多 |
| 分割系 | ≥ 50% | 文件操作密集 |
| 编辑输出 | ≥ 50% | WRITE 语句需要实际输出 |
**静态 vs 动态差距**: 同类差距 ≤ 30%（超过说明静态分析不可靠）
> 门槛说明：基于 HINA 现有 10 个程序的 gcov 预测数据。
> 纯逻辑程序（IF/EVALUATE）可达 70%+，I/O 密集程序（SORT/分割）约 50%。
> 上线后根据实测数据调整。
---
## 14. 架构审核决议汇总
> 来源: `/plan-eng-review` | 日期: 2026-06-19
### 14.1 审核决策
| 分类 | 决策 | 方案 | 结果 |
|:-----|:-----|:-----|:-----|
| 架构 | classification_pipeline/ 归属 | 合并到 hina/pipeline/ | ✅ 采纳 |
| 架构 | parametrized/ 归属 | 独立模块（项目根目录） | ✅ 采纳 |
| 架构 | japanese_data.py 归属 | 独立文件（项目根目录） | ✅ 采纳 |
| 架构 | orchestrator 过渡 | 并行开发，一次性替换 | ✅ 采纳 |
| 架构 | COBOL 样本兼容 | 不可编译类型用注释模拟关键字 | ✅ 采纳 |
| 代码质量 | 矛盾判定规则 | 独立命名函数取代 lambda | ✅ 采纳 |
| 测试 | 新模块单元测试 | 每个 Phase 包含自身测试 | ✅ 采纳 |
| 性能 | 回溯机制 | 加 30s 超时降级 | ✅ 采纳 |
### 14.2 NOT in Scope
| 项目 | 理由 |
|:-----|:------|
| CICS/DB 真实环境集成测试 | 需要大型机模拟器 |
| PySpark 完整管道验证 | Java 兼容性问题 |
| 多语言国际化（除日文外） | 33+2 类型未要求 |
| CI/CD 性能基准自动化 | 不属于 12 个 Phase |
### 14.3 实现任务
- [ ] **T1 (P1, human: ~2h)** — 扩展 extract_structure 新增 8 类特征
- [ ] **T2 (P2, human: ~3h)** — hina/rule_engine/ 8 混淆组（独立函数）
- [ ] **T3 (P3, human: ~1.5h)** — hina/confidence.py 4 因子确信度
- [ ] **T4 (P4, human: ~2.5h)** — test-data/cobol/ 33+2 样本
- [ ] **T5 (P5, human: ~2.5h)** — parametrized/ 数据生成引擎
- [ ] **T6 (P6, human: ~1h)** — japanese_data.py 日文查找表
- [ ] **T7 (P7-10, human: ~6h)** — 类型别测试套件 (~241 测试)
- [ ] **T8 (P11, human: ~2.5h)** — hina/pipeline/ 完整管道 + orchestrator 集成
- [ ] **T9 (P12, human: ~1h)** — 文档更新
### 14.4 总测试预期
```
现有: 428 测试
新增: ~60 (新模块自身单元测试)
新增: ~241 (类型别测试套件 P7-10)
总计: ~729 测试
```
### 14.5 并行策略
```
Lane A: P1 (cobol_testgen 扩展) → 独立
Lane B: P4 (COBOL 样本) → 独立，需先完成
Lane C: P5 (parametrized/) → 需要 cobol_testgen 的 PIC 解析
Lane D: P6 (japanese_data) → 独立
Lane E: P2 (rule_engine) → 需要 P1 的特征
└── P3 (confidence) → 需要 P2
└── P11 (pipeline) → 需要 P2+P3
Lane F: P7-10 (测试套件) → 需要 P4+P5+P6
└── P12 (文档) → 最后
启动顺序:
第 1 批 (并行): Lane A + Lane B + Lane D
第 2 批: Lane C (P1 完成 + 已有 data/) + Lane E (P1 完成)
第 3 批: Lane F (P4+P5+P6 完成)
最后: P12
```
---
## 15. 验收标准
> 所有 Phase 完成后，用以下标准验证是否达标。
| 编号 | 验收项 | 验证方法 | 关联 Phase |
|:-----|:-------|:---------|:-----------|
### 15.1 功能验收
| A01 | extract_structure() 返回包含全部 8 个新增字段 | pytest tests/cobol_testgen/ 全部通过 | P1 |
| A02 | 8 个混淆组规则各有 ≥ 2 个测试 | pytest tests/hina/ 覆盖 | P2 |
| A03 | 4 因子确信度的 4 个判定阈值各 ≥ 1 个测试 | pytest tests/hina/ 覆盖 | P3 |
| A04 | 33+2 个 COBOL 样本全部在 test-data/cobol/ 下 | ls test-data/cobol/category_*/ 共 35+ 文件 | P4 |
| A05 | parametrized/ 各生成函数有测试覆盖主要参数组合 | pytest tests/parametrized/ 全部通过 | P5 |
| A06 | japanese_data.py 生成函数返回正确格式 | pytest tests/parametrized/test_japanese.py | P6 |
| A07 | 类型测试套件 ≥ 200 个测试 | pytest --collect-only | P7-10 |
| A08 | hina/pipeline/ 的 3 条判定路径各有测试覆盖 | pytest tests/hina/ 模拟三种路径 | P11 |
| A09 | gcov 全链路验证测试通过 | pytest tests/test_gcov_basic.py | P0.6 |
| A10 | 质量门禁 gcov 模式下 quality_score_v2 工作 | pytest tests/hina/test_gate.py 覆盖 | P3 |
### 15.2 覆盖率验收
| 验收项 | 目标 | 验证方法 |
|:-------|:----:|:---------|
| 模块覆盖率（pytest --cov）| ≥ 68% | pytest --cov=. |
| 核心管道覆盖率 | ≥ 85% | pytest --cov=cobol_testgen --cov=hina --cov=orchestrator |
| Python 测试总数 | ≥ 650 | pytest --collect-only -q |
| gcov 动态验证（可编译类型）| line_rate ≥ 50% | pytest tests/test_gcov_basic.py |
### 15.3 回归验收
- [ ] 所有现有测试通过: pytest tests/ --ignore=e2e/ -q → 0 failed
- [ ] 新增测试不降低现有覆盖率
- [ ] 所有 __all__ 中列出的公开函数有类型注解
---
---
docs/test-plan.md
-884
View File
@@ -1,884 +0,0 @@
# 增强测试系统 — 全面测试计划 v3.0
> 日期: 2026-06-19 | 対象: feat/enhanced-test-phase1 / main
> 測試范围: 全模块 34/36 + web API/Worker | 7 维度 | ~518 testing points
---
## 测试策略
### 覆盖原则
- **Boil the Lake**: AI 使完整性成本趋近于零，推荐完整覆盖而非 happy path
- **按风险优先级**: 管道中枢 > 外部依赖调用 > 数据模型 > 辅助工具
- **维度**: 功能正确性 / 错误恢复 / 边界值 / 并发安全 / 性能衰减 / 安全防护 / 环境依赖
### 测试层次
```
L0: 模块单元 ─ 全模块独立测试 (pytest, ~80 tests)
├── cobol_testgen (API/cond/core/coverage/design/read/output/models)
├── hina (classifier/gate/gcov/agent/retry/strategy)
├── orchestrator ← 新增: 管道中枢
├── web (api/worker) ← 新增: API 端点 + Worker
├── agents (LLM/Parser/Data/Diagnostic) ← 新增
├── config (Config/Mapping) ← 新增
├── runners (4文件) ← 新增
├── jcl (parser/executor) ← 新增
├── quality / storage / preprocessor ← 新增
└── data models (+ dataclass 复杂逻辑)
L1: 结合测试 ─ 模块间数据流 (pytest, ~25 tests)
├── extract_structure → generate_data
├── HINA 分类 → strategy 模板映射
├── quality gate → orchestrator 循环
├── API → Worker → Orchestrator 全链路 ← 新增
├── LLM 链 (Agent1→2→3) 异常回退 ← 新增
├── Config → Runner 选择路由 ← 新增
├── HINA + gcov → 报告渲染 ← 新增
└── JCL 解析 → 执行 ← 新增
L2: HINA 统合测试 (test-data/ 10 programs, ~10 tests)
├── HINA001: 1:1 マッチング
├── HINA005: IF条件分岐
├── HINA025: CALL
└── HINA101: EXEC SQL
L3: 実 COBOL 验证 (jcl-cobol-git/ 4 programs, ~4 tests)
├── CRDVAL / CRDCALC / CRDRPT / GENDATA
└── 实际金额计算一致性确认
L4: 回归测试 ─ 既存 42 测试完全通过
L5: 非功能测试 ─ 性能/并发/安全 ← 新增层级
├── 大文件上传 10MB 边界
├── Worker 并发任务处理
├── 路径遍历/文件类型校验
└── LLM 超时/隔离时优雅降级
L6: E2E UI 测试 ─ Playwright 浏览器测试 ← 新增层级
├── 上传页加载/表单元素
├── 文件上传 → 202 响应 → 轮询状态
└── 结果页面字段表格/摘要
```
### 测试手法
| 手法 | 适用层级 | 说明 |
|:-----|:--------|:------|
| TDD (红绿) | L0 | 先写测试，再实现 |
| Golden 测试 | L2-L3 | 已知期望值对比 |
| 模糊测试 | L1 | 异常 COBOL 输入容错 |
| 边界值分析 | L0, L5 | PIC 桁数边界、空值、极值 |
| 错误注入 | L0-L1 | LLM timeout/malformed、cobc 编译失败 |
| 降级测试 | L1 | gcov failure/absence 时降级确认 |
| 竞态条件 | L5 | 并发 Worker + Task JSON 文件读写 |
| 安全审计 | L5 | 路径遍历、类型校验、信息泄露 |
---
## L0: 模块单元测试
### 0.1 cobol_testgen API (保持 + 补充)
测试文件: `tests/test_cobol_testgen.py`
| # | 测试名 | 内容 | 输入 | 期待输出 |
|:-:|:-------|:-----|:-----|:---------|
| UT-01 | extract_structure: 空程序 | 空字符串 | `{"total_branches": 0}` |
| UT-02 | extract_structure: IF 1个 | `IF A > B ... ELSE ...` | branches=2, decisions=1 |
| UT-03 | extract_structure: EVALUATE | `EVALUATE X WHEN 1 ... WHEN OTHER` | decisions=1, WHEN 数确认 |
| UT-04 | extract_structure: 多文件 | 3文件程序 | file_count=3 |
| UT-05 | extract_structure: CALL | `CALL 'SUBPGM'` | has_call=True |
| UT-06 | extract_structure: SEARCH ALL | OCCURS+SEARCH ALL | has_search_all=True |
| UT-07 | extract_structure: 固定格式 | 7桁目代码固定格式 | 正常解析(段落数>0) |
| UT-08 | extract_structure: GOBACK | GOBACK 语句 | 非 STOP RUN 但正确退出 |
| UT-09 | extract_structure: ALTER | ALTER X TO PROCEED TO Y | 标记 alter 语句 |
| UT-10 | extract_structure: ENTRY | ENTRY 'ENTPT' | 多入口点识别 |
| UT-11 | extract_structure: 无 PROCEDURE DIVISION | 数据部只有 ID/DATA | 空结构返回，不崩溃 |
| UT-12 | generate_data: 正常生成 | IF 程序 | ≥2 条数据 |
| UT-13 | generate_data: 空程序 | 无分支 | 0 或 1 条 |
| UT-14 | generate_data: 深嵌套 REDEFINES | A REDEFINES B REDEFINES C | 所有变体字段正确取值 |
| UT-15 | generate_data: OCCURS DEPENDING 最大 | ODO 到达最大值 | 数组长度正确 |
| UT-16 | generate_data: PIC 9(18) | 超出 64-bit 范围 | 不溢出，字符串表示 |
| UT-17 | generate_data: SIGN LEADING/TRAILING SEPARATE | SIGN IS LEADING SEPARATE | 符号位正确 |
| UT-18 | incremental_supplement: 差分 | 未覆盖 ID 指定 | 对应 ID 数据 |
| UT-19 | incremental_supplement: 不存在 ID | [-1] | 空列表 |
| UT-20 | check_coverage: 静态报告 | structure 仅 | "note" 含静态限制描述 |
### 0.2 cobol_testgen cond (新增)
测试文件: `tests/cobol_testgen/test_cond.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| CO-01 | parse_single_condition: 数值比较 | `A > 100` | CondLeaf(> 100) |
| CO-02 | parse_single_condition: 文字列 | `B = 'Y'` | CondLeaf(= 'Y') |
| CO-03 | parse_compound: AND | `A > 0 AND B < 5` | CondAnd(>0, <5) |
| CO-04 | parse_compound: OR | `A = 1 OR B = 2` | CondOr(=1, =2) |
| CO-05 | parse_compound: 嵌套 AND+OR | `(A > 0 AND B < 5) OR C = 1` | 正确优先级 |
| CO-06 | mcdc_sets: IF | IF A > 100 | 2 sets |
| CO-07 | mcdc_sets: AND | A > 0 AND B < 5 | 3 sets (MCDC) |
| CO-08 | mcdc_sets: OR | A = 1 OR B = 2 | 3 sets (MCDC) |
| CO-09 | evaluate_tree: 真路径 | A=200 当 A>100 | True |
| CO-10 | evaluate_tree: 假路径 | A=50 当 A>100 | False |
### 0.3 cobol_testgen core (新增)
测试文件: `tests/cobol_testgen/test_core.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| CE-01 | scan_paragraphs: 正常 | 3段落 | 3个段落 |
| CE-02 | scan_paragraphs: 空程序 | 无段落 | 空列表 |
| CE-03 | build_branch_tree: IF | IF 语句 | BrIf 节点 |
| CE-04 | build_branch_tree: EVALUATE | EVALUATE 语句 | BrEval 节点 |
| CE-05 | build_branch_tree: PERFORM | PERFORM VARYING | BrPerform 含循环 |
| CE-06 | build_branch_tree: SEARCH ALL | SEARCH ALL | BrSearch 节点 |
| CE-07 | classify_field_roles: IO / WORKING / LINKAGE | IO / WORKING / LINKAGE 字段 | 正确角色分类 |
| CE-08 | propagate_assignments: 嵌套组 | 子字段赋值传播 | 子字段继承值 |
| CE-09 | propagate_assignments: REDEFINES | REDEFINES 字段赋值 | 共享起始位置 |
### 0.4 cobol_testgen coverage (新增)
测试文件: `tests/cobol_testgen/test_coverage.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| CV-01 | collect_decision_points: IF | 1个 IF | 1个决策点 (2分支) |
| CV-02 | collect_decision_points: EVALUATE | EVALUATE 4 WHEN | 1决策点 4分支 |
| CV-03 | collect_decision_points: SEARCH ALL | SEARCH ALL | 1决策点 |
| CV-04 | mark_coverage: 全覆盖 | 所有分支有测试数据 | 覆盖率 100% |
| CV-05 | mark_coverage: 部分覆盖 | 一半分支有数据 | 覆盖率 50% |
| CV-06 | mark_coverage: 零覆盖 | 无测试数据 | 覆盖率 0% |
| CV-07 | locate_decision_lines: 源码定位 | 已知决策点 | 正确行号 |
| CV-08 | generate_html_report: 基本渲染 | 决策点+统计 | 有效 HTML |
### 0.5 cobol_testgen design (新增)
测试文件: `tests/cobol_testgen/test_design.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| DE-01 | enum_paths: 2层嵌套 | IF 内 IF | 路径枚举数正确 |
| DE-02 | apply_constraint: 数值约束 | field > 100 | 字段值 > 100 |
| DE-03 | apply_constraint: 文字约束 | field = 'ABC' | 字段值 'ABC' |
| DE-04 | apply_constraint: MCDC 约束 | AND 条件 | 满足指定真值 |
| DE-05 | generate_records: 基本 | 已知分支路径 | 记录字段值正确 |
| DE-06 | sync_redefined_fields: REDEFINES | REDEFINES 字段 | 同步后值一致 |
| DE-07 | apply_occurs_depending: ODO | OCCURS DEPENDING ON | 数组长度按依赖字段 |
| DE-08 | make_base_record: 序列值 | seq_num=1 | 字段含序列值 |
### 0.6 cobol_testgen read (新增)
测试文件: `tests/cobol_testgen/test_read.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| RD-01 | preprocess: 固定格式 | 7桁目代码 | 正确提取 |
| RD-02 | preprocess: 自由格式 | `>>SOURCE FORMAT IS FREE` | 正确提取 |
| RD-03 | preprocess: COPY 展开 | `COPY CPYBOOK` | COPY 内容展开 |
| RD-04 | preprocess: 嵌套 COPY | COPY 内含 COPY | 递归展开 |
| RD-05 | extract_data_division: 多段 | ID/DATA/PROCEDURE | DATA DIVISION 文本 |
| RD-06 | parse_pic: 简单 | PIC 9(4) | PicInfo(4, 0) |
| RD-07 | parse_pic: 带小数 | PIC S9(7)V99 | PicInfo(9, 2, signed) |
| RD-08 | parse_pic: COMP-3 | PIC S9(7)V99 COMP-3 | signed, COMP-3 |
| RD-09 | parse_data_division: 层级 | 01/05/10/15 | 正确层级树 |
| RD-10 | parse_data_division: 88-level | 88 AA VALUE 'X' | is_88 识别 |
| RD-11 | parse_data_division: REDEFINES | 字段含 REDEFINES | redefines 属性 |
| RD-12 | parse_data_division: OCCURS | OCCURS 10 TIMES | occurs=10 |
| RD-13 | resolve_copybooks: 多路径 | 搜索多目录 | 找到 COPY |
### 0.7 cobol_testgen output (新增)
测试文件: `tests/cobol_testgen/test_output.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| OU-01 | output_json: 基本 | 3条测试记录 | 有效 JSON 文件 |
| OU-02 | output_input_files: 多方向 | I-O / INPUT 字段 | 文件输出正确 |
### 0.8 HINA Classifier (保持)
测试文件: `tests/hina/test_classifier.py`
| # | 测试名 | 内容 | 输入 | 期待 |
|:-:|:-------|:-----|:-----|:------|
| HC-01 | L1: DB操作 | `EXEC SQL SELECT` | category="DB操作" ≥90% |
| HC-02 | L1: 子程序调用 | `CALL ... LINKAGE SECTION` | category="子程序调用" ≥90% |
| HC-03 | L1: SORT | `SORT WORK-FILE ON KEY` | category="SORT" ≥90% |
| HC-04 | L1: IS INITIAL | `PROGRAM-ID. X IS INITIAL.` | category="IS INITIAL" ≥90% |
| HC-05 | L1: 编辑输出 | `WRITE AFTER ADVANCING` | category="编辑输出" ≥80% |
| HC-06 | L1: 文件编成 | `ORGANIZATION IS` | category="文件编成" ≥90% |
| HC-07 | 关键字重叠 | DB操作+CALL 两者 | 最大确信度关键字胜出 |
| HC-08 | compute_confidence: L1≥90% | L1 仅 | method="keyword" |
| HC-09 | compute_confidence: LLM结果 | LLM 结果 | method="hybrid" |
| HC-10 | compute_confidence: 两者无 | 关键字无+LLM无 | category="unknown" confidence=0 |
### 0.9 HINA Strategy (保持)
测试文件: `tests/hina/test_strategy.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| HS-01 | get_strategy: マッチング | 9 required items |
| HS-02 | get_strategy: キーブレイク | 6 required items |
| HS-03 | get_strategy: 条件分岐 | 4 required items |
| HS-04 | get_strategy: 未知类型 | 空模板 |
| HS-05 | supplement: マーカー追加 | マーカーレコード含む list |
| HS-06 | supplement_only: 特定间隙 | 指定 ID のみマーカー |
### 0.10 HINA Gate (保持)
测试文件: `tests/hina/test_gate.py`
| # | 测试名 | 内容 | 输入 | 期待 |
|:-:|:-------|:-----|:-----|:------|
| QG-01 | 全通过 | branch≥95%, paragraph=100% | passed=True |
| QG-02 | 分岐不足 | branch=80% | passed=False, decision_gaps 有 |
| QG-03 | 段落不足 | paragraph=0.5 | passed=False |
| QG-04 | 数据无 | empty list | passed=False, no_data=True |
| QG-05 | 评分计算 | branch=0.92, para=1.0 | score=0.976 |
### 0.11 HINA Retry (保持 + 补充)
测试文件: `tests/hina/test_retry.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| RH-01 | 即时 PASS | 1次 PASS | heal=0, simple=0 |
| RH-02 | heal 恢复 | BLOCKED→环境修复→PASS | heal=1, simple=0 |
| RH-03 | simple 恢复 | BLOCKED→重试→PASS | heal=0, simple=1 |
| RH-04 | 上限超限 | 全部 FAIL | status=FATAL |
| RH-05 | QUALITY_WARN 不需重试 | QUALITY_WARN→立即返回 | heal=0, simple=0 |
| RH-06 | heal 环境修复失败 | heal 尝试仍然 BLOCKED | simple 回退 | ← 新增 |
| RH-07 | 并发重试计数 | 同时 heal + simple | 计数不竞争 | ← 新增 |
### 0.12 HINA gcov_collector (新增)
测试文件: `tests/hina/test_gcov_collector.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| GC-01 | collect_gcov: cobc 未安装 | 无 cobc 命令 | available=False, reason=cobc_not_found |
| GC-02 | collect_gcov: .gcda/.gcno 不存在 | 工作目录无覆盖文件 | available=False, reason=no_coverage_data |
| GC-03 | collect_gcov: 正常 | 有效 .gcda/.gcno | available=True, line_rate>0 |
### 0.13 HINA Agent (LLM 分类) (补充)
测试文件: `tests/hina/test_agent.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| HA-01 | classify_with_llm: 正常 | 有效结构体 | 返回 dict 含 category |
| HA-02 | classify_with_llm: LLM 返回非法 JSON | LLM 返回乱码 | fallback 分类 | ← 新增 |
| HA-03 | classify_with_llm: LLM 返回空字符串 | LLM 返回 "" | fallback 分类 | ← 新增 |
| HA-04 | classify_with_llm: LLM 超时 | httpx.TimeoutException | fallback + 日志输出 | ← 新增 |
| HA-05 | _parse_llm_response: 合法 JSON | `{"category": "DB操作"}` | 解析成功 |
| HA-06 | _parse_llm_response: 非法 JSON | "暂无" | try/except 不崩溃 |
| HA-07 | _parse_llm_response: 含 markdown 包裹 | `` ```json ... ``` `` | 正确提取 JSON |
| HA-08 | _fallback_classification: 纯 DB | EXEC SQL 无其他 | "DB操作" |
| HA-09 | _fallback_classification: 纯 CALL | CALL 无 SQL | "子程序调用" |
| HA-10 | _fallback_classification: 两者无 | 无关键字匹配 | "unknown" |
### 0.14 orchestrator (新增 — 🔥 高风险)
测试文件: `tests/test_orchestrator.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| OR-01 | run_pipeline: 正常路径 | 所有组件正常工作 | VerificationRun 返回, status=PASS |
| OR-02 | run_pipeline: cobol_testgen 返回空 | extract_structure 空 | pipeline 继续, 适当错误 |
| OR-03 | run_pipeline: HINA Agent 异常 | classify_with_llm 抛出 | 不阻断 pipeline, 日志记录 |
| OR-04 | run_pipeline: quality gate 失败 | 覆盖率不足 | QUALITY_WARN 设置 |
| OR-05 | run_pipeline: gcov 不可用 | collect_gcov 失败 | available=False, pipeline 继续 |
| OR-06 | run_pipeline: Java 编译失败 | mvn 返回非零 | status=BLOCKED, exit_code≠0 |
| OR-07 | run_pipeline: cobc 编译失败 | cobc 返回非零 | status=BLOCKED |
| OR-08 | run_pipeline: Runner 运行失败 | run() 返回非零 | status=BLOCKED |
| OR-09 | run_pipeline: LLM 全部回退 | Agent1/2/3 全部 fallback | 无崩溃, 结果含 fallback 标记 |
| OR-10 | run_pipeline: 无 LLM API key | 环境变量不存在 | Agent1/2/3 使用默认值/failback |
| OR-11 | run_pipeline: 大文件 (10000行 COBOL) | 大型输入文件 | 30秒内完成, 不超时 | ← 新增非功能 |
| OR-12 | _done: 正常结束 | 标准 VerificationRun | 正确写入 report_path |
### 0.15 web/api.py (新增 — 🔥 高风险)
测试文件: `tests/web/test_api.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| WA-01 | GET / 返回 HTML | 无参数 | 200, Content-Type text/html |
| WA-02 | POST /verify 正常上传 | 4个文件 + runner= native | 202, 含 task_id, status=queued |
| WA-03 | POST /verify 文件超 10MB | 超大文件 | 413 |
| WA-04 | POST /verify 缺少文件 | 3个文件 | 422 或 400 |
| WA-05 | POST /verify runner=spark | spark 模式 | 202, runner=spark |
| WA-06 | GET /status 存在任务 | 有效 task_id | 200, 含 status |
| WA-07 | GET /status 不存在 | 无效 task_id | 404 |
| WA-08 | GET /status 任务完成 | 结果已写入 | status=done, fields 含数据 |
| WA-09 | GET /fields 正常 | 有效 task_id | 200, 字段列表 |
| WA-10 | GET /fields 任务不存在 | 无效 task_id | 404 |
| WA-11 | GET / 表单元素存在 | 渲染检查 | 5 个文件/输入元素 |
| WA-12 | 路径遍历防护 | `../../../etc/passwd` 文件上传 | 拒绝或 sanitize | ← 安全 |
### 0.16 web/worker.py (新增 — 🔥 高风险)
测试文件: `tests/web/test_worker.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| WR-01 | main: 无任务 | 空 tasks/ 目录 | 无操作, 继续循环 |
| WR-02 | main: 正常任务 | queued 任务文件 | 处理, 状态→done |
| WR-03 | main: 任务文件损坏 | 非法 JSON | 异常处理, 不崩溃 |
| WR-04 | main: runner=spark 但无 spark-submit | spark-submit 不在 PATH | 状态→blocked, 含 reason |
| WR-05 | main: 并发任务 | 2个 queued 任务 | 依次处理, 各有结果 |
| WR-06 | main: Worker 中断恢复 | running 状态→重启 Worker | running 任务可重新处理 |
| WR-07 | Task 文件状态机 | queued→running→done 转换 | 状态不可逆 |
### 0.17 agents 模块 (新增)
测试文件: `tests/agents/test_agents.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| AG-01 | LLMClient.call: 正常 | 消息列表 | 返回响应字符串 |
| AG-02 | LLMClient.call: 缓存命中 | 相同消息两次调用 | 第二次返回缓存, 不调 API |
| AG-03 | LLMClient.call: 超时 | httpx 超时 | 抛出异常 |
| AG-04 | LLMClient.call: 重试成功 | 首次 500, 重试 200 | 最终成功返回 |
| AG-05 | LLMClient.call: 重试耗尽 | 全部失败 | 抛出异常 |
| AG-06 | Agent1Parser.parse: 正常 COPYBOOK | 合法字段列表 | 返回 FieldTree, 字段数正确 |
| AG-07 | Agent1Parser.parse: LLM 返回非法 JSON | LLM 返回 `not json` | 返回 FieldTree(copybook_name="parse_error") |
| AG-08 | Agent1Parser.parse: JSON 缺失 fields | `{}` | 空 FieldTree, 不崩溃 |
| AG-09 | Agent2Data.design: 正常 | 已知 FieldTree | TestSuite 含测试 case |
| AG-10 | Agent2Data.design: LLM 返回非法 | LLM 异常 | 返回 TestSuite 含 TC-FALLBACK |
| AG-11 | Agent2Data.design: spark_mode | spark=True | SparkConfig 生成 |
| AG-12 | Agent3Diagnostic.analyze: 正常 | FieldResult MISMATCH | 返回诊断字符串 |
### 0.18 config (新增)
测试文件: `tests/config/test_config.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| CF-01 | Config: 默认值 | 无参数 | runner_mode=native, llm_model=gpt-4o-mini |
| CF-02 | Config: from_toml | 有效 TOML 文件 | 正确解析 |
| CF-03 | Config: from_toml 文件不存在 | 不存在路径 | 默认值 |
| CF-04 | Config: from_toml 非法 TOML | 格式错误 | 妥善处理/不崩溃 |
| CF-05 | MappingConfig: 正常 | 有效 YAML 映射 | FieldMapping 列表 |
| CF-06 | MappingConfig: 空映射 | 空 YAML | 空列表 |
| CF-07 | MappingConfig: 格式错误 | 非法 YAML | 解析错误处理 |
### 0.19 runners (新增)
测试文件: `tests/runners/test_runners.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| RN-01 | Runner 抽象类 | 实例化 | TypeError (抽象) |
| RN-02 | NativeJavaRunner.compile: 成功 | mvn 成功 | BuildResult(success=True) |
| RN-03 | NativeJavaRunner.compile: Maven 失败 | mvn 非零退出 | BuildResult(success=False) |
| RN-04 | NativeJavaRunner.run: 正常 | jar 输出 JSON | RunResult(records 含数据) |
| RN-05 | NativeJavaRunner.run: 无输出 | jar 输出空 | RunResult(records=[]) |
| RN-06 | CobolRunner.compile: 成功 | cobc 成功 | BuildResult(success=True) |
| RN-07 | CobolRunner.compile: 编译错误 | cobc 语法错误 | BuildResult(success=False) |
| RN-08 | CobolRunner.compile: gcov 参数 | gcov=True | 含 -fprofile-arcs 参数 |
| RN-09 | CobolRunner.run: 正常 | 二进制执行 | RunResult(success=True) |
| RN-10 | DataWriter.write: 正常 | TestSuite 数据 | 文件写入正确 |
### 0.20 jcl (新增)
测试文件: `tests/jcl/test_jcl.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| JC-01 | parse_jcl: 基本 JOB | JOB + 2 STEP | 1个 Job, 2个 JobStep |
| JC-02 | parse_jcl: COND 参数 | COND=(0,NE) | CondParam(0, NE) |
| JC-03 | parse_jcl: DD 语句 | DD DSN=..., DISP=SHR | DDEntry 含 DSN/DISP |
| JC-04 | parse_jcl: 续行 | 多行 DD 语句 | 合并为单行 |
| JC-05 | parse_jcl: 空文件 | 无内容 | 返回 None |
| JC-06 | parse_jcl: 注释行 | `//* COMMENT` | 跳过注释 |
| JC-07 | parse_jcl: 文件不存在 | 无效路径 | 返回 None |
| JC-08 | JclExecutor.execute: 正常 | 已解析 Job | 执行结果 |
### 0.21 quality (新增)
测试文件: `tests/quality/test_quality.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| QL-01 | L1OffsetValidator.validate: cobc 存在 | 有效 FieldTree | 含 score/mismatches |
| QL-02 | L1OffsetValidator.validate: cobc 不存在 | 无 cobc | 异常或 fallback |
| QL-03 | L2RoundtripValidator.validate: 无 COMP-3 | 无 COMP-3 字段 | pass=True, results=[] |
| QL-04 | L2RoundtripValidator.validate: 有 COMP-3 | 含 COMP-3 字段 | pass=True, 字段值正确 |
### 0.22 storage (新增)
测试文件: `tests/storage/test_storage.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| ST-01 | DiskCache.get/set: 正常 | key-value 存取 | 获取与设置一致 |
| ST-02 | DiskCache.get: 不存在 | 无缓存 key | 返回 None |
| ST-03 | ReportStore.save_history: 正常 | JSONL 写入 | 追加文件 |
| ST-04 | TestDataBundle: 路径 | base_path | cobol_input/spark_input 正确 |
### 0.23 preprocessor (新增)
测试文件: `tests/test_preprocessor.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| PP-01 | expand: 有 COPY 文件 | COPY CPYBOOK → 文件存在 | COPYBOOK 内容展开 |
| PP-02 | expand: 无 COPY 文件 | COPY NOTEXIST | "NOT FOUND" 标记 |
| PP-03 | expand: 无 COPY 语句 | 纯文本 | 原文不变 |
### 0.24 数据模型 (补充断言)
测试文件: `tests/data/test_models.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| DM-01 | Field 构建 | 所有属性 | 属性值正确 |
| DM-02 | FieldTree.flatten: 嵌套 | 层级字段 | 展平字典含所有字段 |
| DM-03 | FieldTree.flatten: 同名字段 | 不同层级同名 | 后覆盖前 |
| DM-04 | VerificationRun: 默认 timestamp | 空构造 | timestamp 自动填充 |
| DM-05 | VerificationRun.verdict: PASS | status=PASS | "PASS" |
| DM-06 | VerificationRun.verdict: BLOCKED | status=BLOCKED | "BLOCKED" |
| DM-07 | VerificationRun.total_fields | matched=5, mismatched=3 | 8 |
| DM-08 | TestSuite.has_spark | spark_config 有/无 | True/False |
| DM-09 | FieldResult 容忍度 | tolerance_applied>0 | 状态含 PASS 但标记 |
### 0.25 报告生成器 (保持)
测试文件: `tests/report/test_generator.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| RG-01 | generate_json: 新字段 | VerificationRun 全字段 | JSON 含所有字段 |
| RG-02 | generate_html: 覆盖率显示 | paragraph_rate>0 | "段落覆盖率" 显示 |
| RG-03 | generate_html: HINA 显示 | hina_type 设置 | "判定类型" 显示 |
| RG-04 | generate_html: HINA 不显示 | hina_type="" | HINA 区不显示 |
| RG-05 | generate_html: 质量评分显示 | quality_score>0 | "质量评分" 显示 |
| RG-06 | generate_html: 质量评分不显示 | quality_score=0 | 质量区不显示 |
| RG-07 | generate_html: 警告显示 | quality_warn 设置 | 警告栏显示 |
| RG-08 | generate_machine_json: 全字段 | VerificationRun | branch_rate 等包含 |
| RG-09 | generate_json: 向后兼容 | 新字段未设置 | 与现有 JSON 同结构 |
### 0.26 comparator (新增)
测试文件: `tests/comparator/test_comparator_all.py`
| # | 测试名 | 内容 | 期待 |
|:-:|:-------|:-----|:------|
| CP-01 | compare_field: 数值完全一致 | c="100.00", j="100.00" | status=PASS |
| CP-02 | compare_field: 数值容忍度内 | c="100.01", j="100.00", tol=0.02 | status=PASS |
| CP-03 | compare_field: 数值超出容忍 | c="110.00", j="100.00", tol=0.02 | status=MISMATCH |
| CP-04 | compare_field: 日期一致 | 同日期不同格式 | PASS |
| CP-05 | compare_field: 字符串 | c="ABC", j="ABC" | PASS |
| CP-06 | align_records: 1:1 | COBOL 1条, Java 1条, 键匹配 | 1个对齐对 |
| CP-07 | align_records: 多对多 | 3条+3条, 键匹配 | 3个对齐对 |
| CP-08 | align_records: 无匹配 | 无共同键 | 空结果 |
| CP-09 | detect_rounding: 有 rounding | c=100, j=99.99 | RoundingResult(detected=True) |
| CP-10 | detect_rounding: 无 rounding | c=100.00, j=100.00 | RoundingResult(detected=False) |
---
## L1: 结合测试
测试文件: `tests/test_integration.py`
| # | 测试名 | 场景 | 期待 |
|:-:|:-------|:------|:------|
| CT-01 | extract→generate 一致性 | 同源 extract→generate | generate_data 可生成数据 |
| CT-02 | HINA→Strategy 映射 | 匹配分类→全标记生成 | 9个标记 |
| CT-03 | QG→incremental 循环控制 | 分支不足→supplement→再检查 | passed=True |
| CT-04 | strategy→TestCase 型一致 | supplement 输出→TestCase 转换 | 可作为 TestCase 使用 |
| CT-05 | orchestrator: 正常路径 | cobol_testgen→HINA→QG→DataWriter | complete_tests 到 DataWriter |
| CT-06 | orchestrator: LLM 异常 | HINA Agent 异常 | 错误日志, pipeline 继续 |
| CT-07 | orchestrator: gcov 无效 | gcov_enabled=False | 动态覆盖率跳过 |
| CT-08 | API→Worker→Orchestrator 全链路 | POST → Worker 消费 → 结果可查 | 状态 queued→running→done | ← 新增 |
| CT-09 | LLM Agent 链异常回退 | Agent1 失败 → Agent2/3 可用 | Agent2 含 TC-FALLBACK | ← 新增 |
| CT-10 | Config→Runner 路由 | runner_mode=spark → SparkJavaRunner | 正确 Runner 实例化 | ← 新增 |
| CT-11 | HINA+gcov→报告渲染 | 覆盖率数据 → 报告 HTML | HTML 含覆盖率和 HINA | ← 新增 |
| CT-12 | JCL 解析→执行 | parse→execute 数据流 | 执行结果 | ← 新增 |
| CT-13 | gcov_collector: 未安装 | gcov 命令不存在 | available=False | ← L1 移入 |
| CT-14 | gcov_collector: 正常 | .gcda/.gcno 存在 | available=True, line_rate 计算 | ← L1 移入 |
| CT-15 | Config: 质量门禁设置 | aurak.toml 变更→from_toml | quality_gate_mode=warn | ← L1 移入 |
---
## L2: HINA 统合测试
测试文件: `test-data/run_validation.py` (HINA*.cbl 10个程序)
| # | 程序 | 验证项 | 期待 |
|:-:|:-----|:-------|:------|
| IT-01 | HINA001 | 匹配结构分析 | 段落≥8, 文件≥2 |
| IT-02 | HINA005 | IF 分支覆盖率 | 分支≥6, 决策点≥3 |
| IT-03 | HINA006 | EVALUATE 覆盖率 | 分支≥6, 决策点≥3 |
| IT-04 | HINA007 | 键中断分析 | 段落≥3, 文件≥2 |
| IT-05 | HINA013 | 项目检查分析 | 分支≥6, 决策点≥3 |
| IT-06 | HINA025 | L1 分类+CALL 分析 | HINA="子程序调用", confidence≥90% |
| IT-07 | HINA101 | L1 分类+SQL 分析 | HINA="DB操作", confidence≥95% |
| IT-08 | run_validation.py 全执行 | 所有 HINA 程序 | 8/10 pass (已知限制2) |
---
## L3: 実 COBOL 验证
| # | 程序 | 验证项 | 期待 |
|:-:|:-----|:-------|:------|
| RT-01 | CRDVAL | COPYBOOK 展开+全 pipeline | 无错误 |
| RT-02 | CRDCALC | 同上 | 同上 |
| RT-03 | CRDRPT | 同上 | 同上 |
| RT-04 | GENDATA | 同上 | 同上 |
---
## L4: 回归测试
| # | 测试 | 命令 | 期待 |
|:-:|:-----|:------|:------|
| RE-01 | comparator 全测试 | `pytest tests/comparator/ -v` | 22 passed |
| RE-02 | report 全测试 | `pytest tests/report/ -v` | 3 passed |
| RE-03 | golden 全测试 | `pytest tests/test_golden.py -v` | 11 passed |
| RE-04 | e2e imports | `pytest tests/test_e2e.py -v` | 1 passed |
| RE-05 | 全单元 | `pytest tests/ --ignore=e2e/ --ignore=test_web_e2e.py --ignore=test_biz_e2e.py -v` | 42 passed |
---
## L5: 非功能测试
### 5.1 性能
测试文件: `tests/nonfunctional/test_performance.py`
| # | 测试名 | 场景 | 接受标准 |
|:-:|:-------|:------|:---------|
| NF-01 | COBOL 10万行解析时间 | extract_structure 含10万行输入 | ≤30秒完成 |
| NF-02 | 大文件上传 10MB 边界 | POST /verify 9.5MB 文件 | 202 响应, ≤10秒 |
| NF-03 | Worker 并发任务处理 | 5个任务同时 enqueue | 全部完成, ≤60秒 |
| NF-04 | 报告 HTML 生成:大数据集 | 1000字段结果渲染 | ≤5秒 |
| NF-05 | LLM 调用缓存加速 | 相同请求重复调用 | 第二次 ≤100ms |
### 5.2 并发安全
测试文件: `tests/nonfunctional/test_concurrency.py`
| # | 测试名 | 场景 | 期待 |
|:-:|:-------|:------|:------|
| NF-06 | 同时 POST 相同文件 | 2个并行 /verify 请求 | 不同 task_id |
| NF-07 | Worker 双实例 | 2个 Worker 同时 polling | 无任务重复处理 |
| NF-08 | Task JSON 并发读写 | 读的同时 Worker 在写入 | 无损坏/无异常 |
### 5.3 安全
测试文件: `tests/nonfunctional/test_security.py`
| # | 测试名 | 场景 | 期待 |
|:-:|:-------|:------|:------|
| NF-09 | 路径遍历: 上传文件名 | 文件名 `../../../etc/passwd` | 拒绝或 sanitize |
| NF-10 | 路径遍历: copybook 路径 | `--cobol-src ../../../etc/passwd` | BLOCKED |
| NF-11 | 文件类型校验 | 非 COBOL 文件扩展名 | 接受或合理处理 |
| NF-12 | API key 环境变量未设置 | LLM_API_KEY 为空 | Agent 使用 fallback 而非崩溃 |
| NF-13 | 错误信息泄露 | API 返回 stack trace | 不包含敏感路径 |
### 5.4 错误恢复与降级
测试文件: `tests/nonfunctional/test_resilience.py`
| # | 测试名 | 场景 | 期待 |
|:-:|:-------|:------|:------|
| NF-14 | Worker 中断→重启 | Worker 在 running 状态崩溃 | 重启后可重新处理 |
| NF-15 | 磁盘满模拟 | task JSON 写失败 | 错误日志, 不崩溃 |
| NF-16 | LLM API 不可用 | 网络隔离 | Agent 全部 fallback, pipeline 继续 |
| NF-17 | cobc 非 fatal warning | 编译通过但有 warning | pipeline 继续, warning 记录 |
---
## L6: E2E UI 测试 (Playwright)
测试文件: `tests/test_web_e2e.py`
| # | 测试名 | 场景 | 期待 |
|:-:|:-------|:------|:------|
| UI-01 | 上传页加载 | GET / | 标题含 verify, h1 可见 |
| UI-02 | 表单元素存在 | 检查 4个文件输入 + 下拉框 | 所有元素可见, 可交互 |
| UI-03 | 文件上传 | 选择4个文件 → 提交 | 202 响应, 跳转到 /status |
| UI-04 | 上传后轮询 | 等待 Worker 完成 | 状态从 queued→done |
| UI-05 | 结果页面: 摘要 | 验证完成 | 显示 matched/mismatched |
| UI-06 | 结果页面: 字段表 | 字段列表渲染 | 每列含 name/status/COBOL/Java |
| UI-07 | 无效文件上传 | 上传非 COBOL 文件 | 合理错误提示 |
---
## 边界测试 (补充 L0-L3)
| # | 场景 | 输入 | 期待 |
|:-:|:-----|:------|:------|
| EC-01 | 空 COBOL | `IDENTIFICATION DIVISION. PROGRAM-ID. X.` | 无错误 |
| EC-02 | 巨大程序 | 1万行级别 | 30秒内无超时 |
| EC-03 | 日文字符串 | PIC N 全角数据 | extract 正常 |
| EC-04 | REDEFINES | REDEFINES 使用 | 正常解析 |
| EC-05 | OCCURS DEPENDING | ODO 使用 | 正常解析 |
| EC-06 | 88-level 值 | 88-level 多个 | is_88=True 识别 |
| EC-07 | 仅注释 | 全行注释 | 无错误 |
| EC-08 | 非法 PIC | `PIC XXX` 非标准 | 正常或合理 fallback |
| EC-09 | 空文件路径 | `--cobol-src` 不存在的文件 | BLOCKED |
| EC-10 | Lark 语法错误 | 未预期的字符串 | 空结构, 错误日志 |
| EC-11 | COMP-3 无效 sign nibble | 0xF 异常 nibble | 取值或报错 | ← 新增 |
| EC-12 | REDEFINES 链 A→B→C | 3层 REDEFINES | 所有变体可访问 | ← 新增 |
| EC-13 | GOBACK 对比 STOP RUN | GOBACK 程序 | 正常退出 | ← 新增 |
| EC-14 | 无文件上传 | POST /verify 无任何文件 | 422 错误 | ← 新增 |
| EC-15 | mapping.yaml 格式错误 | 非法 YAML | 解析错误处理 | ← 新增 |---
## 程序类型覆盖 (33+2 COBOL 程序类型覆盖行)
| 程序类型 | 覆盖状态 | Phase | 测试文件 |
|:---------|:--------:|:-----:|:---------|
| simple_sequential | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| condition_heavy | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| evaluate_driven | ✅ | Phase 7+8 | `tests/parametrized/test_call_search.py` |
| data_file_centric | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| search_intensive | ✅ | Phase 8 | `tests/parametrized/test_call_search.py` |
| call_based | ✅ | Phase 8 | `tests/parametrized/test_call_search.py` |
| mixed_complex | ✅ | Phase 9 | `tests/parametrized/test_crosscutting.py` |
| 1:1 matching | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| 1:N matching | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| N:1 matching | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| KEY break (accumulate) | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| KEY break (aggregate) | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| KEY break (mark) | ✅ | Phase 7 | `tests/parametrized/test_matching.py` |
| Division 50/50 | ✅ | Phase 7 | `tests/parametrized/test_division.py` |
| Division 25/25/25/25 | ✅ | Phase 7 | `tests/parametrized/test_division.py` |
| Division 100 (all) | ✅ | Phase 7 | `tests/parametrized/test_division.py` |
| CSV → FB conversion | ✅ | Phase 7 | `tests/parametrized/test_csv_conversion.py` |
| CALL BY REFERENCE | ✅ | Phase 8 | `tests/parametrized/test_call_search.py` |
| CALL BY VALUE | ✅ | Phase 8 | `tests/parametrized/test_call_search.py` |
| CALL BY CONTENT | ✅ | Phase 8 | `tests/parametrized/test_call_search.py` |
| SEARCH ALL (binary) | ✅ | Phase 8 | `tests/parametrized/test_call_search.py` |
| SEARCH ALL (duplicate) | ✅ | Phase 8 | `tests/parametrized/test_call_search.py` |
| SORT (ascending) | ✅ | Phase 8 | `tests/parametrized/test_sort_merge.py` |
| SORT (descending) | ✅ | Phase 8 | `tests/parametrized/test_sort_merge.py` |
| SORT (multiple keys) | ✅ | Phase 8 | `tests/parametrized/test_sort_merge.py` |
| MERGE (2 files) | ✅ | Phase 8 | `tests/parametrized/test_sort_merge.py` |
| MERGE (uneven) | ✅ | Phase 8 | `tests/parametrized/test_sort_merge.py` |
| VL: ODO logic | ✅ | Phase 9 | `tests/parametrized/test_crosscutting.py` |
| LP: PERFORM VARYING | ✅ | Phase 9 | `tests/parametrized/test_crosscutting.py` |
| LP: PERFORM UNTIL | ✅ | Phase 9 | `tests/parametrized/test_crosscutting.py` |
| NP: COMP-3 precision | ✅ | Phase 9 | `tests/parametrized/test_crosscutting.py` |
| NP: ROUNDED clause | ✅ | Phase 9 | `tests/parametrized/test_crosscutting.py` |
| D: Leap year / Month end | ✅ | Phase 9 | `tests/parametrized/test_crosscutting.py` |
| 日文: 全角片假名 | ✅ | Phase 10 | `tests/parametrized/test_japanese.py` |
| 日文: 半角片假名 | ✅ | Phase 10 | `tests/parametrized/test_japanese.py` |
| 日文: SJIS 5C/7C 问题文字 | ✅ | Phase 10 | `tests/parametrized/test_japanese.py` |
| 日文: 和历日期 | ✅ | Phase 10 | `tests/parametrized/test_japanese.py` |
| 日文: Encoding round-trip | ✅ | Phase 10 | `tests/parametrized/test_japanese.py` |
**33+2 = 35 程序类型全覆盖**
---
## 类型别测试矩阵 (Phase 7-10 测试文件清单)
### Phase 7: 匹配/分割/CSV 转换 (~8 测试文件)
| 测试文件 | 测试内容 | 测试数 |
|:---------|:---------|:------:|
| `tests/parametrized/test_parametrized.py` | 8个公开函数的正常路径+边界 | ~50 |
| `tests/parametrized/test_matching.py` | 1:1/1:N/N:1 匹配 + KEY 中断 + gcov | ~20 |
| `tests/parametrized/test_division.py` | 50%/25%/100% 分割 + 余数处理 | ~15 |
| `tests/parametrized/test_csv_conversion.py` | CSV→FB 字段数/类型/引号 | ~13 |
### Phase 8: CALL / SEARCH ALL / SORT / MERGE (~2 测试文件)
| 测试文件 | 测试内容 | 测试数 |
|:---------|:---------|:------:|
| `tests/parametrized/test_call_search.py` | CALL 3种传递 + SEARCH ALL 查找 | ~22 |
| `tests/parametrized/test_sort_merge.py` | SORT 升/降序 + MERGE 均匀/不均 | ~18 |
### Phase 9: 横断功能测试 (~1 测试文件, ~20 tests)
| 测试文件 | 领域 | 测试数 |
|:---------|:-----|:------:|
| `tests/parametrized/test_crosscutting.py` | VL(ODO)+LP(PERFORM)+NP(COMP3/ROUNDED)+D(闰年/月末/和历) | ~20 |
### Phase 10: 日文测试 (~1 测试文件, ~20 tests)
| 测试文件 | 测试内容 | 测试数 |
|:---------|:---------|:------:|
| `tests/parametrized/test_japanese.py` | 全角/半角/SJIS 5C/7C/和历/编码回环 | ~20 |
---
## 横跨功能测试行 (Phase 9)
横断功能测试覆盖 COBOL 运行时四大核心领域:
| 领域 | 缩写 | 测试内容 | 测试数 |
|:-----|:----:|:---------|:------:|
| 可变长 / ODO | VL | OCCURS DEPENDING ON 长度/读取/边界 | 5 |
| 循环 / PERFORM | LP | PERFORM VARYING 升/降/步进 + UNTIL | 5 |
| 数值精度 | NP | COMP-3 BCD 解码 + ROUNDED 上下舍入 | 5 |
| 日期逻辑 | D | 闰年/月末/和历转换 | 5 |
---
## 日文测试行 (Phase 10)
日文测试覆盖 COBOL 日文处理的特殊场景:
| 测试分组 | 内容 | 测试数 |
|:---------|:-----|:------:|
| 查找表常量 | 全角平/片假名/半角/SJIS 问题文字/和历边界 | 4 |
| 全角文字生成 | PIC N 字段填充 + 长度 + 内容验证 | 3 |
| 半角片假名生成 | PIC X 字段填充 + 长度验证 | 2 |
| SJIS 问题文字 | 5C 问题 + 7C 问题文字 | 2 |
| 和历日期 | 标准格式 + 边界切换 + 默认参数 | 3 |
| 编码回环 | Shift-JIS ↔ UTF-8 回环 + 数据类型选择 | 4 |
| 数据类型选择 | PIC N/9/X 正确分类 | 2 |
---
## 覆盖率目标
```
Module Target Current
────────────────────────────────── ─────── ──────
cobol_testgen/* ≥ 85% ~60% (单元不足)
hina/classifier.py ≥ 90% 基本覆盖
hina/gate.py ≥ 95% 基本覆盖
hina/retry.py ≥ 90% 基本覆盖
hina/strategy.py ≥ 90% 基本覆盖
hina/hina_agent.py ≥ 85% ~60%
hina/gcov_collector.py ≥ 80% 0%
orchestrator.py ≥ 80% 0% ← 新增重点
web/api.py ≥ 85% 0% ← 新增重点
web/worker.py ≥ 75% 0% ← 新增重点
agents/* ≥ 80% 0%
config/* ≥ 85% 0%
runners/* ≥ 70% 0%
jcl/* ≥ 80% 0%
quality/* ≥ 70% 0%
storage/* ≥ 65% ~low
preprocessor.py ≥ 80% 0%
report/generator.py ≥ 75% 基本覆盖
comparator/* ≥ 90% 基本覆盖
data/* ≥ 95% 模块级断言
parametrized/* ≥ 95% 100% ← 新增 (Phase 7-8)
japanese_data.py ≥ 90% 100% ← 新增 (Phase 10)
coverage/* ≥ 80% 100% ← 新增
hina/confidence.py ≥ 90% 100% ← 新增
hina/rule_engine/* ≥ 85% 100% ← 新增
```
---
## 测试执行计划
### Phase A: 核心模块单元 (~15分)
```bash
# 核心: cobol_testgen / hina / agents / config
pytest tests/ -v -k "test_cobol or test_hina or test_agents or test_config" \
--ignore=tests/e2e/ --ignore=tests/test_web_e2e.py
```
### Phase B: 管道中枢 + Web (~10分)
```bash
# orchestrator, web API, Worker
pytest tests/ -v -k "test_orchestrator or test_web or test_worker"
```
### Phase C: 边界 + 非功能 (~15分)
```bash
# 边界值, 性能, 安全, 容错
pytest tests/ -v -k "test_edge or test_nonfunc or test_resilience"
```
### Phase D: runner + JCL + 其他模块 (~8分)
```bash
pytest tests/ -v -k "test_runner or test_jcl or test_quality or test_storage"
```
### Phase E: HINA 统合测试 (~2分)
```bash
python test-data/run_validation.py
```
### Phase F: 回归测试 (~1分)
```bash
python -m pytest tests/comparator/ tests/report/ tests/test_golden.py tests/test_e2e.py -v
```
### Phase G: 実 COBOL 测试 (~5分, WSL + GnuCOBOL)
```bash
# WSL 侧
python -m pytest tests/test_golden.py -v
```
### Phase H: E2E Playwright (~3分, 需启动 server)
```bash
# 终端1
python -m uvicorn web.api:app --host 127.0.0.1 --port 8000
# 终端2
python -m pytest tests/test_web_e2e.py -v
```
### Phase I: 类型别测试 Phase 7-10 (~2分)
```bash
# parametrized 全测试 (匹配/分割/CSV/CALL/SORT/横断/日文)
pytest tests/parametrized/ -v --ignore=tests/e2e/
```
### 一键全自动化
```bash
# 核心 + 边界 + 非功能 (不依赖外部环境)
pytest tests/ -v --ignore=e2e/ --ignore=test_web_e2e.py --ignore=test_biz_e2e.py
```
---
## 预期结果
| 测试维度 | 计划数 | 最低通过 | 通过率目标 |
|:---------|:-----:|:--------:|:---------:|
| L0 单元测试 | 280 | 270 | ≥96% |
| L1 类型测试 (Phase 7-8) | 80 | 75 | ≥93% |
| 横跨功能测试 (Phase 9) | 20 | 18 | ≥90% |
| 日文测试 (Phase 10) | 20 | 18 | ≥90% |
| L2 HINA 统合 | 8 | 6 | ≥75% |
| L3 実 COBOL | 4 | 4 | 100% |
| L4 回归 | 112 | 112 | 100% |
| L5 非功能 | 6 | 5 | ≥83% |
| L6 UI E2E | 7 | 7 | 100% |
| **总计** | **~518** | **~500** | **≥96%** |
**内訳:**
```
L0 单元测试: 280 (测试数 0.1~0.26 子模块单元测试)
L1 类型测试 (Ph7-8): 80 (matching/division/CSV/CALL/SORT/parametrized)
横跨功能测试 (Ph9): 20 (VL/LP/NP/D 四大领域)
日文测试 (Ph10): 20 (全角/半角/SJIS/和历/编码)
非功能测试: 6 (性能/并发/安全/容错)
已有回归: 112 (L2+L3+L4+L6 合计)
总计: ~518
```
---
## 已知限制
1. **Lark 文法**: `SD` / `ASCENDING KEY` 未対応, HINA 2个测试跳过
2. **Windows 编码**: `PYTHONIOENCODING=utf-8` 或 `python -X utf8` 必须, GBK 错误频繁
3. **Docker 不可用**: 当前环境无 Docker Desktop, Spark runner 不可测试
4. **外部依赖**: 実 COBOL 测试需要 WSL + GnuCOBOL + Java (GnuCOBOL 3.1.2.0, OpenJDK 17)
5. **LLM API 成本**: Agent 测试依赖 LLM 调用, 缓存命中可降低成本
6. **沙盒权限**: settings.json 需包含 `D:/cobol-java/**` 读写权限以便子 Agent 并行开发
hina/__init__.py
-25
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@@ -1,25 +0,0 @@
"""HINA 程序分类与质量门禁包
公开 API:
classify_program() — 完整类型判定管道（唯一外部入口）
内部模块（不直接导出，但保留模块级导入以维持向后兼容）:
gate_check() — 质量门禁判定
get_strategy() — 策略模板获取
supplement() — 策略补充
RetryHandler — 分层重试处理器
collect_gcov() — gcov 覆盖率采集
"""
from __future__ import annotations
from .pipeline.pipeline import classify_program
from .gate import check as gate_check
from .strategy import get_strategy, supplement, supplement_only
from .retry import RetryHandler
from .gcov_collector import collect_gcov
__all__ = [
# ═══ 唯一外部入口 ═══
"classify_program", # (source: str, llm?: object) -> dict
]
hina/classifier.py
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@@ -1,132 +0,0 @@
"""
HINA 程序分类器 — L1 关键字规则 + 确信度计算。
通过 COBOL 源码中的关键字匹配进行程序分类，支持多级确信度判定。
"""
from __future__ import annotations
from typing import Any
# ── L1 规则 ──────────────────────────────────────────────────────────────
# 格式: (分类名称, [关键字列表], 置信度阈值)
L1_RULES: list[tuple[str, list[str], float]] = [
("DB操作", ["EXEC SQL"], 0.95),
("子程序调用", ["CALL", "LINKAGE SECTION"], 0.90),
("IS INITIAL", ["IS INITIAL"], 0.99),
("SYSIN", ["SYSIN"], 0.90),
("编码转换", ["ALPHABETIC", "ASCII", "EBCDIC"], 0.85),
("online", ["DFHCOMMAREA", "MAP"], 0.95),
("SORT", ["SORT ON KEY"], 0.95),
("MERGE", ["MERGE ON KEY"], 0.95),
("编辑输出", ["WRITE AFTER", "WRITE BEFORE"], 0.80),
("文件编成", ["ORGANIZATION IS"], 0.99),
("替代索引", ["ALTERNATE RECORD KEY"], 0.99),
]
# ── 冲突解决规则 ─────────────────────────────────────────────────────────
# 当 L1 匹配到多个分类时的消歧策略:
# value = "file_count" → 取测试数更多的分类
# value = "has_accumulator" → 取包含累加器的分类
CONFLICT_RULES: dict[tuple[str, str], str] = {
("マッチング", "キーブレイク"): "file_count",
("編集処理", "項目チェック"): "file_count",
("キーブレイク", "項目チェック(重複)"): "has_accumulator",
}
# ── 关键字检测 ───────────────────────────────────────────────────────────
def detect_keyword(source: str) -> list[tuple[str, float, str]]:
"""在 COBOL 源码中搜索 L1_RULES 定义的关键字，返回匹配结果。
Args:
source: COBOL 程序源码文本。
Returns:
list[tuple[str, float, str]]:
每个元素为 (分类名称, 置信度, 匹配到的关键字原文)。
"""
results: list[tuple[str, float, str]] = []
source_upper = source.upper()
for category, keywords, confidence in L1_RULES:
for kw in keywords:
if kw in source_upper:
results.append((category, confidence, kw))
break # 同一分类只记录一次
return results
# ── 确信度计算 ───────────────────────────────────────────────────────────
def compute_confidence(
source: str,
structure: dict[str, Any] | None = None,
llm_result: dict[str, Any] | None = None,
) -> dict[str, Any]:
"""计算程序分类的确信度。
优先级:
1. L1 关键字命中，且最高置信度 >= 0.90 → 直接返回 L1 结果。
2. LLM 结果存在 → 使用 LLM 的分类结果。
3. 否则 → 返回 unknown。
Args:
source: COBOL 程序源码文本。
structure: 可选的程序结构信息（暂未使用，保留扩展）。
llm_result: 可选的 LLM 分类结果。
预期格式: {"category": str, "confidence": float, ...}
Returns:
dict:
- "category": str — 分类名称或 "unknown"
- "confidence": float — 确信度 (0.0 ~ 1.0)
- "source": str — 结果来源 ("l1" / "llm" / "unknown")
- "matches": list — 匹配到的关键字详情
"""
# ── 1. L1 关键字检测 ──
matches = detect_keyword(source)
# 找出最高置信度的 L1 匹配
if matches:
best = max(matches, key=lambda m: m[1]) # (category, confidence, keyword)
category, confidence, _ = best
if confidence >= 0.90:
return {
"category": category,
"confidence": confidence,
"method": "keyword",
"source": "l1",
"features": [best[2]],
"required_tests": [],
"strategy_params": {"special_boundaries": [], "coverage_requirements": {"branch": 0.95, "paragraph": 1.0}},
"matches": matches,
}
# ── 2. LLM 结果 ──
if llm_result is not None:
llm_category = llm_result.get("category", "unknown")
llm_confidence = llm_result.get("confidence", 0.0)
return {
"category": llm_category,
"confidence": llm_confidence,
"method": "hybrid",
"source": "llm",
"features": [],
"required_tests": [],
"strategy_params": {"special_boundaries": [], "coverage_requirements": {"branch": 0.95, "paragraph": 1.0}},
"matches": matches,
}
# ── 3. 未知 ──
return {
"category": "unknown",
"confidence": 0.0,
"method": "none",
"source": "unknown",
"features": [],
"required_tests": [],
"strategy_params": {"special_boundaries": [], "coverage_requirements": {"branch": 0.95, "paragraph": 1.0}},
"matches": [],
}
hina/confidence.py
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"""
确信度 4 因子计算。
公式: confidence = base × context_factor × consistency_factor × structure_factor
判定:
>= 0.90 auto — 自动通过
0.70-0.89 review — 需要人工审核
0.50-0.69 manual — 需要人工介入
< 0.50 impossible — 无法判定
"""
from __future__ import annotations
from typing import Any
def compute_confidence_v2(
keyword_result: dict[str, Any],
structure_features: dict[str, Any],
contradictions: list[dict[str, Any]] | None = None,
resolution: dict[str, Any] | None = None,
) -> dict[str, Any]:
"""4 因子确信度计算。
Args:
keyword_result: L1 关键字判定结果，
例如 {"category": "DB操作", "base_confidence": 0.95, "match_count": 3}
structure_features: 结构特征分析结果，
例如 {"structure_match_score": 5, "total_paragraphs": 10}
contradictions: 矛盾列表，每条包含 {"type": str, "resolved": bool, ...}
resolution: 矛盾解决方案，
例如 {"resolved_count": 0, "total_count": 0}
Returns:
dict: {
"confidence": float, # 综合确信度 (0.0 ~ 1.0)
"base": float, # 基础确信度
"context_factor": float, # 上下文因子
"consistency_factor": float,# 一致性因子
"structure_factor": float, # 结构一致性因子
"judgment": str, # 判定结果 (auto/review/manual/impossible)
"needs_review": bool, # 是否需要人工审核
}
"""
# ── 1. 基础确信度 ──
base = keyword_result.get("base_confidence", 0.7)
# ── 2. 上下文因子（关键字匹配数）──
match_count = keyword_result.get("match_count", 0)
if match_count >= 3:
context_factor = 1.0
elif match_count == 2:
context_factor = 0.95
elif match_count == 1:
context_factor = 0.90
else:
context_factor = 0.50
# ── 3. 一致性因子（矛盾检测）──
contradictions = contradictions or []
unresolved_count = sum(1 for c in contradictions if not c.get("resolved", False))
total_contradictions = len(contradictions)
if total_contradictions == 0:
consistency_factor = 1.0
elif unresolved_count == 0:
# 有矛盾但全部已解决
consistency_factor = 0.90
elif total_contradictions >= 3:
consistency_factor = 0.50
else:
# 有未解决的矛盾，但少于 3 个
consistency_factor = 0.80
# ── 4. 结构一致性因子 ──
structure_score = structure_features.get("structure_match_score", 0)
if structure_score == 5:
structure_factor = 1.0
elif structure_score >= 3:
structure_factor = 0.7
elif structure_score >= 1:
structure_factor = 0.5
else:
structure_factor = 0.3
# ── 计算综合确信度 ──
confidence = round(base * context_factor * consistency_factor * structure_factor, 4)
# ── 判定 ──
if confidence >= 0.90:
judgment = "auto"
needs_review = False
elif confidence >= 0.70:
judgment = "review"
needs_review = True
elif confidence >= 0.50:
judgment = "manual"
needs_review = True
else:
judgment = "impossible"
needs_review = True
return {
"confidence": confidence,
"base": base,
"context_factor": context_factor,
"consistency_factor": consistency_factor,
"structure_factor": structure_factor,
"judgment": judgment,
"needs_review": needs_review,
}
hina/gate.py
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"""
质量门禁 — 执行前检查测试数据是否满足覆盖率和边界要求。
Phase 1 可用: 决策点覆盖、段落覆盖
Phase 2 启用: HINA 必须项、字段覆盖
"""
from __future__ import annotations
from typing import Any
def check(
complete_tests: list,
hina_result: dict,
coverage: dict,
decision_threshold: float = 0.90,
paragraph_threshold: float = 1.0,
) -> dict:
"""质量门禁检查。
Args:
complete_tests: 完整的测试数据集
hina_result: HINA 分类结果
coverage: check_coverage() 输出的覆盖率数据
decision_threshold: 决策点覆盖率阈值
paragraph_threshold: 段落覆盖率阈值
Returns:
dict with: passed, score, issues
"""
issues = {}
branch_rate = coverage.get("branch_rate", 0.0)
if branch_rate < decision_threshold:
issues["decision_gaps"] = coverage.get("uncovered_decision_ids", [])
paragraph_rate = coverage.get("paragraph_rate", 0.0)
if paragraph_rate < paragraph_threshold:
issues.setdefault("paragraph_gaps", []).append(
f"段落覆盖率不足: {paragraph_rate:.0%}"
)
if not complete_tests:
issues["no_data"] = True
passed = len(issues) == 0
score = _compute_score(coverage, hina_result)
return {"passed": passed, "score": score, "issues": issues}
def _compute_score(coverage: dict, hina_result: dict) -> float:
"""质量评分公式（COBOL 版）。
评分 = 覆盖质量 × 0.6 + 边界质量 × 0.4
覆盖质量 = 段落覆盖率 × 0.5 + 分支覆盖率 × 0.5
边界质量 = HINA 必须项覆盖率（Phase 2 后启用，默认 1.0）
"""
paragraph_rate = coverage.get("paragraph_rate", 0.0)
branch_rate = coverage.get("branch_rate", 0.0)
coverage_quality = paragraph_rate * 0.5 + branch_rate * 0.5
boundary_quality = 1.0
return round(coverage_quality * 0.6 + boundary_quality * 0.4, 2)
def compute_quality_score(
static_coverage: dict[str, Any],
gcov_coverage: dict[str, Any] | None = None,
confidence: float = 0.5,
) -> float:
"""双模式质量评分。
模式 1 — gcov 未启用 (gcov_coverage is None):
score = branch_rate × 0.5 + paragraph_rate × 0.5 + confidence × 0.4
其中 confidence 作为加分项（最高 +0.4）
模式 2 — gcov 启用:
score = static_cov × 0.3 + gcov_cov × 0.4 + confidence × 0.3
其中 static_cov = branch_rate × 0.5 + paragraph_rate × 0.5
Args:
static_coverage: 静态覆盖率数据
{"branch_rate": float, "paragraph_rate": float, ...}
gcov_coverage: gcov 动态覆盖率数据，None 表示未启用
{"gcov_cov": float, ...} 或 None
confidence: 确信度 (0.0 ~ 1.0)
Returns:
float: 质量评分 (0.0 ~ 1.0)
"""
branch_rate = static_coverage.get("branch_rate", 0.0)
paragraph_rate = static_coverage.get("paragraph_rate", 0.0)
static_cov = branch_rate * 0.5 + paragraph_rate * 0.5
if gcov_coverage is not None:
# 模式 2: gcov 启用
gcov_cov = gcov_coverage.get("gcov_cov", 0.0)
score = static_cov * 0.3 + gcov_cov * 0.4 + confidence * 0.3
else:
# 模式 1: gcov 未启用 — confidence 作为加分
score = branch_rate * 0.5 + paragraph_rate * 0.5 + confidence * 0.4
return round(min(score, 1.0), 4)
hina/gcov_collector.py
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@@ -1,58 +0,0 @@
import subprocess
import logging
from pathlib import Path
logger = logging.getLogger(__name__)
def collect_gcov(cobol_src: Path, work_dir: Path) -> dict:
try:
cd = str(work_dir)
gcda_files = list(Path(cd).glob("*.gcda"))
if not gcda_files:
logger.warning("[gcov] 未找到 .gcda 文件，可能未启用插桩编译")
return {"available": False, "reason": "no_gcda_files"}
result = subprocess.run(
["gcov", cobol_src.name],
capture_output=True, text=True, timeout=30,
cwd=cd,
)
if result.returncode != 0:
logger.warning(f"[gcov] gcov 执行失败: {result.stderr[:200]}")
return {"available": False, "reason": "gcov_failed"}
gcov_file = Path(cd) / f"{cobol_src.stem}.cbl.gcov"
if not gcov_file.exists():
gcov_file = Path(cd) / f"{cobol_src.stem}.gcov"
if not gcov_file.exists():
logger.warning("[gcov] .gcov 文件未生成")
return {"available": False, "reason": "no_gcov_output"}
total_lines = 0
executed_lines = 0
with open(str(gcov_file), encoding="utf-8", errors="replace") as f:
for line in f:
stripped = line.strip()
if stripped and not stripped.startswith("-"):
total_lines += 1
if not stripped.startswith("#"):
executed_lines += 1
line_rate = executed_lines / max(total_lines, 1)
return {
"available": True,
"line_rate": round(line_rate, 4),
"total_lines": total_lines,
"executed_lines": executed_lines,
}
except FileNotFoundError:
logger.warning("[gcov] gcov 命令未找到，降级为仅静态分析")
return {"available": False, "reason": "gcov_not_installed"}
except Exception as e:
logger.warning(f"[gcov] 采集异常: {e}")
return {"available": False, "reason": str(e)[:100]}
hina/hina_agent.py
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"""
HINA 混淆组判定 — 基于 LLM 的 COBOL 程序结构分类。
根据 extract_structure() 输出的结构特征，调用 LLM 将程序归类到
混淆组（confusion group），并返回分类结果和策略参数。
"""
import json
import logging
logger = logging.getLogger(__name__)
CONFUSION_PROMPT = """你是一个 COBOL 程序混淆组分类专家。请根据以下程序结构特征，将其归类到合适的混淆组中。
程序结构特征：
- 段落数: {paragraph_count}
- 决策点总数: {decision_count}
- IF 语句数: {if_count}
- EVALUATE 语句数: {evaluate_count}
- 关联文件数: {file_count}
- OPEN 方向: {open_directions}
- SEARCH ALL: {has_search_all}
- CALL 语句: {has_call}
- KEY BREAK 关键词: {has_break}
- 总分支数: {total_branches}
混淆组定义：
1. simple_sequential — 极少决策点（<=2），无 EVALUATE/SEARCH ALL/CALL，直接顺序执行
2. condition_heavy — IF 语句占比高（>60% 的决策点），嵌套深，逻辑复杂
3. evaluate_driven — EVALUATE 主导，多分支选择结构
4. data_file_centric — 文件操作密集（>=2 文件），OPEN 方向多样（I-O/OUTPUT/INPUT）
5. search_intensive — 包含 SEARCH ALL，表/数组查找为主
6. call_based — 包含 CALL 语句，模块间调用为主
7. mixed_complex — 同时具备多种复杂特征（决策点多且文件多且含 CALL/SEARCH 等）
请按 JSON 格式输出分类结果，不要包含其他文字：
```json
{{
"category": "<混淆组类别>",
"subtype": "<子类别，如 nested_if / flat_evaluate / multi_file 等>",
"confidence": <0~1 置信度>,
"features": {{
"paragraph_count": {paragraph_count},
"decision_count": {decision_count},
"if_count": {if_count},
"evaluate_count": {evaluate_count},
"file_count": {file_count},
"has_search_all": {has_search_all},
"has_call": {has_call},
"has_break": {has_break},
"total_branches": {total_branches}
}},
"required_tests": <建议测试用例数，整数>,
"strategy_params": {{
"max_nesting_depth": <最大嵌套深度建议>,
"coverage_target": "branch" 或 "path",
"file_isolation": true 或 false,
"supplement_strategy": "incremental" 或 "full" 或 "skip"
}}
}}
```"""
def classify_with_llm(structure: dict, llm) -> dict:
"""调用 LLM 对程序结构进行混淆组分类。
根据 extract_structure() 返回的结构字典，构造 CONFUSION_PROMPT
并调用 LLM 进行分类。结果包含 category、subtype、confidence、
features、required_tests、strategy_params。
Args:
structure: extract_structure() 返回的字典，包含 paragraphs、
decision_points、file_count、open_directions、
has_search_all、has_evaluate、has_call、has_break、
total_branches、total_paragraphs 等字段。
llm: LLMClient 实例，call 方法签名为
llm.call([{"role":"system","content":"..."},
{"role":"user","content":prompt}]) -> str
Returns:
dict: {
"category": str,
"subtype": str,
"confidence": float,
"features": dict,
"required_tests": int,
"strategy_params": dict
}
"""
decision_points = structure.get("decision_points", [])
if_count = sum(1 for dp in decision_points if dp.get("kind") == "IF")
evaluate_count = sum(1 for dp in decision_points if dp.get("kind") == "EVALUATE")
paragraph_count = structure.get("total_paragraphs", len(structure.get("paragraphs", [])))
open_dirs = structure.get("open_directions", {})
has_search_all = str(structure.get("has_search_all", False)).lower()
has_call = str(structure.get("has_call", False)).lower()
has_break = str(structure.get("has_break", False)).lower()
prompt = CONFUSION_PROMPT.format(
paragraph_count=paragraph_count,
decision_count=len(decision_points),
if_count=if_count,
evaluate_count=evaluate_count,
file_count=structure.get("file_count", 0),
open_directions=json.dumps(open_dirs, ensure_ascii=False),
has_search_all=has_search_all,
has_call=has_call,
has_break=has_break,
total_branches=structure.get("total_branches", 0),
)
messages = [
{"role": "system", "content": "你是一个 COBOL 程序混淆组分类专家。只输出 JSON，不要输出解释。"},
{"role": "user", "content": prompt},
]
try:
raw = llm.call(messages)
result = _parse_llm_response(raw)
logger.info(
"HINA classification: %s/%s (confidence=%.2f, tests=%s)",
result.get("category", "?"),
result.get("subtype", "?"),
result.get("confidence", 0.0),
result.get("required_tests", "?"),
)
return result
except Exception as e:
logger.warning("HINA LLM classification failed: %s", e)
return _fallback_classification(structure)
def _parse_llm_response(raw: str) -> dict:
"""从 LLM 响应中提取 JSON 并解析。
处理 JSON 可能被 ```json ... ``` 包裹的情况。
"""
text = raw.strip()
# 尝试提取 ```json ... ``` 代码块
if "```json" in text:
start = text.index("```json") + 7
end = text.index("```", start) if "```" in text[start:] else len(text)
text = text[start:end].strip()
elif "```" in text:
# 尝试 ``` ... ``` （无 json 标注）
start = text.index("```") + 3
end = text.index("```", start) if "```" in text[start:] else len(text)
text = text[start:end].strip()
try:
parsed = json.loads(text)
return _validate_result(parsed)
except (json.JSONDecodeError, ValueError):
return _validate_result({})
def _validate_result(parsed: dict) -> dict:
"""验证并规范化 LLM 返回的分类结果。"""
defaults = {
"category": "unknown",
"subtype": "",
"confidence": 0.0,
"features": {},
"required_tests": 1,
"strategy_params": {
"max_nesting_depth": 1,
"coverage_target": "branch",
"file_isolation": False,
"supplement_strategy": "full",
},
}
result = {}
for key, default_value in defaults.items():
value = parsed.get(key, default_value)
if key == "confidence":
try:
value = float(value)
value = max(0.0, min(1.0, value))
except (ValueError, TypeError):
value = 0.0
elif key == "required_tests":
try:
value = int(value)
value = max(1, value)
except (ValueError, TypeError):
value = 1
result[key] = value
return result
def _fallback_classification(structure: dict) -> dict:
"""当 LLM 调用失败时，基于规则的兜底分类。"""
decision_points = structure.get("decision_points", [])
if_count = sum(1 for dp in decision_points if dp.get("kind") == "IF")
evaluate_count = sum(1 for dp in decision_points if dp.get("kind") == "EVALUATE")
total_decisions = len(decision_points)
file_count = structure.get("file_count", 0)
has_search_all = structure.get("has_search_all", False)
has_call = structure.get("has_call", False)
has_break = structure.get("has_break", False)
# 规则优先级：从高到低
if total_decisions == 0:
category, subtype = "simple_sequential", "no_branch"
required_tests = 1
strategy = {"max_nesting_depth": 0, "coverage_target": "branch",
"file_isolation": False, "supplement_strategy": "skip"}
elif has_search_all:
category, subtype = "search_intensive", "table_lookup"
required_tests = max(total_decisions, 3)
strategy = {"max_nesting_depth": 3, "coverage_target": "path",
"file_isolation": True, "supplement_strategy": "incremental"}
elif has_call:
category, subtype = "call_based", "external_call"
required_tests = max(total_decisions, 3)
strategy = {"max_nesting_depth": 2, "coverage_target": "branch",
"file_isolation": False, "supplement_strategy": "full"}
elif evaluate_count > if_count and evaluate_count >= 2:
category, subtype = "evaluate_driven", "multi_way"
required_tests = total_decisions + 1
strategy = {"max_nesting_depth": evaluate_count, "coverage_target": "path",
"file_isolation": False, "supplement_strategy": "full"}
elif file_count >= 2:
category, subtype = "data_file_centric", "multi_file"
required_tests = max(total_decisions, file_count * 2)
strategy = {"max_nesting_depth": 2, "coverage_target": "branch",
"file_isolation": True, "supplement_strategy": "incremental"}
elif if_count >= 5 or total_decisions >= 8:
category, subtype = "condition_heavy", "nested_if"
required_tests = total_decisions + 2
strategy = {"max_nesting_depth": 4, "coverage_target": "path",
"file_isolation": False, "supplement_strategy": "incremental"}
elif if_count >= 2:
category, subtype = "condition_heavy", "simple_if"
required_tests = total_decisions + 1
strategy = {"max_nesting_depth": 2, "coverage_target": "branch",
"file_isolation": False, "supplement_strategy": "incremental"}
else:
category, subtype = "simple_sequential", "minimal"
required_tests = 1
strategy = {"max_nesting_depth": 0, "coverage_target": "branch",
"file_isolation": False, "supplement_strategy": "skip"}
# 检查是否应升级为 mixed_complex
complexity_flags = sum([
has_search_all,
has_call,
has_break,
file_count >= 2,
if_count >= 5,
evaluate_count >= 3,
])
if complexity_flags >= 3:
category, subtype = "mixed_complex", f"{subtype}_plus"
required_tests = max(required_tests, 10)
strategy["max_nesting_depth"] = max(strategy.get("max_nesting_depth", 2), 5)
strategy["coverage_target"] = "path"
strategy["supplement_strategy"] = "full"
return {
"category": category,
"subtype": subtype,
"confidence": 0.6,
"features": {
"paragraph_count": structure.get("total_paragraphs", len(structure.get("paragraphs", []))),
"decision_count": total_decisions,
"if_count": if_count,
"evaluate_count": evaluate_count,
"file_count": file_count,
"has_search_all": has_search_all,
"has_call": has_call,
"has_break": has_break,
"total_branches": structure.get("total_branches", 0),
},
"required_tests": required_tests,
"strategy_params": strategy,
}
hina/pipeline/__init__.py
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"""HINA 完整类型判定管道。"""
hina/pipeline/pipeline.py
-432
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@@ -1,432 +0,0 @@
"""
完整程序类型判定管道 — classify_program()
流程:
1. 并行: detect_keyword() + extract_structure()
2. keyword confidence >= 90% -> 直接输出
3. keyword 50-89% -> 规则引擎 + 确信度计算 + 矛盾回溯
4. keyword < 50% -> LLM 辅助 + 规则引擎验证
5. 输出最终 JSON
"""
from __future__ import annotations
import logging
from concurrent.futures import ThreadPoolExecutor, as_completed
from typing import Any
from hina.classifier import detect_keyword
from hina.confidence import compute_confidence_v2
from hina.rule_engine.confusion_groups import resolve_confusion_pair
from hina.rule_engine.contradiction import (
CONTRADICTION_PAIRS,
detect_contradictions,
resolve_contradiction,
)
from cobol_testgen import extract_structure
logger = logging.getLogger(__name__)
# 所有可尝试的混淆对名称
_PAIR_NAMES = [
"matching_vs_keybreak",
"dedup_vs_nodedup",
"validation_vs_keybreak",
"csv_merge_vs_split",
"simple_vs_two_stage",
"pure_vs_mixed",
"division_50_25_100",
"mn_output_mode",
]
# ── 内部工具 ──────────────────────────────────────────────────────────────────
def _get_best_keyword_match(matches: list) -> dict | None:
"""从 L1 关键字匹配结果中找出最佳匹配。
Args:
matches: detect_keyword() 返回的 list[tuple[str, float, str]]
Returns:
dict | None: {"category", "confidence", "keyword", "all_matches"}
"""
if not matches:
return None
best = max(matches, key=lambda m: m[1]) # (category, confidence, keyword)
return {
"category": best[0],
"confidence": best[1],
"keyword": best[2],
"all_matches": matches,
}
def _compute_structure_match_score(structure: dict) -> int:
"""计算结构匹配度评分 (0-5)，供 compute_confidence_v2 使用。"""
return min(
5,
bool(structure.get("total_paragraphs", 0)) # 有段落
+ bool(structure.get("file_count", 0)) # 有文件
+ bool(len(structure.get("decision_points", []))) # 有决策点
+ bool(structure.get("if_types", {}).get("total", 0)) # 有 IF
+ bool(structure.get("branch_tree_obj") is not None), # 有分支树
)
def _build_structure_summary(structure: dict) -> dict:
"""从完整结构中提取调试摘要。"""
return {
"paragraph_count": structure.get("total_paragraphs", 0),
"file_count": structure.get("file_count", 0),
"decision_count": len(structure.get("decision_points", [])),
"has_call": structure.get("has_call", False),
"has_divide": structure.get("has_divide", False),
}
def _build_keyword_result_for_v2(keyword_info: dict | None) -> dict:
"""构建 compute_confidence_v2 所需的 keyword_result。"""
if keyword_info:
return {
"base_confidence": keyword_info["confidence"],
"match_count": len(keyword_info["all_matches"]),
}
return {"base_confidence": 0.0, "match_count": 0}
def _build_structure_features(structure: dict) -> dict:
"""构建 compute_confidence_v2 所需的 structure_features。"""
return {
"structure_match_score": _compute_structure_match_score(structure),
"total_paragraphs": structure.get("total_paragraphs", 0),
}
# ── 分路径逻辑 ────────────────────────────────────────────────────────────────
def _path_keyword_direct(
keyword_info: dict,
structure: dict,
) -> dict:
"""路径 A: keyword confidence >= 90%, 直接输出。
仍会计算 v2 确信度用于最终 validation，但结果来源标记为 "keyword"。
"""
keyword_result_v2 = _build_keyword_result_for_v2(keyword_info)
structure_features = _build_structure_features(structure)
v2_conf = compute_confidence_v2(
keyword_result=keyword_result_v2,
structure_features=structure_features,
contradictions=[],
resolution={"resolved_count": 0, "total_count": 0},
)
return {
"category": keyword_info["category"],
"confidence": v2_conf["confidence"],
"needs_review": v2_conf["needs_review"],
"method": "keyword",
"source": "l1",
"judgment": v2_conf["judgment"],
"matches": keyword_info["all_matches"],
"contradictions": [],
"v2_confidence": v2_conf,
"structure": _build_structure_summary(structure),
}
def _path_rule_engine(
keyword_info: dict | None,
structure: dict,
) -> dict:
"""路径 B: keyword 50-89%, 规则引擎 + 确信度计算 + 矛盾回溯。
流程:
1. 用 structure 特征构建 features dict
2. 遍历所有混淆组解析器, 收集 resolved_types
3. 检测矛盾并解决
4. 确定最终分类
5. 计算 4 因子确信度
"""
# 1. 结构特征直接作为 features
features = dict(structure)
# 2. 运行所有混淆组解析器
resolved_types: dict[str, str] = {}
resolved_confidences: dict[str, float] = {}
for pair_name in _PAIR_NAMES:
try:
result = resolve_confusion_pair(features, pair_name)
if result["resolved_type"] != "unknown" and result["confidence"] > 0:
resolved_types[pair_name] = result["resolved_type"]
resolved_confidences[pair_name] = result["confidence"]
except Exception as e:
logger.debug("[pipeline] 混淆对 %s 解析异常: %s", pair_name, e)
features["resolved_types"] = resolved_types
# 3. 矛盾检测与解决
contradictions = detect_contradictions(features)
resolution_map: dict[str, Any] = {
"resolved_count": 0,
"total_count": len(contradictions),
}
for c in contradictions:
try:
winner = resolve_contradiction(features, c)
if winner:
resolution_map[c.get("name", "unknown")] = winner
resolution_map["resolved_count"] += 1
except Exception as e:
logger.debug("[pipeline] 矛盾解决异常: %s", e)
# 4. 确定最终分类与基础置信度
final_category = "unknown"
final_base_confidence = 0.0
# 优先采纳 keyword 判定
if keyword_info:
final_category = keyword_info["category"]
final_base_confidence = keyword_info["confidence"]
# 如果规则引擎有更高置信度的结果, 则采纳
# 使用第一轮缓存的结果（M1: 消除冗余重复调用）
best_resolved_type = None
best_resolved_conf = 0.0
for pair_name, rtype in resolved_types.items():
cached_conf = resolved_confidences.get(pair_name, 0.0)
if cached_conf > best_resolved_conf:
best_resolved_conf = cached_conf
best_resolved_type = rtype
if best_resolved_type and best_resolved_conf > final_base_confidence:
final_category = best_resolved_type
final_base_confidence = best_resolved_conf
# 5. 计算 4 因子确信度
keyword_result_v2 = _build_keyword_result_for_v2(keyword_info)
keyword_result_v2["base_confidence"] = final_base_confidence
structure_features = _build_structure_features(structure)
v2_confidence = compute_confidence_v2(
keyword_result=keyword_result_v2,
structure_features=structure_features,
contradictions=contradictions,
resolution=resolution_map,
)
# 6. 组装结果
return {
"category": final_category,
"confidence": v2_confidence["confidence"],
"needs_review": v2_confidence["needs_review"],
"method": "rule_engine",
"source": "pipeline",
"judgment": v2_confidence["judgment"],
"matches": keyword_info["all_matches"] if keyword_info else [],
"contradictions": contradictions,
"contradiction_resolution": resolution_map,
"resolved_types": resolved_types,
"v2_confidence": v2_confidence,
"structure": _build_structure_summary(structure),
}
def _path_llm_assisted(
keyword_info: dict | None,
structure: dict,
llm: Any,
) -> dict:
"""路径 C: keyword < 50%, LLM 辅助 + 规则引擎验证。
流程:
1. 调用 classify_with_llm 获取 LLM 分类
2. 规则引擎验证 LLM 结果
3. 矛盾检测
4. 确信度计算
"""
from hina.hina_agent import classify_with_llm
# 1. LLM 分类
llm_result = classify_with_llm(structure, llm)
llm_category = llm_result.get("category", "unknown")
llm_confidence = llm_result.get("confidence", 0.5)
# 2. 规则引擎验证 LLM 分类
features = dict(structure)
validated_category = llm_category
validated_confidence = llm_confidence
for pair_name in _PAIR_NAMES:
try:
pair_result = resolve_confusion_pair(features, pair_name)
if (pair_result["resolved_type"] != "unknown"
and pair_result["confidence"] > validated_confidence):
validated_category = pair_result["resolved_type"]
validated_confidence = pair_result["confidence"]
except Exception:
continue
# 3. 矛盾检测与解决 (M2: 消除硬编码 resolved_count=0)
resolved_types: dict[str, str] = {}
for pair_name in _PAIR_NAMES:
try:
rr = resolve_confusion_pair(features, pair_name)
if rr["resolved_type"] != "unknown":
resolved_types[pair_name] = rr["resolved_type"]
except Exception:
continue
features["resolved_types"] = resolved_types
contradictions = detect_contradictions(features)
resolution_map: dict[str, Any] = {
"resolved_count": 0,
"total_count": len(contradictions),
}
for c in contradictions:
try:
winner = resolve_contradiction(features, c)
if winner:
resolution_map[c.get("name", "unknown")] = winner
resolution_map["resolved_count"] += 1
except Exception as e:
logger.debug("[pipeline] Path C 矛盾解决异常: %s", e)
# 4. 确信度计算
keyword_result_v2 = _build_keyword_result_for_v2(keyword_info)
keyword_result_v2["base_confidence"] = validated_confidence
structure_features = _build_structure_features(structure)
v2_confidence = compute_confidence_v2(
keyword_result=keyword_result_v2,
structure_features=structure_features,
contradictions=contradictions,
resolution=resolution_map,
)
return {
"category": validated_category,
"confidence": v2_confidence["confidence"],
"needs_review": v2_confidence["needs_review"],
"method": "llm",
"source": "pipeline",
"judgment": v2_confidence["judgment"],
"matches": keyword_info["all_matches"] if keyword_info else [],
"contradictions": contradictions,
"llm_raw": llm_result,
"v2_confidence": v2_confidence,
"structure": _build_structure_summary(structure),
}
# ── 主入口 ────────────────────────────────────────────────────────────────────
def classify_program(cobol_source: str, llm: Any = None) -> dict:
"""完整程序类型判定管道。
流程:
1. 并行: detect_keyword() + extract_structure()
2. keyword confidence >= 90% -> 直接输出
3. keyword 50-89% -> 规则引擎 + 确信度计算 + 矛盾回溯
4. keyword < 50% -> LLM 辅助 + 规则引擎验证
5. 输出最终 JSON
Args:
cobol_source: COBOL 程序源码文本。
llm: 可选的 LLM 客户端实例。
在 keyword confidence < 50% 路径中用于 LLM 辅助分类。
若为 None 且 keyword < 50%, 则使用规则引擎兜底。
Returns:
dict: {
"category": str, # 程序分类名称
"confidence": float, # 综合确信度 (0.0 ~ 1.0)
"needs_review": bool, # 是否需要人工审核
"method": str, # "keyword" | "rule_engine" | "llm"
"source": str, # 结果来源: "l1" / "pipeline"
"judgment": str, # auto / review / manual / impossible
"matches": list, # L1 关键字匹配详情
"contradictions": list, # 矛盾列表
"v2_confidence": dict, # 4 因子确信度详情
"structure": dict, # 结构特征摘要（调试用）
}
Raises:
ValueError: 如果 cobol_source 为空或无效。
"""
if not cobol_source or not cobol_source.strip():
return {
"category": "unknown",
"confidence": 0.0,
"needs_review": True,
"method": "none",
"source": "error",
"judgment": "impossible",
"matches": [],
"contradictions": [],
"v2_confidence": {},
"structure": {},
}
# ── 第 1 步: 并行执行 keyword 检测和结构提取 ──
keyword_matches: list = []
structure: dict = {}
with ThreadPoolExecutor(max_workers=2) as executor:
future_keyword = executor.submit(detect_keyword, cobol_source)
future_structure = executor.submit(extract_structure, cobol_source)
for future in as_completed([future_keyword, future_structure]):
if future == future_keyword:
try:
keyword_matches = future.result()
except Exception as e:
logger.warning("[pipeline] detect_keyword 失败: %s", e)
elif future == future_structure:
try:
structure = future.result()
except Exception as e:
logger.warning("[pipeline] extract_structure 失败: %s", e)
# ── 第 2 步: 分析关键字结果, 确定路径 ──
keyword_info = _get_best_keyword_match(keyword_matches)
max_keyword_confidence = keyword_info["confidence"] if keyword_info else 0.0
logger.info(
"[pipeline] keyword matches=%d, max_confidence=%.2f, paragraphs=%d, files=%d",
len(keyword_matches),
max_keyword_confidence,
structure.get("total_paragraphs", 0),
structure.get("file_count", 0),
)
# ── 第 3 步: 根据确信度分路径 ──
# 路径 A: keyword >= 90% -> 直接输出
if max_keyword_confidence >= 0.90:
logger.info("[pipeline] 路径 A: keyword 高确信度 (%.2f)", max_keyword_confidence)
return _path_keyword_direct(keyword_info, structure)
# 路径 B: keyword 50-89% -> 规则引擎
if max_keyword_confidence >= 0.50:
logger.info("[pipeline] 路径 B: keyword 中确信度 (%.2f) -> 规则引擎", max_keyword_confidence)
return _path_rule_engine(keyword_info, structure)
# 路径 C: keyword < 50% -> LLM 辅助
if llm is not None:
logger.info("[pipeline] 路径 C: keyword 低确信度 (%.2f) -> LLM 辅助", max_keyword_confidence)
return _path_llm_assisted(keyword_info, structure, llm)
# LLM 不可用: 使用规则引擎兜底
logger.info("[pipeline] 路径 C(fallback): keyword 低确信度 (%.2f) -> 规则引擎兜底", max_keyword_confidence)
result = _path_rule_engine(keyword_info, structure)
result["method"] = "rule_engine_fallback"
return result
hina/retry.py
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@@ -1,82 +0,0 @@
"""
分层重试 — 部署在 orchestrator 调用者层（main.py / worker.py）。
"""
import logging
import os
from typing import Callable
from data.diff_result import VerificationRun
logger = logging.getLogger(__name__)
HEALING_FIXES = {
"compile_error": {
"detect": lambda log: "not found" in (log or "").lower(),
"fix": lambda: _try_set_env(
"COB_LIBRARY_PATH",
"D:\\360安全浏览器下载\\GC32-BDB-SP1-rename-7z-to-exe\\lib\\gnucobol",
),
},
"s0c7": {
"detect": lambda log: "S0C7" in (log or ""),
"fix": lambda: logger.warning("[Retry] S0C7 需要人工修正测试数据中的数值字段"),
},
}
def _try_set_env(key: str, value: str) -> None:
"""尝试设置环境变量（如果当前未设置）"""
if not os.environ.get(key):
os.environ[key] = value
logger.info(f"[Retry] 已设置环境变量 {key}={value}")
else:
logger.info(f"[Retry] {key} 已存在，跳过")
class RetryHandler:
def __init__(self, max_heal: int = 2, max_simple: int = 3):
self.max_heal = max_heal
self.max_simple = max_simple
self.heal_count = 0
self.simple_count = 0
self.history: list[VerificationRun] = []
def run(self, pipeline_fn: Callable[[], VerificationRun]) -> VerificationRun:
while (self.heal_count + self.simple_count) < (self.max_heal + self.max_simple):
vr = pipeline_fn()
self.history.append(vr)
if vr.status in ("PASS", "QUALITY_WARN"):
vr.heal_retry = self.heal_count
vr.simple_retry = self.simple_count
vr.total_retry = self.heal_count + self.simple_count
return vr
if vr.status in ("BLOCKED", "ERROR") and self.heal_count < self.max_heal:
build_log = vr.debug.get("cobol_build", {}).get("log", "")
healed = False
for name, fix_def in HEALING_FIXES.items():
if fix_def["detect"](build_log):
fix_def["fix"]()
self.heal_count += 1
healed = True
logger.info(
f"[Retry] 自愈修复应用: {name} "
f"(heal_retry={self.heal_count})"
)
break
if healed:
continue
self.simple_count += 1
logger.info(f"[Retry] 朴素重试 (simple_retry={self.simple_count})")
logger.error("[Retry] 重试次数超过上限，标记 FATAL")
vr = self.history[-1] if self.history else VerificationRun(
status="FATAL", exit_code=4
)
vr.status = "FATAL"
vr.exit_code = 4
vr.heal_retry = self.heal_count
vr.simple_retry = self.simple_count
vr.total_retry = self.heal_count + self.simple_count
return vr
hina/rule_engine/__init__.py
-47
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@@ -1,47 +0,0 @@
"""HINA 混淆组判定规则引擎
公开 API:
resolve_confusion_pair() — 根据 pair_name 调度对应函数
detect_contradictions() — 检测可能矛盾的类型对
resolve_contradiction() — 解决矛盾，返回胜出的类型名
BacktrackResolver — 多轮回溯判定
"""
from __future__ import annotations
from .confusion_groups import (
resolve_confusion_pair,
resolve_matching_vs_keybreak,
resolve_dedup_vs_nodedup,
resolve_validation_vs_keybreak,
resolve_csv_merge_vs_split,
resolve_simple_vs_two_stage,
resolve_pure_vs_mixed,
resolve_division_50_25_100,
resolve_mn_output_mode,
)
from .contradiction import (
CONTRADICTION_PAIRS,
detect_contradictions,
resolve_contradiction,
)
from .backtrack import BacktrackResolver
__all__ = [
# 混淆组判定
"resolve_confusion_pair",
"resolve_matching_vs_keybreak",
"resolve_dedup_vs_nodedup",
"resolve_validation_vs_keybreak",
"resolve_csv_merge_vs_split",
"resolve_simple_vs_two_stage",
"resolve_pure_vs_mixed",
"resolve_division_50_25_100",
"resolve_mn_output_mode",
# 矛盾检测与解决
"CONTRADICTION_PAIRS",
"detect_contradictions",
"resolve_contradiction",
# 回溯
"BacktrackResolver",
]
hina/rule_engine/backtrack.py
-96
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@@ -1,96 +0,0 @@
"""回溯机制 — 多轮判定，必要时重新提取特征以化解矛盾。
BacktrackResolver 封装了多轮判定的核心逻辑:
1. 用当前 features 检测矛盾。
2. 对有矛盾的对调用 resolve_contradiction。
3. 如果仍然存在矛盾，重新提取特征再判定。
4. 超过 max_rounds 轮或 30s 超时后降级。
"""
from __future__ import annotations
import time
from typing import Any, Callable
from .contradiction import detect_contradictions, resolve_contradiction
class BacktrackResolver:
"""多轮回溯判定器。
Args:
structure_extractor: 接受 COBOL 源码字符串，返回 features dict 的可调用对象。
"""
def __init__(self, structure_extractor: Callable[[str], dict[str, Any]]) -> None:
self.extract = structure_extractor
self.max_rounds = 3
def _needs_backtrack(self, contradictions: list[dict]) -> bool:
"""判断是否需要回溯重提取。
只要检测到矛盾（列表非空），就需要回溯。
"""
return len(contradictions) > 0
def resolve(self, cobol_source: str, initial_features: dict) -> dict[str, Any]:
"""多轮判定，30s 超时降级。
Args:
cobol_source: COBOL 程序源码。
initial_features: 初始提取的特征字典。
Returns:
最终的特征字典，可能包含 backtrack_rounds 和 backtrack_timeout 信息。
"""
start = time.time()
features: dict[str, Any] = dict(initial_features)
features["backtrack_rounds"] = 0
for round_num in range(1, self.max_rounds + 1):
# 超时检查
if time.time() - start > 30:
features["backtrack_timeout"] = True
break
# 检测矛盾
contradictions = detect_contradictions(features)
if not contradictions:
# 无矛盾，判定完成
features["backtrack_resolved"] = True
break
# 解决矛盾
for c in contradictions:
resolution = resolve_contradiction(features, c)
# 将解决结果写入 features
resolved_types = features.setdefault("resolved_types", {})
resolved_types[f"resolved_{c['name']}"] = resolution
features["backtrack_rounds"] = round_num
# 判断是否需要重新提取
if self._needs_backtrack(contradictions):
# 重新提取特征
try:
new_features = self.extract(cobol_source)
# 合并新特征，保留旧特征中的回溯状态和已解决的矛盾
preserved_keys = ("backtrack_rounds", "backtrack_timeout", "resolved_types")
preserved = {k: features[k] for k in preserved_keys if k in features}
features.update(new_features)
features.update(preserved)
except Exception:
features["backtrack_extract_error"] = True
break
else:
# max_rounds 耗尽，标记降级
features["backtrack_degraded"] = True
# 确保时间字段存在
elapsed = time.time() - start
features.setdefault("backtrack_timeout", False)
features.setdefault("backtrack_resolved", False)
features.setdefault("backtrack_degraded", False)
features["backtrack_elapsed"] = round(elapsed, 3)
return features
hina/rule_engine/confusion_groups.py
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@@ -1,235 +0,0 @@
"""混淆组判定规则引擎 — 8 个混淆对的化解函数。
每个函数接收 features dict，返回:
{
"resolved_type": str,
"confidence": float,
"evidence": list[str],
}
"""
from __future__ import annotations
def resolve_matching_vs_keybreak(features: dict) -> dict:
"""区分「マッチング」与「キーブレイク」。
规则:
- IF 三路分支 (comparison ≥ 2) + SELECT 文件数 ≥ 2 → マッチング
- IF 双路分支 (equality 为主) + WS-PREV-KEY 存在 + 累加器存在 → キーブレイク
"""
if_types = features.get("if_types", {})
total_ifs = if_types.get("total", 0)
comparison_ifs = if_types.get("comparison", 0)
equality_ifs = if_types.get("equality", 0)
select_files = features.get("select_files", {})
file_count = len(select_files) if isinstance(select_files, dict) else features.get("file_count", 0)
variable_patterns = features.get("variable_patterns", {})
has_prev_key = variable_patterns.get("has_prev_key", False)
has_accumulator = variable_patterns.get("has_accumulator", False)
evidence: list[str] = []
# 规则 1: 三路分支 + 多文件 → マッチング
if comparison_ifs >= 2 and file_count >= 2:
evidence.append(f"三路 IF 分支 (comparison={comparison_ifs}) + SELECT 文件数 >=2 ({file_count}) → マッチング")
return {"resolved_type": "マッチング", "confidence": 0.90, "evidence": evidence}
# 规则 2: 双路 + WS-PREV-KEY + 累加器 → キーブレイク
if total_ifs >= 1 and has_prev_key and has_accumulator:
evidence.append(f"WS-PREV-KEY 存在 + 累加器存在 + IF 分支 → キーブレイク")
return {"resolved_type": "キーブレイク", "confidence": 0.85, "evidence": evidence}
# 补充规则: SELECT 文件数 >= 2 且 comparison 至少 1 → 倾向マッチング
if file_count >= 2 and comparison_ifs >= 1:
evidence.append(f"SELECT 文件数 >=2 + comparison IF >=1 → マッチング")
return {"resolved_type": "マッチング", "confidence": 0.75, "evidence": evidence}
# 回退: 无法明确判定
evidence.append(f"特征不足: total_ifs={total_ifs}, comparison={comparison_ifs}, "
f"file_count={file_count}, has_prev_key={has_prev_key}, "
f"has_accumulator={has_accumulator}")
return {"resolved_type": "unknown", "confidence": 0.0, "evidence": evidence}
def resolve_dedup_vs_nodedup(features: dict) -> dict:
"""区分「項目チェック(重複含む)」与「項目チェック(重複含まず)」。
规则:
- WS-PREV-KEY 存在 → 含重复
- 无 WS-PREV-KEY → 不含重复
"""
variable_patterns = features.get("variable_patterns", {})
has_prev_key = variable_patterns.get("has_prev_key", False)
evidence: list[str] = []
if has_prev_key:
evidence.append("WS-PREV-KEY 存在 → 含重复")
return {"resolved_type": "項目チェック(重複含む)", "confidence": 0.90, "evidence": evidence}
else:
evidence.append("未检测到 WS-PREV-KEY → 不含重复")
return {"resolved_type": "項目チェック(重複含まず)", "confidence": 0.85, "evidence": evidence}
def resolve_validation_vs_keybreak(features: dict) -> dict:
"""区分「編集処理(校验)」与「キーブレイク」。
规则:
- WS-ERR* 相关字段存在 → 校验 (validation)
- WS-*CNT 累加计数器存在 → キーブレイク (key break)
"""
variable_patterns = features.get("variable_patterns", {})
has_error_flag = variable_patterns.get("has_error_flag", False)
has_counter = variable_patterns.get("has_counter", False)
evidence: list[str] = []
if has_error_flag:
evidence.append("WS-ERR* 错误字段存在 → 校验")
return {"resolved_type": "編集処理(校验)", "confidence": 0.85, "evidence": evidence}
if has_counter:
evidence.append("WS-*CNT 计数器存在 → キーブレイク")
return {"resolved_type": "キーブレイク", "confidence": 0.80, "evidence": evidence}
evidence.append("既无错误字段也无计数器，无法判定")
return {"resolved_type": "unknown", "confidence": 0.0, "evidence": evidence}
def resolve_csv_merge_vs_split(features: dict) -> dict:
"""区分 CSV 合并与拆分。
规则:
- STRING 语句存在 → 无换行 (合并, merge)
- INSPECT REPLACING 存在 → 有换行 (拆分, split)
"""
has_string = features.get("has_string", False)
has_inspect = features.get("has_inspect", False)
evidence: list[str] = []
if has_string:
evidence.append("STRING 语句存在 → CSV 合并 (无换行)")
return {"resolved_type": "CSV合并", "confidence": 0.85, "evidence": evidence}
if has_inspect:
evidence.append("INSPECT REPLACING 存在 → CSV 拆分 (有换行)")
return {"resolved_type": "CSV拆分", "confidence": 0.85, "evidence": evidence}
evidence.append("既无 STRING 也无 INSPECT REPLACING")
return {"resolved_type": "unknown", "confidence": 0.0, "evidence": evidence}
def resolve_simple_vs_two_stage(features: dict) -> dict:
"""区分「単純マッチング」与「二段階マッチング」。
规则:
- OPEN → CLOSE → 再 OPEN 模式 → 二级匹配
- 其他顺序 → 简单匹配
"""
open_pattern = features.get("open_pattern", "")
evidence: list[str] = []
if open_pattern == "open-close-open":
evidence.append("OPEN→CLOSE→再OPEN 模式 → 二级匹配")
return {"resolved_type": "二段階マッチング", "confidence": 0.90, "evidence": evidence}
else:
evidence.append(f"OPEN 模式为 '{open_pattern}' → 简单匹配")
return {"resolved_type": "単純マッチング", "confidence": 0.80, "evidence": evidence}
def resolve_pure_vs_mixed(features: dict) -> dict:
"""区分「純粋マッチング」与「混合マッチング」。
规则:
- variable_patterns 中 has_switch 且 has_counter → 混合（隐含额外键比较）
- 有 PERFORM 且 多文件 → 可能混合
- 否则 → 纯粹匹配（低确信度，因无法静态确定有无额外键比较）
"""
variable_patterns = features.get("variable_patterns", {})
if_types = features.get("if_types", {})
evidence: list[str] = []
has_switch = variable_patterns.get("has_switch", False)
has_counter = variable_patterns.get("has_counter", False)
if_count = if_types.get("total", 0)
if has_switch and has_counter and if_count >= 3:
evidence.append("多个变量模式和 IF 分支 → 可能混合匹配")
return {"resolved_type": "混合マッチング", "confidence": 0.70, "evidence": evidence}
evidence.append("无明确混合特征 → 纯粹匹配（需数据验证）")
return {"resolved_type": "unknown", "confidence": 0.0, "evidence": evidence}
def resolve_division_50_25_100(features: dict) -> dict:
"""区分 DIVIDE 被除数常量 50/25/100。
从 features["divide_constants"] 列表中匹配已知常量。
"""
divide_constants = features.get("divide_constants", [])
evidence: list[str] = []
if not isinstance(divide_constants, (list, tuple)):
evidence.append("divide_constants 格式无效")
return {"resolved_type": "unknown", "confidence": 0.0, "evidence": evidence}
for c in divide_constants:
if c in (50, 25, 100):
evidence.append(f"DIVIDE 被除数 = {c}")
return {"resolved_type": f"DIVIDE_{c}", "confidence": 0.95, "evidence": evidence}
evidence.append(f"未匹配已知常量 (50/25/100)，当前值: {divide_constants}")
return {"resolved_type": "unknown", "confidence": 0.0, "evidence": evidence}
def resolve_mn_output_mode(features: dict) -> dict:
"""判断 M:N 输出模式。
规则:
- 根据文件或记录数判断 M:N 关系
- 返回 unknown 注明需数据验证
"""
select_files = features.get("select_files", {})
file_count = len(select_files) if isinstance(select_files, dict) else features.get("file_count", 0)
evidence: list[str] = []
# 尝试判断 M:N（从现有特征推断）
select_count = len(select_files)
total_branches = features.get("total_branches", 0)
if select_count >= 2 and total_branches >= 3:
evidence.append(f"SELECT={select_count}, 分支={total_branches} → 可能 M:N")
return {"resolved_type": "M:N", "confidence": 0.65, "evidence": evidence}
if file_count >= 3:
evidence.append(f"文件数 {file_count} >= 3, 可能为 M:N 关系")
return {"resolved_type": "M:N", "confidence": 0.60, "evidence": evidence}
evidence.append("需数据验证确定 M:N 输出模式")
return {"resolved_type": "unknown", "confidence": 0.0, "evidence": evidence}
# ── 调度表 ──────────────────────────────────────────────────────────────────
_RESOLVER_MAP = {
"matching_vs_keybreak": resolve_matching_vs_keybreak,
"dedup_vs_nodedup": resolve_dedup_vs_nodedup,
"validation_vs_keybreak": resolve_validation_vs_keybreak,
"csv_merge_vs_split": resolve_csv_merge_vs_split,
"simple_vs_two_stage": resolve_simple_vs_two_stage,
"pure_vs_mixed": resolve_pure_vs_mixed,
"division_50_25_100": resolve_division_50_25_100,
"mn_output_mode": resolve_mn_output_mode,
}
def resolve_confusion_pair(features: dict, pair_name: str) -> dict:
"""Dispatch to the correct function by pair_name."""
resolver = _RESOLVER_MAP.get(pair_name)
if resolver is None:
return {
"resolved_type": "unknown",
"confidence": 0.0,
"evidence": [f"未知混淆对名称: {pair_name}"],
}
return resolver(features)
hina/rule_engine/contradiction.py
-163
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@@ -1,163 +0,0 @@
"""矛盾检测与解决 — 检测来自不同混淆组的类型冲突。
CONTRADICTION_PAIRS 定义了可能会矛盾的分类类型对。
"""
from __future__ import annotations
from typing import Any
# ── 矛盾对定义 ──────────────────────────────────────────────────────────────
CONTRADICTION_PAIRS: list[dict[str, str]] = [
{
"name": "matching_vs_keybreak",
"type_a": "マッチング",
"type_b": "キーブレイク",
},
{
"name": "dedup_vs_nodedup",
"type_a": "項目チェック(重複含む)",
"type_b": "項目チェック(重複含まず)",
},
{
"name": "validation_vs_keybreak",
"type_a": "編集処理(校验)",
"type_b": "キーブレイク",
},
{
"name": "csv_merge_vs_split",
"type_a": "CSV合并",
"type_b": "CSV拆分",
},
{
"name": "simple_vs_two_stage",
"type_a": "単純マッチング",
"type_b": "二段階マッチング",
},
{
"name": "pure_vs_mixed",
"type_a": "純粋マッチング",
"type_b": "混合マッチング",
},
{
"name": "division_50_25_100",
"type_a": "DIVIDE_50",
"type_b": "DIVIDE_100",
},
{
"name": "division_50_25_100",
"type_a": "DIVIDE_50",
"type_b": "DIVIDE_25",
},
{
"name": "division_50_25_100",
"type_a": "DIVIDE_100",
"type_b": "DIVIDE_25",
},
{
"name": "mn_output_mode",
"type_a": "M:N",
"type_b": "1:1",
},
]
# ── 冲突优先级: 当同一种类型被多个混淆组判定时，优先级高者胜出 ──────────
TYPE_PRIORITY: dict[str, int] = {
"マッチング": 10,
"キーブレイク": 9,
"項目チェック(重複含む)": 8,
"項目チェック(重複含まず)": 8,
"編集処理(校验)": 7,
"CSV合并": 6,
"CSV拆分": 6,
"単純マッチング": 5,
"二段階マッチング": 5,
"純粋マッチング": 4,
"混合マッチング": 4,
"DIVIDE_50": 3,
"DIVIDE_100": 3,
"DIVIDE_25": 3,
"M:N": 2,
"1:1": 2,
}
def detect_contradictions(features: dict) -> list[dict]:
"""检测可能矛盾的类型对，返回矛盾列表。
检查 features["resolved_types"] 中已判定的类型，
如果同一混淆组内两个类型同时存在，或不同组的类型存在冲突，则记录。
Args:
features: 包含所有已判定的 resolved_types 字典。
Returns:
矛盾列表。每个元素格式: {"name": str, "type_a": str, "type_b": str}
"""
resolved_types: dict[str, str] = features.get("resolved_types", {})
if not resolved_types:
return []
contradictions: list[dict] = []
for pair in CONTRADICTION_PAIRS:
name = pair["name"]
type_a = pair["type_a"]
type_b = pair["type_b"]
# 检查该混淆组的判定结果中是否同时包含两个类型
for key, resolved_type in resolved_types.items():
if resolved_type == type_a:
for other_key, other_type in resolved_types.items():
if other_key != key and other_type == type_b:
contradictions.append({
"name": name,
"type_a": type_a,
"type_b": type_b,
"source_a": key,
"source_b": other_key,
})
break
break
return contradictions
def resolve_contradiction(features: dict, contradiction: dict) -> str:
"""解决矛盾，返回胜出的类型名。
策略:
1. 根据 TYPE_PRIORITY 取优先级高的类型。
2. 若优先级相同，根据 features 中的额外证据选择。
Args:
features: 完整特征字典。
contradiction: detect_contradictions 返回的单个矛盾。
Returns:
胜出的类型名称。
"""
type_a = contradiction["type_a"]
type_b = contradiction["type_b"]
priority_a = TYPE_PRIORITY.get(type_a, 0)
priority_b = TYPE_PRIORITY.get(type_b, 0)
if priority_a > priority_b:
return type_a
elif priority_b > priority_a:
return type_b
# 优先级相同，尝试使用 confusion_groups 重判定
from .confusion_groups import resolve_confusion_pair
pair_name = contradiction.get("name", "")
if pair_name:
result = resolve_confusion_pair(features, pair_name)
if result.get("confidence", 0) >= 0.80:
return result["resolved_type"]
# 最终回退: 取 type_a
return type_a
hina/strategy.py
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"""
HINA 策略模板 — 根据程序分类定义必须的测试项和边界条件。
Task 2.2: 必须项模板 + supplement 函数
"""
STRATEGY_TEMPLATES: dict[str, dict] = {
"マッチング": {
"required": [
"COM-N001", "COM-N002", "COM-A002", "COM-A003",
"MT-N001", "MT-N002", "MT-N004", "MT-N005", "MT-N006",
],
"boundary": ["MT-B001", "MT-B002"],
},
"キーブレイク": {
"required": [
"COM-N001", "COM-A002",
"KB-N001", "KB-N004", "KB-N005", "KB-A001",
],
"boundary": ["KB-B001", "KB-B002"],
},
"条件分岐": {
"required": [
"B-N001", "B-N003", "B-N006", "B-N009",
],
},
"内部表検索": {
"required": [
"T-N001", "T-N002", "T-A001", "T-A002",
],
},
"項目チェック": {
"required": [
"VF-N001", "VF-N002", "VF-N004", "VF-A001",
],
},
}
def get_strategy(hina_type: str) -> dict:
"""返回对应 HINA 类型的策略模板。
Args:
hina_type: HINA 程序分类名称（如 "マッチング"）。
Returns:
dict: required 列表及可选的 boundary 列表。
未知类型返回空模板 {"required": [], "boundary": []}。
"""
return STRATEGY_TEMPLATES.get(hina_type, {"required": [], "boundary": []})
def _make_marker(code: str, prefix: str = "REQ") -> dict:
"""生成一条标记记录。"""
return {
"id": f"{prefix}-{code}",
"coverage_targets": [code],
"fields": {},
}
def supplement(base_tests: list[dict], hina_result: dict) -> list[dict]:
"""根据 HINA 类型追加模板中的必须项标记记录。
从 ``hina_result["category"]`` 获取分类，查找对应的策略模板，
将模板中所有的 required 和 boundary 项以标记记录形式追加到测试列表末尾。
Args:
base_tests: 已有的测试数据列表（每个元素为 dict）。
hina_result: HINA 分类结果，至少包含 ``{"category": str}``。
Returns:
list[dict]: 追加必须项标记记录后的完整测试列表。
"""
hina_type = hina_result.get("category", "unknown")
template = get_strategy(hina_type)
result = list(base_tests)
for code in template.get("required", []):
result.append(_make_marker(code))
for code in template.get("boundary", []):
result.append(_make_marker(code, prefix="BND"))
return result
def supplement_only(base_tests: list[dict], hina_gaps: list[str]) -> list[dict]:
"""增量补充指定必须项的标记记录。
根据传入的 code 列表（而不是从模板查找），只追加缺失的那些必须项标记。
Args:
base_tests: 已有的测试数据列表（每个元素为 dict）。
hina_gaps: 需要补充的 HINA 必须项 code 列表。
Returns:
list[dict]: 追加标记记录后的完整测试列表。
"""
result = list(base_tests)
for code in hina_gaps:
result.append(_make_marker(code))
return result
japanese_data.py
-234
View File
@@ -1,234 +0,0 @@
"""Japanese test data generation lookup tables and helper functions.
Provides constants and generators for creating Japanese-language test data
including fullwidth/halfwidth characters, Shift-JIS encoding edge cases,
wareki (Japanese era) dates, and encoding round-trip test data.
"""
from __future__ import annotations
import random
from datetime import date, timedelta
# ── Lookup table constants ──
FULLWIDTH_KATAKANA = "アイウエオカキクケコサシスセソタチツテトナニヌネノハヒフヘホマミムメモヤユヨラリルレロワヲン"
FULLWIDTH_HIRAGANA = "あいうえおかきくけこさしすせそたちつてとなにぬねのはひふへほまみむめもやゆよらりるれろわをん"
FULLWIDTH_DIGITS = "０１２３４５６７８９"
FULLWIDTH_ALPHA = "ＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺ"
HALFWIDTH_KATAKANA = "ｱｲｳｴｵｶｷｸｹｺｻｼｽｾｿﾀﾁﾂﾃﾄﾅﾆﾇﾈﾉﾊﾋﾌﾍﾎﾏﾐﾑﾒﾓﾔﾕﾖﾗﾘﾙﾚﾛﾜｦﾝ"
# Shift-JIS 第2字节 0x5C 问题文字
SJIS_5C_PROBLEM = ["ソ", "噂", "能", "刈", "搾", "汚"]
# Shift-JIS 第2字节 0x7C 问题文字
SJIS_7C_PROBLEM = ["本", "問", "王", "歓", "輸"]
WAREKI_BOUNDARIES = [
("令和", 2019, "R010501", None, None),
("平成", 1989, "H010108", "2019/04/30", "H310430"),
("昭和", 1926, "S611231", "1989/01/07", "S640107"),
("大正", 1912, "T011231", "1926/12/25", "T151225"),
("明治", 1868, "M451229", "1912/01/29", "M450129"),
]
# ── Helper: simulate COBOL PIC clause field for length ──
def _field_length(field: dict) -> int:
"""Get the storage length from a PIC field definition dict."""
if "pic_info" in field and field["pic_info"]:
pi = field["pic_info"]
if pi.get("length", 0) > 0:
return pi["length"]
dig = pi.get("digits", 0)
dec = pi.get("decimal", 0)
return dig + dec
if "length" in field:
return field["length"]
if "digits" in field:
d = field["digits"]
dec = field.get("decimal", 0)
return d + dec
return 10 # fallback
# ── Generation functions ──
def generate_fullwidth_text(field: dict) -> str:
"""Generate fullwidth text filling a PIC N field.
Returns a string of fullwidth katakana characters padded to the field length.
Each PIC N character is 2 bytes (fullwidth), so the number of characters
equals the field length.
"""
length = _field_length(field)
if length <= 0:
length = 10
chars = list(FULLWIDTH_KATAKANA)
return "".join(random.choice(chars) for _ in range(length))
def generate_halfwidth_katakana(field: dict) -> str:
"""Generate halfwidth katakana filling a PIC X field.
Returns a string of halfwidth katakana characters to fit the field byte length.
Halfwidth katakana are single-byte in Shift-JIS, so the character count
equals the field length.
"""
length = _field_length(field)
if length <= 0:
length = 10
chars = list(HALFWIDTH_KATAKANA)
return "".join(random.choice(chars) for _ in range(length))
def generate_sjis_5c_problem(field: dict) -> str:
"""Generate a string containing Shift-JIS 0x5C problem characters.
These characters have 0x5C (backslash) as their second byte in Shift-JIS,
which can be misinterpreted as an escape character.
"""
length = _field_length(field)
if length <= 0:
length = 6
result = []
chars = list(SJIS_5C_PROBLEM)
while len(result) < length:
result.append(random.choice(chars))
return "".join(result)
def generate_sjis_7c_problem(field: dict) -> str:
"""Generate a string containing Shift-JIS 0x7C problem characters.
These characters have 0x7C (pipe) as their second byte in Shift-JIS,
which can be misinterpreted as a field separator.
"""
length = _field_length(field)
if length <= 0:
length = 5
result = []
chars = list(SJIS_7C_PROBLEM)
while len(result) < length:
result.append(random.choice(chars))
return "".join(result)
def generate_wareki_date(wareki_type: str = "R") -> str:
"""Generate a Japanese era (wareki) date string.
Args:
wareki_type: Era prefix letter:
"R" = Reiwa (令和), "H" = Heisei (平成),
"S" = Showa (昭和), "T" = Taisho (大正),
"M" = Meiji (明治)
Returns:
Wareki date string formatted as e.g. "R050101" (Reiwa 5, Jan 1).
The year part is zero-padded to 2 digits (e.g. 01, 05, 12).
"""
era_map = {
"R": ("令和", 2019),
"H": ("平成", 1989),
"S": ("昭和", 1926),
"T": ("大正", 1912),
"M": ("明治", 1868),
}
if wareki_type not in era_map:
wareki_type = "R"
era_name, base_year = era_map[wareki_type]
# Generate a random date within the era's range (assuming at least 30 years)
year_offset = random.randint(1, 30)
month = random.randint(1, 12)
day = random.randint(1, 28)
return f"{wareki_type}{year_offset:02d}{month:02d}{day:02d}"
def generate_wareki_boundary(era: str = "平成") -> tuple[str, str]:
"""Generate a pair of wareki date strings representing an era boundary.
Args:
era: Era name in Japanese: "令和", "平成", "昭和", "大正", "明治"
Returns:
Tuple of (end_date_of_previous_era, start_date_of_new_era),
e.g. for "平成": ("S640107", "H010108")
"""
boundaries = {name: (prev_end, new_start) for name, _, prev_end, _, new_start in WAREKI_BOUNDARIES if prev_end and new_start}
if era not in boundaries:
# Default to Heisei boundary
era = "平成"
return boundaries[era]
def generate_encoding_test_data(from_enc: str = "shift_jis", to_enc: str = "utf-8") -> tuple[bytes, bytes]:
"""Generate encoding test data with round-trip verification.
Creates a known string, encodes it to the source encoding, decodes to
the target encoding, and returns both for comparison.
Args:
from_enc: Source encoding name (default: "shift_jis")
to_enc: Target encoding name (default: "utf-8")
Returns:
Tuple of (source_bytes, target_bytes) for comparison.
"""
test_string = "あいうえおアイウエオ亜唖娃阿"
source_bytes = test_string.encode(from_enc, errors="replace")
decoded = source_bytes.decode(from_enc, errors="replace")
target_bytes = decoded.encode(to_enc, errors="replace")
return source_bytes, target_bytes
def generate_encoding_test_data_bytes(text: str = None, from_enc: str = "shift_jis", to_enc: str = "utf-8") -> tuple[bytes, bytes]:
"""Generate encoding test data from explicit text.
Args:
text: Source text to encode; defaults to Japanese test phrase
from_enc: Source encoding name
to_enc: Target encoding name
Returns:
Tuple of (source_bytes, target_bytes)
"""
if text is None:
text = "あいうえおアイウエオ亜唖娃阿"
source_bytes = text.encode(from_enc, errors="replace")
decoded = source_bytes.decode(from_enc, errors="replace")
target_bytes = decoded.encode(to_enc, errors="replace")
return source_bytes, target_bytes
def select_data_type(field: dict) -> str:
"""Select the appropriate data type label for a field.
Examines the field definition and returns a label indicating
the kind of test data to generate.
Args:
field: Field definition dict with 'pic_info' containing 'type' and 'usage'
Returns:
One of: "japanese", "numeric", "halfwidth"
"""
pi = field.get("pic_info", {})
typ = pi.get("type", "unknown")
usage = pi.get("usage", "").upper() if pi.get("usage") else ""
# PIC N (national) or USAGE NATIONAL → Japanese fullwidth
if typ == "national" or usage == "NATIONAL":
return "japanese"
# PIC 9 or numeric usage → numeric
if typ in ("numeric", "numeric_edited", "numeric_float") or "COMP" in usage:
return "numeric"
# PIC X with DISPLAY usage → halfwidth katakana candidate
if typ == "alphanumeric" or typ == "alphabetic":
return "halfwidth"
return "halfwidth"
jcl/__init__.py
-24
View File
@@ -1,24 +0,0 @@
"""JCL 解析与执行包
公开 API:
parse_jcl() — JCL 解析 → Job 对象
JclExecutor — JCL 执行器（编译 + 运行 COBOL）
Job — JCL 作业
JobStep — JCL 步骤
DDEntry — DD 条目
CondParam — COND 参数
"""
from __future__ import annotations
from .parser import parse_jcl, Job, JobStep, DDEntry, CondParam
from .executor import JclExecutor
__all__ = [
"parse_jcl", # (filepath: str) → Optional[Job]
"JclExecutor", # class
"Job", # dataclass
"JobStep", # dataclass
"DDEntry", # dataclass
"CondParam", # dataclass
]
jcl/executor.py
+2 -11
View File
@@ -59,17 +59,8 @@ class JclExecutor:
elif name in ("VALIDOUT", "REJECT", "REPORTERR", "CALCOUT", "STMT", "SUMMARY"):
env_out[name] = str(path)
# 创建空输入文件（如果无 input DD）
if env_in:
input_path = env_in.get(next(iter(env_in.keys())), "")
else:
import tempfile
empty = Path(tempfile.mkstemp(suffix=".bin")[1])
empty.write_bytes(b"")
input_path = str(empty)
output_path = env_out.get(next(iter(env_out.keys()), ""), str(self.root_dir / "data" / "work" / f"{step.step_name.lower()}_out.bin"))
# 确保输出目录存在
Path(output_path).parent.mkdir(parents=True, exist_ok=True)
input_path = env_in.get(list(env_in.keys())[0], "")
output_path = env_out.get(list(env_out.keys())[0], str(self.root_dir / "data" / "work" / f"{step.step_name.lower()}_out.bin"))
run = runner.run(build.artifact_path, input_path, output_path)
self.results[step.step_name] = {
main.py
-5
View File
@@ -15,9 +15,6 @@ def main():
p.add_argument("--verbose", action="store_true")
p.add_argument("--dry-run", action="store_true")
p.add_argument("--output-dir", default="./reports")
p.add_argument("--quality-gate-mode", choices=["warn", "off"], default="warn",
help="质量门禁模式: warn=记录警告, off=关闭")
p.add_argument("--gcov", action="store_true", help="启用 gcov 覆盖率采集")
args = p.parse_args()
if args.dry_run:
@@ -38,8 +35,6 @@ def main():
c.runner_mode = args.runner
c.coverage_default = args.coverage
c.tolerance = args.tolerance
c.quality_gate_mode = args.quality_gate_mode
c.gcov_enabled = args.gcov
vr = run_pipeline(c, args.copybook, args.cobol_src, args.java_src, args.mapping)
t = vr.fields_matched + vr.fields_mismatched
print(f"{vr.program}: {vr.status} ({vr.fields_matched}/{t}, {vr.duration_s:.0f}s)" if t else f"{vr.program}: {vr.status}")
orchestrator.py
+15 -83
View File
@@ -1,19 +1,23 @@
import shutil, time, logging
import shutil, time
from pathlib import Path
from data.field_tree import FieldTree
from data.test_case import TestSuite, SparkConfig, TestCase
from data.test_case import TestSuite, SparkConfig
from data.diff_result import VerificationRun, FieldResult
from runners.runner import Runner
from runners import NativeJavaRunner, SparkJavaRunner, CobolRunner, DataWriter
from agents import Agent1Parser, Agent2Data, Agent3Diagnostic, LLMClient
from comparator import align_records, compare_field, CobolBinaryReader
from report import ReportGenerator
from storage import TestDataBundle
from runners.native_java_runner import NativeJavaRunner
from runners.spark_java_runner import SparkJavaRunner
from runners.cobol_runner import CobolRunner
from runners.data_writer import DataWriter
from agents.agent1_parser import Agent1Parser
from agents.agent2_data import Agent2Data
from agents.agent3_diagnostic import Agent3Diagnostic
from agents.llm import LLMClient
from comparator.aligner import align_records
from comparator.field_compare import compare_field
from comparator.cobol_binary_reader import CobolBinaryReader
from report.generator import ReportGenerator
from storage.bundle import TestDataBundle
from config import Config
from cobol_testgen import extract_structure, generate_data, incremental_supplement, check_coverage
from hina import classify_program, gate_check, supplement as strategy_supplement
logger = logging.getLogger(__name__)
def run_pipeline(cfg: Config, cpath: str, cbl: str, java: str, map_path: str) -> VerificationRun:
@@ -36,80 +40,8 @@ def run_pipeline(cfg: Config, cpath: str, cbl: str, java: str, map_path: str) ->
if vr.llm_cost > cfg.max_llm_cost:
return _done(vr, t0, "BLOCKED", 3)
# ── Phase 1+2: cobol_testgen + HINA Agent + 策略 Agent + 质量门禁 ──
try:
cobol_src_text = Path(cbl).read_text(encoding="utf-8")
structure = extract_structure(cobol_src_text, source_dir=str(Path(cbl).parent))
# cobol_testgen 路径枚举 + 基础数据生成
base_records = generate_data(cobol_src_text, structure, source_dir=str(Path(cbl).parent))
vr.debug["cobol_testgen_records"] = len(base_records)
vr.debug["total_branches"] = structure.get("total_branches", 0)
# 转换为 TestCase 列表（增强管线的基础数据集）
complete_tests = []
for i, rec in enumerate(base_records):
complete_tests.append(TestCase(id=f"CTG-{i+1:04d}", fields=dict(rec)))
# HINA 完整类型判定管道（Keyword / 规则引擎 / LLM 辅助三路径）
classification: dict = {}
try:
classification = classify_program(cobol_src_text, llm=llm)
vr.hina_type = classification["category"]
vr.hina_confidence = classification["confidence"]
vr.debug["classification"] = classification
if classification["needs_review"]:
vr.quality_warn = f"类型判定确信度过低({classification['confidence']:.0%})"
except Exception as e:
vr.debug["hina_classify_error"] = str(e)
logger.warning(f"[orchestrator] HINA 类型判定失败: {e}")
# 策略 Agent 补充（追加标记记录，统一为 TestCase 格式）
for m in strategy_supplement([], classification):
complete_tests.append(TestCase(
id=m.get("id", f"STG-{len(complete_tests)+1:04d}"),
fields=m.get("fields", {}),
coverage_targets=m.get("coverage_targets", []),
))
# 质量门禁循环
cov = check_coverage(structure, base_records)
for attempt in range(cfg.max_quality_retries):
gate_result = gate_check(
complete_tests, classification, cov,
decision_threshold=cfg.quality_gate_decision_threshold,
paragraph_threshold=cfg.quality_gate_paragraph_threshold,
)
if gate_result.get("passed"):
break
gaps = gate_result.get("issues", {}).get("decision_gaps", [])
if gaps and structure.get("branch_tree_obj"):
delta = incremental_supplement(structure["branch_tree_obj"], gaps)
base_records.extend(delta)
# 同步更新 complete_tests
for i, d in enumerate(delta):
complete_tests.append(TestCase(
id=f"CTG-S{attempt+1}-{i+1:04d}",
fields=dict(d),
))
cov = check_coverage(structure, base_records)
else:
break
vr.paragraph_rate = 0.0 # Phase 3 通过 gcov 获取精确值
vr.branch_rate = cov.get("branch_rate", 0.0)
vr.decision_rate = cov.get("decision_rate", 0.0)
if cfg.quality_gate_mode != "off" and not gate_result.get("passed", True):
vr.quality_warn = f"质量门禁未完全通过 (尝试 {attempt+1} 次)"
vr.debug["quality_issues"] = gate_result.get("issues", {})
except Exception as e:
vr.debug["cobol_testgen_error"] = str(e)
logger.warning(f"[orchestrator] cobol_testgen 分析失败: {e}")
suite = Agent2Data(llm).design(tree, cfg.coverage_default, cfg.runner_mode == "spark")
vr.llm_cost += 0.002
suite.test_cases = complete_tests # 替换为增强管线数据（P1/P2 修复）
vr.debug["test_cases"] = [{"id":tc.id,"fields":tc.fields,"targets":tc.coverage_targets} for tc in suite.test_cases]
vr.debug["spark_config"] = {"records":suite.spark_config.num_records} if suite.has_spark else None
parametrized/__init__.py
-9
View File
@@ -1,9 +0,0 @@
__all__ = [
"generate_matching_data", "generate_keybreak_data",
"generate_division_data", "generate_zero_byte_file",
"generate_boundary_values", "generate_minimal_records",
"generate_sorted_records", "generate_duplicate_keys",
]
from .matching import generate_matching_data, generate_keybreak_data
from .division import generate_division_data
from .common import generate_zero_byte_file, generate_boundary_values, generate_minimal_records, generate_sorted_records, generate_duplicate_keys
parametrized/common.py
-275
View File
@@ -1,275 +0,0 @@
"""通用测试数据生成工具函数模块。
"""
from __future__ import annotations
import pathlib
import re
from typing import Any
def generate_zero_byte_file(path: str) -> None:
"""生成一个 0 字节的空文件。
自动创建父目录（如果不存在）。
参数
----------
path : str
待创建的空文件路径。
"""
p = pathlib.Path(path)
p.parent.mkdir(parents=True, exist_ok=True)
p.write_bytes(b"")
def generate_minimal_records(fields: list[dict[str, Any]]) -> list[dict[str, Any]]:
"""为给定的字段定义生成 1 条正常记录（最小数据量）。
参数
----------
fields : list[dict]
字段定义列表，每个字典可包含以下键（均为可选）:
- "name" : str 字段名，默认为 "FIELD_{i}"
- "type" : str 类型: "numeric" / "string" / "date"，默认 "string"
- "length" : int 长度，字符串用，默认 10
- "default" : Any 默认值，优先使用
返回
-------
list[dict]
包含一条记录的列表，记录中每个字段的值为类型合理的默认值。
"""
if not fields:
return [{}]
record: dict[str, Any] = {}
for i, f in enumerate(fields):
name = f.get("name", f"FIELD_{i}")
if "default" in f:
record[name] = f["default"]
else:
typ = f.get("type", "string")
if typ == "numeric":
record[name] = 0
elif typ == "date":
record[name] = "0001-01-01"
else: # string
length = f.get("length", 10)
record[name] = "A" * length
return [record]
def _parse_pic(pic: str) -> dict[str, Any]:
"""解析 COBOL PIC 子句，返回类型、位数、小数位等信息。
支持的格式:
- S9(7)V99 signed, 7 整数位, 2 小数位
- 9(4) 无符号, 4 整数位
- S9(3) signed, 3 整数位
- 9(4)V9(2) 无符号, 4 整数位, 2 小数位
- X(10) 字符串, 10 字符
- 9(7)V99 无符号, 7 整数位, 2 小数位
参数
----------
pic : str
COBOL PIC 字符串，如 "S9(7)V99"。
返回
-------
dict
包含 type, digits, decimal, signed, total_digits 等信息的字典。
"""
pic = pic.strip().upper()
result: dict[str, Any] = {
"type": "unknown",
"digits": 0,
"decimal": 0,
"signed": False,
"total_digits": 0,
}
# 字符串类型
if pic.startswith("X") or pic.startswith("A"):
result["type"] = "string"
m = re.match(r'[XA]\((\d+)\)', pic)
if m:
result["digits"] = int(m.group(1))
else:
result["digits"] = 1
return result
# 数值类型
if "9" in pic or pic.startswith("S"):
result["type"] = "numeric"
signed_match = re.match(r'S(.*)', pic)
if signed_match:
result["signed"] = True
pic_body = signed_match.group(1)
else:
result["signed"] = False
pic_body = pic
# 解析整数和小数部分
# 9(7)V99 或 9(7)V9(2)
v_match = re.match(r'9\((\d+)\)V9\((\d+)\)', pic_body)
if v_match:
result["digits"] = int(v_match.group(1))
result["decimal"] = int(v_match.group(2))
else:
# 尝试 9(4) 或 9(7)V99
m2 = re.match(r'9\((\d+)\)', pic_body)
if m2:
result["digits"] = int(m2.group(1))
rest = pic_body[m2.end():]
if rest.startswith("V"):
dec_str = rest[1:]
dm = re.match(r'9\((\d+)\)', dec_str)
if dm:
result["decimal"] = int(dm.group(1))
elif re.match(r'9+', dec_str):
result["decimal"] = len(dec_str)
# 处理简写: 9(7)V99
elif rest.startswith("V"):
dec_part = rest[1:]
dm = re.match(r'9\((\d+)\)', dec_part)
if dm:
result["decimal"] = int(dm.group(1))
elif re.match(r'9+', dec_part):
result["decimal"] = len(dec_part)
result["total_digits"] = result["digits"] + result["decimal"]
return result
return result
def generate_boundary_values(pic: str) -> dict[str, Any]:
"""从 PIC 子句解析出最大值、最小值和溢出值。
参数
----------
pic : str
COBOL PIC 字符串，如 "S9(7)V99"。
返回
-------
dict
{
"max": 类型最大值,
"min": 类型最小值,
"overflow": 溢出值（超出最大位数的值）,
"zero": 0,
"pic_info": 解析出的 PIC 信息,
}
"""
info = _parse_pic(pic)
if info["type"] == "string":
length = info["digits"]
return {
"max": "X" * length,
"min": "" if length == 0 else "A" + " " * (length - 1),
"overflow": "X" * (length + 1) if length > 0 else "X",
"zero": "" if length == 0 else " " * length,
"pic_info": info,
}
if info["type"] == "numeric":
digits = info["digits"]
decimal = info["decimal"]
signed = info["signed"]
factor = 10 ** decimal
total_digits = info.get("total_digits", digits + decimal)
max_val = (10 ** total_digits - 1) / factor
overflow_val = (10 ** (total_digits + 1)) / factor
if signed:
min_val = -max_val
else:
min_val = 0
return {
"max": max_val,
"min": min_val,
"overflow": overflow_val,
"zero": 0.0 if decimal > 0 else 0,
"pic_info": info,
}
return {
"max": None,
"min": None,
"overflow": None,
"zero": None,
"pic_info": info,
}
def generate_sorted_records(
record_count: int = 10,
key_field: str = "KEY",
) -> list[dict[str, Any]]:
"""按 KEY 升序生成记录。
参数
----------
record_count : int
生成记录数，默认 10。
key_field : str
键字段名，默认 "KEY"。
返回
-------
list[dict]
已按 key_field 排序的记录列表。
"""
if record_count < 1:
raise ValueError(f"record_count 必须 >= 1，收到 {record_count}")
records: list[dict[str, Any]] = []
for i in range(record_count):
records.append({
key_field: f"KEY-{i:04d}",
"DATA": f"sorted_data_{i}",
"SEQ": i + 1,
})
return records
def generate_duplicate_keys(
records: list[dict[str, Any]],
key_field: str = "KEY",
) -> list[dict[str, Any]]:
"""在已有记录基础上，为每条记录追加一条或多条同键值记录。
适用于测试重复键处理逻辑（如 SORT MERGE / 去重检查）。
参数
----------
records : list[dict]
原始记录列表。
key_field : str
作为重复键的字段名，默认 "KEY"。
返回
-------
list[dict]
追加了重复键记录的完整列表。
"""
if not records:
return []
duplicates: list[dict[str, Any]] = []
for rec in records:
dup = dict(rec)
dup[key_field] = rec[key_field]
dup["DATA"] = rec.get("DATA", "") + "_DUP"
dup["SEQ"] = rec.get("SEQ", 0) + 10000
duplicates.append(dup)
return records + duplicates
parametrized/division.py
-80
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@@ -1,80 +0,0 @@
"""分割系测试数据生成模块。
提供 generate_division_data() 用于生成按比例/规则分割到多个文件的测试数据，
模拟 COBOL SORT 或 OUTPUT 分件场景。
"""
from __future__ import annotations
import math
from typing import Any
def generate_division_data(
division_type: int = 50,
record_count: int = 50,
) -> list[list[dict[str, Any]]]:
"""生成分割系测试数据。
按指定的分割方式和记录总数，将记录分配到多个文件中。
参数
----------
division_type : int
分割方式:
- 50 对半分割 → 2 个文件，各 50%
- 25 四等分分割 → 4 个文件，各 25%
- 100 全量（不分）→ 1 个文件，100%
record_count : int
记录总数（将在各文件间分配）。
返回
-------
list[list[dict]]
按文件分组的记录列表: [[文件1记录], [文件2记录], ...]
每条记录包含 KEY, DATA, FILE_NO 等字段。
"""
if division_type not in (50, 25, 100):
raise ValueError(f"division_type 必须为 50 / 25 / 100，收到 {division_type}")
if record_count < 1:
raise ValueError(f"record_count 必须 >= 1，收到 {record_count}")
if division_type == 100:
n_files = 1
ratios = [1.0]
elif division_type == 50:
n_files = 2
ratios = [0.5, 0.5]
elif division_type == 25:
n_files = 4
ratios = [0.25, 0.25, 0.25, 0.25]
else:
raise AssertionError("unreachable")
result: list[list[dict[str, Any]]] = []
allocated = 0
for file_no in range(n_files):
if file_no == n_files - 1:
# 最后一个文件获取剩余全部记录
file_count = record_count - allocated
else:
file_count = max(0, int(math.floor(record_count * ratios[file_no])))
# 确保不会超出总记录数
if allocated + file_count > record_count:
file_count = record_count - allocated
file_records: list[dict[str, Any]] = []
for i in range(file_count):
seq = allocated + i + 1
file_records.append({
"KEY": f"DIV-{seq:04d}",
"DATA": f"div_data_{seq}",
"FILE_NO": file_no + 1,
"SEQ": seq,
})
result.append(file_records)
allocated += file_count
return result
parametrized/matching.py
-194
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@@ -1,194 +0,0 @@
"""匹配系测试数据生成模块。
提供两种生成器：
- generate_matching_data() — 生成主/从匹配测试数据
- generate_keybreak_data() — 生成 KEY 切中断测试数据
"""
from __future__ import annotations
import random
from typing import Any
def generate_matching_data(
matching_type: str = "1:1",
record_count_r01: int = 10,
record_count_r02: int = 10,
key_match_ratio: float = 1.0,
) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
"""生成匹配系测试数据。
参数
----------
matching_type : str
匹配模式，支持:
- "1:1" 主件每条在从件最多命中一条
- "1:N" 主件每条在从件可能命中多条
- "N:1" 从件每条在主件可能命中多条
record_count_r01 : int
主文件(R01)记录条数
record_count_r02 : int
从文件(R02)记录条数
key_match_ratio : float
键值匹配比例，0.0~1.0 之间。
1.0 表示全部匹配，0.0 表示全部不匹配。
返回
-------
tuple[list[dict], list[dict]]
(主文件记录列表, 从文件记录列表)
"""
if matching_type not in ("1:1", "1:N", "N:1"):
raise ValueError(f"不支持的 matching_type：{matching_type!r}，应为 '1:1' / '1:N' / 'N:1'")
if not 0.0 <= key_match_ratio <= 1.0:
raise ValueError(f"key_match_ratio 必须在 0.0~1.0 之间，收到 {key_match_ratio}")
if record_count_r01 < 0 or record_count_r02 < 0:
raise ValueError("记录数不能为负数")
main_records: list[dict[str, Any]] = []
sub_records: list[dict[str, Any]] = []
# 生成主文件记录
for i in range(record_count_r01):
main_records.append({
"KEY": f"MAIN-{i:04d}",
"DATA": f"main_data_{i}",
"SEQ": i + 1,
})
# 生成从文件记录
matched = 0
unmatched = 0
if matching_type == "1:1":
# 1:1 — 最多让 record_count_r01 条从件匹配
max_match = min(record_count_r01, record_count_r02)
match_count = int(max_match * key_match_ratio)
for i in range(record_count_r02):
if i < match_count and i < record_count_r01:
sub_records.append({
"KEY": f"MAIN-{i:04d}",
"DATA": f"sub_data_{i}",
"SEQ": i + 1,
})
matched += 1
else:
sub_records.append({
"KEY": f"UNMATCHED-SUB-{unmatched:04d}",
"DATA": f"sub_unmatched_{unmatched}",
"SEQ": record_count_r01 + unmatched + 1,
})
unmatched += 1
elif matching_type == "1:N":
# 1:N — 每条主件可能对应多条从件
match_count = int(record_count_r01 * key_match_ratio)
idx = 0
for i in range(record_count_r01):
if i < match_count:
n_per_main = max(1, record_count_r02 // max(1, match_count))
for _ in range(n_per_main):
if idx < record_count_r02:
sub_records.append({
"KEY": f"MAIN-{i:04d}",
"DATA": f"sub_data_{idx}",
"SEQ": idx + 1,
})
idx += 1
else:
if idx < record_count_r02:
sub_records.append({
"KEY": f"UNMATCHED-SUB-{unmatched:04d}",
"DATA": f"sub_unmatched_{unmatched}",
"SEQ": idx + 1,
})
idx += 1
unmatched += 1
# 补齐剩余
while idx < record_count_r02:
sub_records.append({
"KEY": f"UNMATCHED-SUB-{unmatched:04d}",
"DATA": f"sub_unmatched_{unmatched}",
"SEQ": idx + 1,
})
idx += 1
unmatched += 1
elif matching_type == "N:1":
# N:1 — 多条主件对应同一条从件
match_count = int(record_count_r02 * key_match_ratio)
for i in range(record_count_r02):
if i < match_count:
sub_records.append({
"KEY": f"MAIN-{i % max(1, record_count_r01):04d}",
"DATA": f"sub_data_{i}",
"SEQ": i + 1,
})
matched += 1
else:
sub_records.append({
"KEY": f"UNMATCHED-SUB-{unmatched:04d}",
"DATA": f"sub_unmatched_{unmatched}",
"SEQ": i + 1,
})
unmatched += 1
return main_records, sub_records
def generate_keybreak_data(
group_count: int = 3,
records_per_group: int = 2,
sum_type: str = "accumulate",
) -> list[dict[str, Any]]:
"""生成 KEY 切测试数据，组间 KEY 值变化触发中断。
每组内的记录 KEY 值相同；组间 KEY 值递增。
适用于测试 AT END / BREAK / 集计功能。
参数
----------
group_count : int
分组数量，默认 3。
records_per_group : int
每组记录数，默认 2。
sum_type : str
集计类型:
- "accumulate" 累加型（FIELD 值递增）
- "aggregate" 集计型（FIELD 值相同）
- "mark" 标记型（FIELD 为固定标记值）
返回
-------
list[dict]
包含 KEY、FIELD、GROUP、SEQ 等字段的记录列表。
"""
if group_count < 1:
raise ValueError(f"group_count 必须 >= 1，收到 {group_count}")
if records_per_group < 1:
raise ValueError(f"records_per_group 必须 >= 1，收到 {records_per_group}")
if sum_type not in ("accumulate", "aggregate", "mark"):
raise ValueError(f"不支持的 sum_type：{sum_type!r}")
records: list[dict[str, Any]] = []
seq = 0
for g in range(group_count):
group_key = f"KEY-{chr(65 + g) if g < 26 else g}" # KEY-A, KEY-B, ...
for r in range(records_per_group):
seq += 1
if sum_type == "accumulate":
field_val = (g + 1) * 100 + r + 1
elif sum_type == "aggregate":
field_val = (g + 1) * 100
else: # mark
field_val = f"MARK-{chr(65 + g)}"
records.append({
"KEY": group_key,
"FIELD": field_val,
"GROUP": g + 1,
"SEQ": seq,
})
return records
quality/__init__.py
-16
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@@ -1,16 +0,0 @@
"""质量验证包
公开 API:
L1OffsetValidator — COBOL 编译验证字段偏移
L2RoundtripValidator — COMP-3 值回环验证
"""
from __future__ import annotations
from .l1_offset_validate import L1OffsetValidator
from .l2_value_roundtrip import L2RoundtripValidator
__all__ = [
"L1OffsetValidator", # class
"L2RoundtripValidator", # class
]
report/__init__.py
-13
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@@ -1,13 +0,0 @@
"""报表生成包
公开 API:
ReportGenerator — VerificationRun → JSON / HTML / machine JSON
"""
from __future__ import annotations
from .generator import ReportGenerator
__all__ = [
"ReportGenerator", # class
]
report/generator.py
+8 -80
View File
@@ -9,11 +9,6 @@ class ReportGenerator:
"timestamp": run.timestamp, "duration_s": run.duration_s,
"fields_matched": run.fields_matched, "fields_mismatched": run.fields_mismatched,
"runner": run.runner, "branch_rate": run.branch_rate, "llm_cost": run.llm_cost,
"paragraph_rate": run.paragraph_rate, "decision_rate": run.decision_rate,
"quality_score": run.quality_score, "quality_warn": run.quality_warn,
"hina_type": run.hina_type, "hina_confidence": run.hina_confidence,
"heal_retry": run.heal_retry, "simple_retry": run.simple_retry,
"total_retry": run.total_retry,
"field_results": [{"field_name": fr.field_name, "status": fr.status,
"cobol_value": fr.cobol_value, "java_value": fr.java_value,
"suggestion": fr.suggestion} for fr in run.field_results]}
@@ -26,85 +21,18 @@ class ReportGenerator:
f'</td><td>{fr.status}</td><td>{fr.cobol_value}</td><td>{fr.java_value}</td>'
f'<td>{fr.suggestion}</td></tr>'
for fr in run.field_results)
# 覆盖率卡片
coverage_html = ""
if run.paragraph_rate > 0 or run.branch_rate > 0:
mode = "静态+动态" if run.branch_rate > 0 else "仅静态"
pcolor = "green" if run.paragraph_rate >= 1.0 else "orange"
bcolor = "green" if run.branch_rate >= 0.9 else "orange"
coverage_html = f"""
<h2>覆盖率</h2>
<table border=1 cellpadding=4>
<tr><td>方式</td><td>{mode}</td></tr>
<tr><td>段落覆盖率</td><td style="color:{pcolor}">{run.paragraph_rate:.0%}</td></tr>
<tr><td>分支覆盖率</td><td style="color:{bcolor}">{run.branch_rate:.0%}</td></tr>
<tr><td>决策点覆盖率</td><td>{run.decision_rate:.0%}</td></tr>
</table>"""
# HINA 卡片
hina_html = ""
if run.hina_type:
hina_html = f"""
<h2>HINA 信息</h2>
<table border=1 cellpadding=4>
<tr><td>判定类型</td><td>{run.hina_type}</td></tr>
<tr><td>确信度</td><td>{run.hina_confidence:.0%}</td></tr>
</table>"""
# 质量评分卡片
quality_html = ""
if run.quality_score > 0:
color = "green" if run.quality_score >= 0.8 else "orange"
quality_html = f"""
<h2>质量评分</h2>
<div style="font-size:2rem;color:{color};font-weight:bold">{run.quality_score:.0%}</div>"""
# 重试历史卡片
retry_html = ""
if run.total_retry > 0:
retry_html = f"""
<h2>重试历史</h2>
<table border=1 cellpadding=4>
<tr><td>heal_retry</td><td>{run.heal_retry}</td></tr>
<tr><td>simple_retry</td><td>{run.simple_retry}</td></tr>
<tr><td>total_retry</td><td>{run.total_retry}</td></tr>
</table>"""
warn_html = ""
if run.quality_warn:
warn_html = f'<div style="background:#fff3cd;padding:1rem;margin:1rem 0">{run.quality_warn}</div>'
html = f"""<!DOCTYPE html>
<html><head><meta charset=utf-8><title>{run.program}</title>
<style>
body{{font-family:monospace;max-width:900px;margin:2rem auto}}
.pass{{background:#e6ffe6}}.fail{{background:#ffe6e6}}
pre{{background:#f0f0f0;padding:1rem}}
table{{border-collapse:collapse}} td,th{{padding:6px 12px}}
</style></head><body>
<h1>{run.program}</h1>
<pre>Status: {run.status} | Runner: {run.runner} | {run.fields_matched} matched | {run.duration_s:.0f}s</pre>
{warn_html}
<h2>字段比对</h2>
<table border=1 cellpadding=4>
<tr><th>Field</th><th>Status</th><th>COBOL</th><th>Java</th><th>Suggestion</th></tr>
{rows}</table>
{coverage_html}
{hina_html}
{quality_html}
{retry_html}
</body></html>"""
html = f"<!DOCTYPE html><html><head><meta charset=utf-8><title>{run.program}</title>" \
f"<style>body{{font-family:monospace;max-width:900px;margin:2rem auto}}" \
f".pass{{background:#e6ffe6}}.fail{{background:#ffe6e6}}pre{{background:#f0f0f0;padding:1rem}}" \
f"</style></head><body><h1>{run.program}</h1><pre>Status: {run.status} | " \
f"Runner: {run.runner} | {run.fields_matched} fields | {run.duration_s}s</pre>" \
f"<table border=1 cellpadding=4><tr><th>Field</th><th>Status</th><th>COBOL</th>" \
f"<th>Java</th><th>Suggestion</th></tr>{rows}</table></body></html>"
p.write_text(html)
return p
def generate_machine_json(self, run: VerificationRun, p: Path) -> Path:
d = {"program": run.program, "status": run.status, "exit_code": run.exit_code,
"timestamp": run.timestamp, "duration_s": run.duration_s, "runner": run.runner,
"branch_rate": run.branch_rate, "paragraph_rate": run.paragraph_rate,
"decision_rate": run.decision_rate, "quality_score": run.quality_score,
"hina_type": run.hina_type, "hina_confidence": run.hina_confidence,
"heal_retry": run.heal_retry, "simple_retry": run.simple_retry,
"total_retry": run.total_retry}
"timestamp": run.timestamp, "duration_s": run.duration_s, "runner": run.runner}
p.write_text(json.dumps(d))
return p
reset_task.py
-11
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@@ -1,11 +0,0 @@
import json
for tf_name in ["tasks/ec17bf32.json"]:
with open(tf_name) as f:
d = json.load(f)
d["status"] = "queued"
d.pop("result", None)
d.pop("fields", None)
d.pop("debug", None)
with open(tf_name, "w") as f:
json.dump(d, f)
print(f"{tf_name} reset to queued")
runners/__init__.py
-30
View File
@@ -1,31 +1 @@
"""编译运行引擎包
公开 API:
CobolRunner — COBOL 编译 + 运行（cobc）
NativeJavaRunner — Java 本地运行（mvn + java -jar）
SparkJavaRunner — Spark 运行（spark-submit）
DataWriter — 测试数据写入（二进制/JSON）
Runner — 抽象基类
BuildResult — 编译结果
RunResult — 运行结果
CoverageReport — 覆盖率报告
"""
from __future__ import annotations
from .runner import Runner, BuildResult, RunResult, CoverageReport
from .cobol_runner import CobolRunner
from .native_java_runner import NativeJavaRunner
from .spark_java_runner import SparkJavaRunner
from .data_writer import DataWriter
__all__ = [
"CobolRunner", # class
"NativeJavaRunner", # class
"SparkJavaRunner", # class
"DataWriter", # class
"Runner", # ABC
"BuildResult", # dataclass
"RunResult", # dataclass
"CoverageReport", # dataclass
]
runners/cobol_runner.py
+3 -5
View File
@@ -4,13 +4,11 @@ from runners.runner import BuildResult, RunResult
class CobolRunner:
def compile(self, src: str, dialect="ibm", gcov: bool = False) -> BuildResult:
def compile(self, src: str, dialect="ibm") -> BuildResult:
stem = Path(src).stem
out = str(Path(src).parent / stem)
cmd = ["cobc", "-x", f"-std={dialect}-strict", "-o", out, src]
if gcov:
cmd = ["cobc", "-x", f"-std={dialect}-strict", "--coverage", "-o", out, src]
p = subprocess.run(cmd, capture_output=True, text=True, timeout=30)
p = subprocess.run(["cobc", "-x", f"-std={dialect}-strict", "-o", out, src],
capture_output=True, text=True, timeout=30)
return BuildResult(success=p.returncode == 0, artifact_path=out, log=p.stdout + p.stderr)
def run(self, binary: str, input_path: str, output_path: str) -> RunResult:
storage/__init__.py
-17
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@@ -1,18 +1 @@
"""存储层包
公开 API:
DiskCache — 磁盘缓存（SHA256 key → JSON）
ReportStore — 报告历史存储（JSONL）
TestDataBundle — 测试数据文件路径管理
"""
from __future__ import annotations
from .store import DiskCache, ReportStore
from .bundle import TestDataBundle
__all__ = [
"DiskCache", # class
"ReportStore", # class
"TestDataBundle", # class
]
test-data/cobol/HINA001.cbl
-84
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@@ -1,84 +0,0 @@
* HINA001 - 1:1 マッチング
>>SOURCE FORMAT IS FREE
* 2入力ファイル(R01/R02)をキー一致でマージ
* 期待: 2ファイル, 3 IF, 6 分岐, ~5 段落
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA001.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT R01-FILE ASSIGN TO "R01.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
SELECT R02-FILE ASSIGN TO "R02.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
SELECT W01-FILE ASSIGN TO "W01.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
DATA DIVISION.
FILE SECTION.
FD R01-FILE.
01 R01-REC PIC X(30).
FD R02-FILE.
01 R02-REC PIC X(30).
FD W01-FILE.
01 W01-REC PIC X(60).
WORKING-STORAGE SECTION.
01 WS-R01-KEY PIC X(10).
01 WS-R02-KEY PIC X(10).
01 WS-R01-DATA PIC X(20).
01 WS-R02-DATA PIC X(20).
01 WS-EOF1 PIC X VALUE 'N'.
88 R01-EOF VALUE 'Y'.
01 WS-EOF2 PIC X VALUE 'N'.
88 R02-EOF VALUE 'Y'.
PROCEDURE DIVISION.
0000-MAIN.
OPEN INPUT R01-FILE R02-FILE.
OPEN OUTPUT W01-FILE.
PERFORM 1000-READ-R01.
PERFORM 2000-READ-R02.
PERFORM 3000-MATCH UNTIL R01-EOF AND R02-EOF.
CLOSE R01-FILE R02-FILE W01-FILE.
STOP RUN.
1000-READ-R01.
READ R01-FILE INTO R01-REC
AT END MOVE 'Y' TO WS-EOF1
NOT AT END PERFORM 1100-PARSE-R01.
1100-PARSE-R01.
MOVE R01-REC(1:10) TO WS-R01-KEY.
MOVE R01-REC(11:20) TO WS-R01-DATA.
2000-READ-R02.
READ R02-FILE INTO R02-REC
AT END MOVE 'Y' TO WS-EOF2
NOT AT END PERFORM 2100-PARSE-R02.
2100-PARSE-R02.
MOVE R02-REC(1:10) TO WS-R02-KEY.
MOVE R02-REC(11:20) TO WS-R02-DATA.
3000-MATCH.
IF R01-EOF THEN
PERFORM 4000-WRITE-R02-ONLY
PERFORM 2000-READ-R02
ELSE IF R02-EOF THEN
PERFORM 5000-WRITE-R01-ONLY
PERFORM 1000-READ-R01
ELSE IF WS-R01-KEY < WS-R02-KEY THEN
PERFORM 5000-WRITE-R01-ONLY
PERFORM 1000-READ-R01
ELSE IF WS-R01-KEY > WS-R02-KEY THEN
PERFORM 4000-WRITE-R02-ONLY
PERFORM 2000-READ-R02
ELSE
PERFORM 6000-WRITE-MATCH
PERFORM 1000-READ-R01
PERFORM 2000-READ-R02.
4000-WRITE-R02-ONLY.
STRING WS-R02-KEY WS-R02-DATA DELIMITED BY SIZE
INTO W01-REC.
WRITE W01-REC.
5000-WRITE-R01-ONLY.
STRING WS-R01-KEY WS-R01-DATA DELIMITED BY SIZE
INTO W01-REC.
WRITE W01-REC.
6000-WRITE-MATCH.
STRING WS-R01-KEY WS-R01-DATA WS-R02-DATA
DELIMITED BY SIZE INTO W01-REC.
WRITE W01-REC.
test-data/cobol/HINA004.cbl
-54
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@@ -1,54 +0,0 @@
* HINA004 - 編集出力(GETPUT)
>>SOURCE FORMAT IS FREE
* レイアウト編集 レコード入出力
* 期待: 2ファイル, 1 IF, 5 段落
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA004.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT IN-FILE ASSIGN TO "IN.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
SELECT OUT-FILE ASSIGN TO "OUT.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
DATA DIVISION.
FILE SECTION.
FD IN-FILE.
01 IN-REC.
05 IN-ID PIC X(05).
05 IN-NAME PIC X(20).
05 IN-AMT PIC 9(07)V99.
FD OUT-FILE.
01 OUT-REC PIC X(80).
WORKING-STORAGE SECTION.
01 WS-EOF PIC X VALUE 'N'.
88 WS-EOF-Y VALUE 'Y'.
01 WS-HEADER PIC X(80).
01 WS-DETAIL PIC X(80).
01 WS-LINE-CNT PIC 9(02).
PROCEDURE DIVISION.
0000-MAIN.
OPEN INPUT IN-FILE.
OPEN OUTPUT OUT-FILE.
MOVE "ID NAME AMOUNT" TO WS-HEADER.
WRITE OUT-REC FROM WS-HEADER.
MOVE 0 TO WS-LINE-CNT.
PERFORM 1000-READ.
PERFORM 2000-PROCESS UNTIL WS-EOF-Y.
CLOSE IN-FILE OUT-FILE.
STOP RUN.
1000-READ.
READ IN-FILE INTO IN-REC
AT END MOVE 'Y' TO WS-EOF-Y.
2000-PROCESS.
IF WS-LINE-CNT > 50 THEN
MOVE SPACES TO WS-DETAIL
STRING "--- PAGE BREAK ---"
DELIMITED BY SIZE INTO WS-DETAIL
WRITE OUT-REC FROM WS-DETAIL
MOVE 0 TO WS-LINE-CNT.
STRING IN-ID IN-NAME IN-AMT DELIMITED BY SIZE
INTO WS-DETAIL.
WRITE OUT-REC FROM WS-DETAIL.
ADD 1 TO WS-LINE-CNT.
PERFORM 1000-READ.
test-data/cobol/HINA005.cbl
-24
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@@ -1,24 +0,0 @@
* >>SOURCE FORMAT IS FREE
IDENTIFICATION DIVISION.
PROGRAM-ID. TEST.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC X(01).
01 WS-B PIC 9(05).
01 WS-C PIC X(20).
PROCEDURE DIVISION.
IF WS-A = 'A' THEN
MOVE 'HIGH' TO WS-C
IF WS-B > 1000 THEN
MOVE 'HIGH-1000' TO WS-C
ELSE
MOVE 'LOW-1000' TO WS-C
END-IF
ELSE IF WS-A = 'B' THEN
MOVE 'MED' TO WS-C
IF WS-B > 500 THEN
MOVE 'MED-500' TO WS-C
END-IF
ELSE
MOVE 'OTHER' TO WS-C.
GOBACK.
test-data/cobol/HINA006.cbl
-24
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@@ -1,24 +0,0 @@
* >>SOURCE FORMAT IS FREE
IDENTIFICATION DIVISION.
PROGRAM-ID. TEST.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC X(01).
01 WS-B PIC 9(05).
01 WS-C PIC X(20).
PROCEDURE DIVISION.
IF WS-A = 'A' THEN
MOVE 'HIGH' TO WS-C
IF WS-B > 1000 THEN
MOVE 'HIGH-1000' TO WS-C
ELSE
MOVE 'LOW-1000' TO WS-C
END-IF
ELSE IF WS-A = 'B' THEN
MOVE 'MED' TO WS-C
IF WS-B > 500 THEN
MOVE 'MED-500' TO WS-C
END-IF
ELSE
MOVE 'OTHER' TO WS-C.
GOBACK.
test-data/cobol/HINA007.cbl
-54
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@@ -1,54 +0,0 @@
* HINA007 - キーブレイク(集計)
>>SOURCE FORMAT IS FREE
* キー切替時の累計集計処理
* 期待: 2 IF, 1 PERFORM, 5 段落, キーブレイク有
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA007.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT IN-FILE ASSIGN TO "TRANS.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
SELECT OUT-FILE ASSIGN TO "SUM.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
DATA DIVISION.
FILE SECTION.
FD IN-FILE.
01 IN-REC.
05 IN-KEY PIC X(05).
05 IN-AMT PIC 9(07).
FD OUT-FILE.
01 OUT-REC PIC X(30).
WORKING-STORAGE SECTION.
01 WS-PREV-KEY PIC X(05).
01 WS-SUM PIC 9(10).
01 WS-EOF PIC X VALUE 'N'.
88 EOF-VALUE VALUE 'Y'.
01 WS-FIRST PIC X VALUE 'Y'.
88 FIRST-REC VALUE 'Y'.
PROCEDURE DIVISION.
0000-MAIN.
OPEN INPUT IN-FILE.
OPEN OUTPUT OUT-FILE.
PERFORM 1000-READ.
PERFORM 2000-PROCESS UNTIL EOF-VALUE.
PERFORM 3000-WRITE-BREAK.
CLOSE IN-FILE OUT-FILE.
STOP RUN.
1000-READ.
READ IN-FILE INTO IN-REC
AT END MOVE 'Y' TO WS-EOF.
2000-PROCESS.
IF FIRST-REC THEN
MOVE IN-KEY TO WS-PREV-KEY
MOVE 'N' TO WS-FIRST.
IF IN-KEY NOT = WS-PREV-KEY THEN
PERFORM 3000-WRITE-BREAK
MOVE IN-KEY TO WS-PREV-KEY
MOVE 0 TO WS-SUM.
ADD IN-AMT TO WS-SUM.
PERFORM 1000-READ.
3000-WRITE-BREAK.
STRING WS-PREV-KEY WS-SUM DELIMITED BY SIZE
INTO OUT-REC.
WRITE OUT-REC.
test-data/cobol/HINA013.cbl
-24
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@@ -1,24 +0,0 @@
* >>SOURCE FORMAT IS FREE
IDENTIFICATION DIVISION.
PROGRAM-ID. TEST.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC X(01).
01 WS-B PIC 9(05).
01 WS-C PIC X(20).
PROCEDURE DIVISION.
IF WS-A = 'A' THEN
MOVE 'HIGH' TO WS-C
IF WS-B > 1000 THEN
MOVE 'HIGH-1000' TO WS-C
ELSE
MOVE 'LOW-1000' TO WS-C
END-IF
ELSE IF WS-A = 'B' THEN
MOVE 'MED' TO WS-C
IF WS-B > 500 THEN
MOVE 'MED-500' TO WS-C
END-IF
ELSE
MOVE 'OTHER' TO WS-C.
GOBACK.
test-data/cobol/HINA024.cbl
-42
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@@ -1,42 +0,0 @@
* HINA024 - 内部テーブル検索(SEARCH ALL)
>>SOURCE FORMAT IS FREE
* OCCURS + SEARCH ALL によるテーブル検索
* 期待: SEARCH ALL, OCCURS, 2 IF, 5 段落
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA024.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-TABLE.
05 WS-ENTRY OCCURS 10 TIMES
ASCENDING KEY IS WS-ENTRY-ID
INDEXED BY WS-IDX.
10 WS-ENTRY-ID PIC 9(03).
10 WS-ENTRY-NAME PIC X(10).
01 WS-SEARCH-ID PIC 9(03).
01 WS-FOUND PIC X VALUE 'N'.
88 FOUND-YES VALUE 'Y'.
01 WS-RESULT PIC X(30).
PROCEDURE DIVISION.
0000-MAIN.
PERFORM 1000-INIT.
MOVE 7 TO WS-SEARCH-ID.
PERFORM 2000-SEARCH.
DISPLAY WS-RESULT.
MOVE 99 TO WS-SEARCH-ID.
PERFORM 2000-SEARCH.
DISPLAY WS-RESULT.
STOP RUN.
1000-INIT.
MOVE 1 TO WS-ENTRY-ID(1) MOVE "ALPHA" TO WS-ENTRY-NAME(1).
MOVE 3 TO WS-ENTRY-ID(2) MOVE "BETA" TO WS-ENTRY-NAME(2).
MOVE 5 TO WS-ENTRY-ID(3) MOVE "GAMMA" TO WS-ENTRY-NAME(3).
MOVE 7 TO WS-ENTRY-ID(4) MOVE "DELTA" TO WS-ENTRY-NAME(4).
MOVE 9 TO WS-ENTRY-ID(5) MOVE "EPSLN" TO WS-ENTRY-NAME(5).
2000-SEARCH.
SET WS-IDX TO 1.
SEARCH ALL WS-ENTRY
AT END
MOVE "NOT FOUND" TO WS-RESULT
WHEN WS-ENTRY-ID(WS-IDX) = WS-SEARCH-ID
STRING "FOUND=" WS-ENTRY-NAME(WS-IDX)
DELIMITED BY SIZE INTO WS-RESULT.
test-data/cobol/HINA025.cbl
-31
View File
@@ -1,31 +0,0 @@
* HINA025 - サブプログラムCALL
>>SOURCE FORMAT IS FREE
* CALL文によるサブプログラム呼び出し
* 期待: CALL文, LINKAGE SECTION, 2段落
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA025.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC 9(05) VALUE 100.
01 WS-B PIC 9(05) VALUE 200.
01 WS-RESULT PIC 9(06).
PROCEDURE DIVISION.
0000-MAIN.
CALL 'HINA025SUB' USING WS-A WS-B WS-RESULT.
DISPLAY "RESULT=" WS-RESULT.
CALL 'HINA025SUB' USING WS-B WS-A WS-RESULT.
DISPLAY "RESULT2=" WS-RESULT.
STOP RUN.
* サブプログラム(インライン)
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA025SUB.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-TEMP PIC 9(06).
LINKAGE SECTION.
01 X PIC 9(05).
01 Y PIC 9(05).
01 Z PIC 9(06).
PROCEDURE DIVISION USING X Y Z.
ADD X TO Y GIVING Z.
GOBACK.
test-data/cobol/HINA034.cbl
-39
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@@ -1,39 +0,0 @@
* HINA034 - SORT処理
>>SOURCE FORMAT IS FREE
* SORT文によるファイルソート
* 期待: SORT文, INPUT/OUTPUT PROCEDURE
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA034.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT IN-FILE ASSIGN TO "SORTIN.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
SELECT OUT-FILE ASSIGN TO "SORTOUT.DAT"
ORGANIZATION IS LINE SEQUENTIAL.
SELECT WORK-FILE ASSIGN TO "SORTWORK".
DATA DIVISION.
FILE SECTION.
FD IN-FILE.
01 IN-REC.
05 IN-KEY PIC 9(05).
05 IN-DATA PIC X(20).
FD OUT-FILE.
01 OUT-REC.
05 OUT-KEY PIC 9(05).
05 OUT-DATA PIC X(20).
SD WORK-FILE.
01 WORK-REC.
05 WORK-KEY PIC 9(05).
05 WORK-DATA PIC X(20).
WORKING-STORAGE SECTION.
01 WS-CNT PIC 9(05).
01 WS-MAX PIC 9(05).
PROCEDURE DIVISION.
0000-MAIN.
SORT WORK-FILE
ON ASCENDING KEY WORK-KEY
USING IN-FILE
GIVING OUT-FILE.
DISPLAY "SORT COMPLETE".
STOP RUN.
test-data/cobol/HINA101.cbl
-23
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@@ -1,23 +0,0 @@
* HINA101 - EXEC SQL(SELECT条件)
>>SOURCE FORMAT IS FREE
* EXEC SQL 埋め込みSQL
* 期待: L1キーワード "EXEC SQL" で判定
IDENTIFICATION DIVISION.
PROGRAM-ID. HINA101.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-CUST-ID PIC X(10).
01 WS-CUST-NAME PIC X(30).
01 WS-SQLCODE PIC S9(09) COMP.
PROCEDURE DIVISION.
0000-MAIN.
EXEC SQL
SELECT CUST_NAME INTO :WS-CUST-NAME
FROM CUSTOMERS
WHERE CUST_ID = :WS-CUST-ID
END-EXEC.
IF SQLCODE = 0 THEN
DISPLAY "FOUND:" WS-CUST-NAME
ELSE
DISPLAY "NOT FOUND".
STOP RUN.
test-data/cobol/category_cics/CI01_CICS.cbl
-31
View File
@@ -1,31 +0,0 @@
* ==== TYPE: CI01 CICS ====
*> FEATURE: DFHCOMMAREA + MAP simulation
*> NOTE: CICS keywords marked with *> not for compilation
IDENTIFICATION DIVISION.
PROGRAM-ID. CI01.
ENVIRONMENT DIVISION.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-COMMAREA.
05 WS-CA-LENGTH PIC S9(4) COMP.
05 WS-CA-DATA PIC X(100).
01 WS-MAP-RECV.
05 WS-MAP-INPUT PIC X(50).
01 WS-MAP-SEND.
05 WS-MAP-OUTPUT PIC X(50).
01 WS-RESPONSE PIC S9(8) COMP.
PROCEDURE DIVISION.
*> EXEC CICS RECEIVE MAP('MAP01')
*> INTO(WS-MAP-RECV)
*> RESP(WS-RESPONSE)
*> END-EXEC.
DISPLAY 'RECEIVED MAP'.
*> EXEC CICS SEND MAP('MAP01')
*> FROM(WS-MAP-SEND)
*> RESP(WS-RESPONSE)
*> END-EXEC.
DISPLAY 'SENT MAP'.
*> EXEC CICS RETURN
*> COMMAREA(WS-COMMAREA)
*> END-EXEC.
STOP RUN.
test-data/cobol/category_csv/CV01_CSV_NO_NEWLINE.cbl
-24
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@@ -1,24 +0,0 @@
* ==== TYPE: CV01 CSV(NO NEWLINE) ====
* FEATURE: STRING concatenation without newline
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. CV01.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-FIELD1 PIC X(10) VALUE 'ALPHA'.
01 WS-FIELD2 PIC X(10) VALUE 'BETA'.
01 WS-FIELD3 PIC X(10) VALUE 'GAMMA'.
01 WS-CSV-LINE PIC X(100).
01 WS-PTR PIC 9(3) VALUE 1.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
MOVE 1 TO WS-PTR.
STRING WS-FIELD1 DELIMITED BY SPACES
',' DELIMITED BY SIZE
WS-FIELD2 DELIMITED BY SPACES
',' DELIMITED BY SIZE
WS-FIELD3 DELIMITED BY SPACES
INTO WS-CSV-LINE
WITH POINTER WS-PTR.
DISPLAY 'CSV: ' WS-CSV-LINE.
STOP RUN.
test-data/cobol/category_csv/CV02_CSV_WITH_NEWLINE.cbl
-25
View File
@@ -1,25 +0,0 @@
* ==== TYPE: CV02 CSV(WITH NEWLINE) ====
* FEATURE: INSPECT REPLACING for newline handling
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. CV02.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-LINE PIC X(100) VALUE
'FIELD1,FIELD2,FIELD3'.
01 WS-PTR PIC 9(3) VALUE 1.
01 WS-COM-COUNT PIC 9(3) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
INSPECT WS-LINE TALLYING WS-COM-COUNT
FOR ALL ','.
DISPLAY 'COMMA COUNT: ' WS-COM-COUNT.
INSPECT WS-LINE REPLACING ALL ',' BY '|'.
DISPLAY 'PIPE LINE: ' WS-LINE.
MOVE 1 TO WS-PTR.
STRING WS-LINE DELIMITED BY SPACES
';' DELIMITED BY SIZE
INTO WS-LINE
WITH POINTER WS-PTR.
DISPLAY 'CSV+TERM: ' WS-LINE.
STOP RUN.
test-data/cobol/category_csv/CV03_ASCII_EBCDIC.cbl
-27
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@@ -1,27 +0,0 @@
* ==== TYPE: CV03 ASCII-EBCDIC ====
* FEATURE: ASCII to EBCDIC conversion simulation
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. CV03.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-ASCII-DATA PIC X(10) VALUE 'ABCDEF0123'.
01 WS-EBCDIC-DATA PIC X(10).
01 WS-I PIC 9(2) VALUE 1.
01 WS-CHAR PIC X(1).
PROCEDURE DIVISION.
MAIN-PROCEDURE.
MOVE SPACES TO WS-EBCDIC-DATA.
PERFORM VARYING WS-I FROM 1 BY 1 UNTIL WS-I > 10
MOVE WS-ASCII-DATA(WS-I:1) TO WS-CHAR
IF WS-CHAR >= 'A' AND <= 'Z'
DISPLAY 'ALPHA AT ' WS-I
ELSE IF WS-CHAR >= '0' AND <= '9'
DISPLAY 'DIGIT AT ' WS-I
ELSE
DISPLAY 'OTHER AT ' WS-I
END-IF
END-PERFORM.
MOVE WS-ASCII-DATA TO WS-EBCDIC-DATA.
DISPLAY 'EBCDIC: ' WS-EBCDIC-DATA.
STOP RUN.
test-data/cobol/category_db/DB01_SELECT_UPDATE.cbl
-34
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@@ -1,34 +0,0 @@
* ==== TYPE: DB01 SELECT-UPDATE ====
*> FEATURE: EXEC SQL + INSERT/UPDATE simulation
*> NOTE: SQL keywords marked with *> not for compilation
IDENTIFICATION DIVISION.
PROGRAM-ID. DB01.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-EMP-ID PIC X(10).
01 WS-EMP-NAME PIC X(30).
01 WS-EMP-SALARY PIC 9(7)V99.
01 WS-SQLCODE PIC S9(4) COMP.
01 WS-SQLMSG PIC X(50).
PROCEDURE DIVISION.
*> EXEC SQL
*> SELECT EMP_NAME, EMP_SALARY
*> INTO :WS-EMP-NAME, :WS-EMP-SALARY
*> FROM EMPLOYEE
*> WHERE EMP_ID = :WS-EMP-ID
*> END-EXEC.
DISPLAY 'SELECTED: ' WS-EMP-NAME.
*> EXEC SQL
*> UPDATE EMPLOYEE
*> SET EMP_SALARY = :WS-EMP-SALARY
*> WHERE EMP_ID = :WS-EMP-ID
*> END-EXEC.
DISPLAY 'UPDATED: ' WS-EMP-ID.
*> EXEC SQL
*> INSERT INTO EMPLOYEE
*> (EMP_ID, EMP_NAME, EMP_SALARY)
*> VALUES (:WS-EMP-ID, :WS-EMP-NAME,
*> :WS-EMP-SALARY)
*> END-EXEC.
DISPLAY 'INSERTED: ' WS-EMP-ID.
STOP RUN.
test-data/cobol/category_division/DV01_DIVIDE_50.cbl
-22
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@@ -1,22 +0,0 @@
* ==== TYPE: DV01 DIVIDE(50) ====
* FEATURE: DIVIDE 50 INTO
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. DV01.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-VALUE PIC 9(5) VALUE 10000.
01 WS-RESULT PIC 9(5) VALUE 0.
01 WS-REMAIND PIC 9(5) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
DIVIDE 50 INTO WS-VALUE GIVING WS-RESULT
REMAINDER WS-REMAIND.
DISPLAY 'VALUE: ' WS-VALUE ' RESULT: ' WS-RESULT
' REM: ' WS-REMAIND.
IF WS-REMAIND = 0
DISPLAY 'DIVISIBLE BY 50'
ELSE
DISPLAY 'NOT DIVISIBLE BY 50'
END-IF.
STOP RUN.
test-data/cobol/category_division/DV02_DIVIDE_25.cbl
-22
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@@ -1,22 +0,0 @@
* ==== TYPE: DV02 DIVIDE(25) ====
* FEATURE: DIVIDE 25 INTO
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. DV02.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-VALUE PIC 9(5) VALUE 5000.
01 WS-RESULT PIC 9(5) VALUE 0.
01 WS-REMAIND PIC 9(5) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
DIVIDE 25 INTO WS-VALUE GIVING WS-RESULT
REMAINDER WS-REMAIND.
DISPLAY 'VALUE: ' WS-VALUE ' RESULT: ' WS-RESULT
' REM: ' WS-REMAIND.
IF WS-REMAIND = 0
DISPLAY 'DIVISIBLE BY 25'
ELSE
DISPLAY 'NOT DIVISIBLE BY 25'
END-IF.
STOP RUN.
test-data/cobol/category_division/DV03_DIVIDE_100.cbl
-22
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@@ -1,22 +0,0 @@
* ==== TYPE: DV03 DIVIDE(100) ====
* FEATURE: DIVIDE 100 INTO
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. DV03.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-VALUE PIC 9(5) VALUE 20000.
01 WS-RESULT PIC 9(5) VALUE 0.
01 WS-REMAIND PIC 9(5) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
DIVIDE 100 INTO WS-VALUE GIVING WS-RESULT
REMAINDER WS-REMAIND.
DISPLAY 'VALUE: ' WS-VALUE ' RESULT: ' WS-RESULT
' REM: ' WS-REMAIND.
IF WS-REMAIND = 0
DISPLAY 'DIVISIBLE BY 100'
ELSE
DISPLAY 'NOT DIVISIBLE BY 100'
END-IF.
STOP RUN.
test-data/cobol/category_matching/MT01_1TO1.cbl
-43
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@@ -1,43 +0,0 @@
* ==== TYPE: MT01 MATCHING(1:1) ====
* FEATURE: 2 input files, IF KEY = compare, 3-way IF
* BRANCHES: 4, DECISIONS: 2
IDENTIFICATION DIVISION.
PROGRAM-ID. MT01.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-A ASSIGN TO 'FILEA.DAT'.
SELECT FILE-B ASSIGN TO 'FILEB.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-A.
01 REC-A PIC X(80).
FD FILE-B.
01 REC-B PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-A PIC X(10).
01 WS-KEY-B PIC X(10).
01 WS-EOF-A PIC X VALUE 'N'.
01 WS-EOF-B PIC X VALUE 'N'.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT FILE-A FILE-B.
READ FILE-A INTO REC-A
AT END MOVE 'Y' TO WS-EOF-A.
READ FILE-B INTO REC-B
AT END MOVE 'Y' TO WS-EOF-B.
PERFORM UNTIL WS-EOF-A = 'Y' OR WS-EOF-B = 'Y'
IF WS-KEY-A = WS-KEY-B
DISPLAY 'MATCH: ' REC-A(1:50)
READ FILE-A AT END MOVE 'Y' TO WS-EOF-A
READ FILE-B AT END MOVE 'Y' TO WS-EOF-B
ELSE IF WS-KEY-A < WS-KEY-B
DISPLAY 'UNMATCH-A: ' REC-A(1:50)
READ FILE-A AT END MOVE 'Y' TO WS-EOF-A
ELSE
DISPLAY 'UNMATCH-B: ' REC-B(1:50)
READ FILE-B AT END MOVE 'Y' TO WS-EOF-B
END-IF
END-PERFORM.
CLOSE FILE-A FILE-B.
STOP RUN.
test-data/cobol/category_matching/MT02_1TON.cbl
-44
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@@ -1,44 +0,0 @@
* ==== TYPE: MT02 MATCHING(1:N) ====
* FEATURE: 1 master file, N transaction files
* BRANCHES: 6, DECISIONS: 3
IDENTIFICATION DIVISION.
PROGRAM-ID. MT02.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT MASTER-FILE ASSIGN TO 'MASTER.DAT'.
SELECT TRANS-FILE ASSIGN TO 'TRANS.DAT'.
DATA DIVISION.
FILE SECTION.
FD MASTER-FILE.
01 MASTER-REC PIC X(80).
FD TRANS-FILE.
01 TRANS-REC PIC X(80).
WORKING-STORAGE SECTION.
01 WS-MAST-KEY PIC X(10).
01 WS-TRAN-KEY PIC X(10).
01 WS-MAST-EOF PIC X VALUE 'N'.
01 WS-TRAN-EOF PIC X VALUE 'N'.
01 WS-MATCH-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT MASTER-FILE TRANS-FILE.
READ MASTER-FILE INTO MASTER-REC
AT END MOVE 'Y' TO WS-MAST-EOF.
READ TRANS-FILE INTO TRANS-REC
AT END MOVE 'Y' TO WS-TRAN-EOF.
PERFORM UNTIL WS-MAST-EOF = 'Y' OR WS-TRAN-EOF = 'Y'
IF WS-MAST-KEY = WS-TRAN-KEY
ADD 1 TO WS-MATCH-COUNT
DISPLAY 'MATCH: ' TRANS-REC(1:50)
READ TRANS-FILE AT END MOVE 'Y' TO WS-TRAN-EOF
ELSE IF WS-MAST-KEY < WS-TRAN-KEY
DISPLAY 'MASTER UNMATCHED: ' MASTER-REC(1:40)
READ MASTER-FILE AT END MOVE 'Y' TO WS-MAST-EOF
ELSE
DISPLAY 'TRAN UNMATCHED: ' TRANS-REC(1:40)
READ TRANS-FILE AT END MOVE 'Y' TO WS-TRAN-EOF
END-IF
END-PERFORM.
CLOSE MASTER-FILE TRANS-FILE.
STOP RUN.
test-data/cobol/category_matching/MT03_NTO1.cbl
-44
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@@ -1,44 +0,0 @@
* ==== TYPE: MT03 MATCHING(N:1) ====
* FEATURE: N master files, 1 transaction file
* BRANCHES: 6, DECISIONS: 3
IDENTIFICATION DIVISION.
PROGRAM-ID. MT03.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-M ASSIGN TO 'FILEM.DAT'.
SELECT FILE-T ASSIGN TO 'FILET.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-M.
01 REC-M PIC X(80).
FD FILE-T.
01 REC-T PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-M PIC X(10).
01 WS-KEY-T PIC X(10).
01 WS-M-EOF PIC X VALUE 'N'.
01 WS-T-EOF PIC X VALUE 'N'.
01 WS-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT FILE-M FILE-T.
READ FILE-M INTO REC-M
AT END MOVE 'Y' TO WS-M-EOF.
READ FILE-T INTO REC-T
AT END MOVE 'Y' TO WS-T-EOF.
PERFORM UNTIL WS-M-EOF = 'Y' OR WS-T-EOF = 'Y'
IF WS-KEY-M = WS-KEY-T
ADD 1 TO WS-COUNT
DISPLAY 'MATCHED: ' REC-M(1:50)
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF
ELSE IF WS-KEY-M < WS-KEY-T
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF
ELSE
DISPLAY 'TRAN ONLY: ' REC-T(1:50)
READ FILE-T AT END MOVE 'Y' TO WS-T-EOF
END-IF
END-PERFORM.
DISPLAY 'TOTAL MATCHED: ' WS-COUNT.
CLOSE FILE-M FILE-T.
STOP RUN.
test-data/cobol/category_matching/MT16_TWO_STAGE_1TO1.cbl
-64
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@@ -1,64 +0,0 @@
* ==== TYPE: MT16 TWO-STAGE MATCHING(1:1) ====
* FEATURE: 1:1 -> intermediate file -> re-match
* BRANCHES: 8, DECISIONS: 4
IDENTIFICATION DIVISION.
PROGRAM-ID. MT16.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-A ASSIGN TO 'FILEA.DAT'.
SELECT FILE-B ASSIGN TO 'FILEB.DAT'.
SELECT FILE-C ASSIGN TO 'FILEC.DAT'.
SELECT INT-FILE ASSIGN TO 'INTERM.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-A.
01 REC-A PIC X(80).
FD FILE-B.
01 REC-B PIC X(80).
FD FILE-C.
01 REC-C PIC X(80).
FD INT-FILE.
01 INT-REC PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-A PIC X(10).
01 WS-KEY-B PIC X(10).
01 WS-KEY-C PIC X(10).
01 WS-EOF-A PIC X VALUE 'N'.
01 WS-EOF-B PIC X VALUE 'N'.
01 WS-EOF-I PIC X VALUE 'N'.
PROCEDURE DIVISION.
STAGE-1.
OPEN INPUT FILE-A FILE-B.
OPEN OUTPUT INT-FILE.
READ FILE-A AT END MOVE 'Y' TO WS-EOF-A.
READ FILE-B AT END MOVE 'Y' TO WS-EOF-B.
PERFORM UNTIL WS-EOF-A = 'Y' OR WS-EOF-B = 'Y'
IF WS-KEY-A = WS-KEY-B
WRITE INT-REC FROM REC-A
READ FILE-A AT END MOVE 'Y' TO WS-EOF-A
READ FILE-B AT END MOVE 'Y' TO WS-EOF-B
ELSE IF WS-KEY-A < WS-KEY-B
READ FILE-A AT END MOVE 'Y' TO WS-EOF-A
ELSE
READ FILE-B AT END MOVE 'Y' TO WS-EOF-B
END-IF
END-PERFORM.
CLOSE FILE-A FILE-B INT-FILE.
STAGE-2.
OPEN INPUT INT-FILE FILE-C.
READ INT-FILE AT END MOVE 'Y' TO WS-EOF-I.
READ FILE-C AT END MOVE 'Y' TO WS-EOF-A.
PERFORM UNTIL WS-EOF-I = 'Y' OR WS-EOF-A = 'Y'
IF WS-KEY-C = WS-KEY-A
DISPLAY 'FINAL MATCH'
READ INT-FILE AT END MOVE 'Y' TO WS-EOF-I
READ FILE-C AT END MOVE 'Y' TO WS-EOF-A
ELSE IF WS-KEY-C < WS-KEY-A
READ FILE-C AT END MOVE 'Y' TO WS-EOF-A
ELSE
READ INT-FILE AT END MOVE 'Y' TO WS-EOF-I
END-IF
END-PERFORM.
CLOSE INT-FILE FILE-C.
STOP RUN.
test-data/cobol/category_matching/MT17_TWO_STAGE_NTO1.cbl
-55
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@@ -1,55 +0,0 @@
* ==== TYPE: MT17 TWO-STAGE MATCHING(N:1) ====
* FEATURE: N:1 -> intermediate file -> re-match
* BRANCHES: 8, DECISIONS: 4
IDENTIFICATION DIVISION.
PROGRAM-ID. MT17.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-X ASSIGN TO 'FILEX.DAT'.
SELECT FILE-Y ASSIGN TO 'FILEY.DAT'.
SELECT INT-FILE ASSIGN TO 'INTERM.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-X.
01 REC-X PIC X(80).
FD FILE-Y.
01 REC-Y PIC X(80).
FD INT-FILE.
01 INT-REC PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-X PIC X(10).
01 WS-KEY-Y PIC X(10).
01 WS-EOF-X PIC X VALUE 'N'.
01 WS-EOF-Y PIC X VALUE 'N'.
01 WS-EOF-I PIC X VALUE 'N'.
01 WS-INT-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
STAGE-1.
OPEN INPUT FILE-X FILE-Y.
OPEN OUTPUT INT-FILE.
READ FILE-X AT END MOVE 'Y' TO WS-EOF-X.
READ FILE-Y AT END MOVE 'Y' TO WS-EOF-Y.
PERFORM UNTIL WS-EOF-X = 'Y' OR WS-EOF-Y = 'Y'
IF WS-KEY-X = WS-KEY-Y
WRITE INT-REC FROM REC-Y
READ FILE-Y AT END MOVE 'Y' TO WS-EOF-Y
ELSE IF WS-KEY-X < WS-KEY-Y
READ FILE-X AT END MOVE 'Y' TO WS-EOF-X
ELSE
READ FILE-Y AT END MOVE 'Y' TO WS-EOF-Y
END-IF
END-PERFORM.
CLOSE FILE-X FILE-Y INT-FILE.
STAGE-2.
OPEN INPUT INT-FILE.
OPEN OUTPUT FILE-X.
READ INT-FILE AT END MOVE 'Y' TO WS-EOF-I.
PERFORM UNTIL WS-EOF-I = 'Y'
ADD 1 TO WS-INT-COUNT
WRITE REC-X FROM INT-REC
READ INT-FILE AT END MOVE 'Y' TO WS-EOF-I
END-PERFORM.
DISPLAY 'INT RECORDS: ' WS-INT-COUNT.
CLOSE INT-FILE FILE-X.
STOP RUN.
test-data/cobol/category_matching/MT18_MN_TO_M.cbl
-42
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@@ -1,42 +0,0 @@
* ==== TYPE: MT18 MATCHING(M:N -> M) ====
* FEATURE: M:N combination, output M records
* BRANCHES: 6, DECISIONS: 3
IDENTIFICATION DIVISION.
PROGRAM-ID. MT18.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-M ASSIGN TO 'FILEM.DAT'.
SELECT FILE-N ASSIGN TO 'FILEN.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-M.
01 REC-M PIC X(80).
FD FILE-N.
01 REC-N PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-M PIC X(10).
01 WS-KEY-N PIC X(10).
01 WS-M-EOF PIC X VALUE 'N'.
01 WS-N-EOF PIC X VALUE 'N'.
01 WS-M-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT FILE-M FILE-N.
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF.
READ FILE-N AT END MOVE 'Y' TO WS-N-EOF.
PERFORM UNTIL WS-M-EOF = 'Y' OR WS-N-EOF = 'Y'
IF WS-KEY-M = WS-KEY-N
ADD 1 TO WS-M-COUNT
DISPLAY 'M-OUT: ' REC-M(1:50)
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF
ELSE IF WS-KEY-M < WS-KEY-N
DISPLAY 'M-ONLY: ' REC-M(1:50)
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF
ELSE
READ FILE-N AT END MOVE 'Y' TO WS-N-EOF
END-IF
END-PERFORM.
DISPLAY 'M RECORDS OUT: ' WS-M-COUNT.
CLOSE FILE-M FILE-N.
STOP RUN.
test-data/cobol/category_matching/MT19_MN_TO_N.cbl
-42
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@@ -1,42 +0,0 @@
* ==== TYPE: MT19 MATCHING(M:N -> N) ====
* FEATURE: M:N combination, output N records
* BRANCHES: 6, DECISIONS: 3
IDENTIFICATION DIVISION.
PROGRAM-ID. MT19.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-M ASSIGN TO 'FILEM.DAT'.
SELECT FILE-N ASSIGN TO 'FILEN.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-M.
01 REC-M PIC X(80).
FD FILE-N.
01 REC-N PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-M PIC X(10).
01 WS-KEY-N PIC X(10).
01 WS-M-EOF PIC X VALUE 'N'.
01 WS-N-EOF PIC X VALUE 'N'.
01 WS-N-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT FILE-M FILE-N.
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF.
READ FILE-N AT END MOVE 'Y' TO WS-N-EOF.
PERFORM UNTIL WS-M-EOF = 'Y' OR WS-N-EOF = 'Y'
IF WS-KEY-M = WS-KEY-N
ADD 1 TO WS-N-COUNT
DISPLAY 'N-OUT: ' REC-N(1:50)
READ FILE-N AT END MOVE 'Y' TO WS-N-EOF
ELSE IF WS-KEY-M < WS-KEY-N
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF
ELSE
DISPLAY 'N-ONLY: ' REC-N(1:50)
READ FILE-N AT END MOVE 'Y' TO WS-N-EOF
END-IF
END-PERFORM.
DISPLAY 'N RECORDS OUT: ' WS-N-COUNT.
CLOSE FILE-M FILE-N.
STOP RUN.
test-data/cobol/category_matching/MT20_MN_TO_MXN.cbl
-48
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@@ -1,48 +0,0 @@
* ==== TYPE: MT20 MATCHING(M:N -> MxN) ====
* FEATURE: M:N Cartesian product
* BRANCHES: 8, DECISIONS: 4
IDENTIFICATION DIVISION.
PROGRAM-ID. MT20.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-M ASSIGN TO 'FILEM.DAT'.
SELECT FILE-N ASSIGN TO 'FILEN.DAT'.
SELECT FILE-O ASSIGN TO 'FILEO.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-M.
01 REC-M PIC X(80).
FD FILE-N.
01 REC-N PIC X(80).
FD FILE-O.
01 REC-O PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-M PIC X(10).
01 WS-KEY-N PIC X(10).
01 WS-M-EOF PIC X VALUE 'N'.
01 WS-N-EOF PIC X VALUE 'N'.
01 WS-PROD-COUNT PIC 9(6) VALUE 0.
01 WS-SAVE-KEY PIC X(10).
01 WS-SAVE-REC PIC X(80).
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT FILE-M FILE-N.
OPEN OUTPUT FILE-O.
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF.
PERFORM UNTIL WS-M-EOF = 'Y'
MOVE WS-KEY-M TO WS-SAVE-KEY
MOVE REC-M TO WS-SAVE-REC
READ FILE-N AT END MOVE 'Y' TO WS-N-EOF
PERFORM UNTIL WS-N-EOF = 'Y'
IF WS-KEY-N = WS-SAVE-KEY
ADD 1 TO WS-PROD-COUNT
WRITE REC-O FROM WS-SAVE-REC
END-IF
READ FILE-N AT END MOVE 'Y' TO WS-N-EOF
END-PERFORM
READ FILE-M AT END MOVE 'Y' TO WS-M-EOF
END-PERFORM.
DISPLAY 'CARTESIAN PRODUCT COUNT: ' WS-PROD-COUNT.
CLOSE FILE-M FILE-N FILE-O.
STOP RUN.
test-data/cobol/category_matching/MT32_MIXED_SAME_KEY.cbl
-47
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@@ -1,47 +0,0 @@
* ==== TYPE: MT32 MIXED MATCHING(SAME KEY) ====
* FEATURE: 1:N + same key mixed
* BRANCHES: 8, DECISIONS: 4
IDENTIFICATION DIVISION.
PROGRAM-ID. MT32.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-P ASSIGN TO 'FILEP.DAT'.
SELECT FILE-Q ASSIGN TO 'FILEQ.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-P.
01 REC-P PIC X(80).
FD FILE-Q.
01 REC-Q PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-P PIC X(10).
01 WS-KEY-Q PIC X(10).
01 WS-P-EOF PIC X VALUE 'N'.
01 WS-Q-EOF PIC X VALUE 'N'.
01 WS-PREV-KEY PIC X(10) VALUE SPACES.
01 WS-MIXED-FLAG PIC X VALUE 'N'.
01 WS-GROUP-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT FILE-P FILE-Q.
READ FILE-P AT END MOVE 'Y' TO WS-P-EOF.
READ FILE-Q AT END MOVE 'Y' TO WS-Q-EOF.
PERFORM UNTIL WS-P-EOF = 'Y' OR WS-Q-EOF = 'Y'
IF WS-KEY-P = WS-KEY-Q
IF WS-PREV-KEY NOT = WS-KEY-P
MOVE 'Y' TO WS-MIXED-FLAG
MOVE WS-KEY-P TO WS-PREV-KEY
END-IF
ADD 1 TO WS-GROUP-COUNT
READ FILE-P AT END MOVE 'Y' TO WS-P-EOF
READ FILE-Q AT END MOVE 'Y' TO WS-Q-EOF
ELSE IF WS-KEY-P < WS-KEY-Q
READ FILE-P AT END MOVE 'Y' TO WS-P-EOF
ELSE
READ FILE-Q AT END MOVE 'Y' TO WS-Q-EOF
END-IF
END-PERFORM.
DISPLAY 'MIXED GROUPS: ' WS-GROUP-COUNT.
CLOSE FILE-P FILE-Q.
STOP RUN.
test-data/cobol/category_matching/MT33_MIXED_DIFF_KEY.cbl
-45
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@@ -1,45 +0,0 @@
* ==== TYPE: MT33 MIXED MATCHING(DIFF KEY) ====
* FEATURE: 1:N + different key mixed
* BRANCHES: 8, DECISIONS: 4
IDENTIFICATION DIVISION.
PROGRAM-ID. MT33.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-R ASSIGN TO 'FILER.DAT'.
SELECT FILE-S ASSIGN TO 'FILES.DAT'.
DATA DIVISION.
FILE SECTION.
FD FILE-R.
01 REC-R PIC X(80).
FD FILE-S.
01 REC-S PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY-R PIC X(10).
01 WS-KEY-S PIC X(10).
01 WS-ALT-KEY PIC X(10).
01 WS-R-EOF PIC X VALUE 'N'.
01 WS-S-EOF PIC X VALUE 'N'.
01 WS-DIFF-FLAG PIC X VALUE 'N'.
01 WS-CROSS-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT FILE-R FILE-S.
READ FILE-R AT END MOVE 'Y' TO WS-R-EOF.
READ FILE-S AT END MOVE 'Y' TO WS-S-EOF.
PERFORM UNTIL WS-R-EOF = 'Y' OR WS-S-EOF = 'Y'
MOVE WS-KEY-R TO WS-ALT-KEY
IF WS-KEY-R = WS-KEY-S
ADD 1 TO WS-CROSS-COUNT
MOVE 'Y' TO WS-DIFF-FLAG
READ FILE-R AT END MOVE 'Y' TO WS-R-EOF
READ FILE-S AT END MOVE 'Y' TO WS-S-EOF
ELSE IF WS-ALT-KEY < WS-KEY-S
READ FILE-R AT END MOVE 'Y' TO WS-R-EOF
ELSE
READ FILE-S AT END MOVE 'Y' TO WS-S-EOF
END-IF
END-PERFORM.
DISPLAY 'CROSS MATCHES: ' WS-CROSS-COUNT.
CLOSE FILE-R FILE-S.
STOP RUN.
test-data/cobol/category_sort/ST01_SORT.cbl
-38
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@@ -1,38 +0,0 @@
* ==== TYPE: ST01 SORT ====
* FEATURE: SORT USING/GIVING ascending + INPUT PROCEDURE
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. ST01.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT IN-FILE ASSIGN TO 'INDATA.DAT'.
SELECT OUT-FILE ASSIGN TO 'OUTDATA.DAT'.
SELECT SORT-FILE ASSIGN TO 'SORTWORK'.
DATA DIVISION.
FILE SECTION.
FD IN-FILE.
01 IN-REC PIC X(80).
FD OUT-FILE.
01 OUT-REC PIC X(80).
SD SORT-FILE.
01 SORT-REC.
05 SORT-KEY PIC X(10).
05 SORT-DATA PIC X(70).
WORKING-STORAGE SECTION.
01 WS-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
SORT SORT-FILE
ON ASCENDING KEY SORT-KEY
USING IN-FILE
INPUT PROCEDURE IS INPUT-FILTER
GIVING OUT-FILE.
DISPLAY 'SORT COMPLETE'.
STOP RUN.
INPUT-FILTER SECTION.
INPUT-FILTER-PROC.
RETURN SORT-FILE INTO SORT-REC
AT END DISPLAY 'END OF INPUT'.
ADD 1 TO WS-COUNT.
DISPLAY 'SORTED REC: ' SORT-REC(1:30).
test-data/cobol/category_sort/ST02_MERGE.cbl
-32
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@@ -1,32 +0,0 @@
* ==== TYPE: ST02 MERGE ====
* FEATURE: MERGE 2 files into 1
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. ST02.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT FILE-1 ASSIGN TO 'FILE1.DAT'.
SELECT FILE-2 ASSIGN TO 'FILE2.DAT'.
SELECT FILE-O ASSIGN TO 'FILEO.DAT'.
SELECT MERGE-FILE ASSIGN TO 'MERGWORK'.
DATA DIVISION.
FILE SECTION.
FD FILE-1.
01 REC-1 PIC X(80).
FD FILE-2.
01 REC-2 PIC X(80).
FD FILE-O.
01 REC-O PIC X(80).
SD MERGE-FILE.
01 MERGE-REC.
05 MERGE-KEY PIC X(10).
05 MERGE-DATA PIC X(70).
PROCEDURE DIVISION.
MAIN-PROCEDURE.
MERGE MERGE-FILE
ON ASCENDING KEY MERGE-KEY
USING FILE-1 FILE-2
GIVING FILE-O.
DISPLAY 'MERGE COMPLETE'.
STOP RUN.
test-data/cobol/category_validation/VL01_CHECK_WITH_DUP.cbl
-39
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@@ -1,39 +0,0 @@
* ==== TYPE: VL01 VALIDATION(WITH DUP) ====
* FEATURE: Duplicate detection with WS-PREV-KEY
* BRANCHES: 4, DECISIONS: 2
IDENTIFICATION DIVISION.
PROGRAM-ID. VL01.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT IN-FILE ASSIGN TO 'INDATA.DAT'.
DATA DIVISION.
FILE SECTION.
FD IN-FILE.
01 IN-REC PIC X(80).
WORKING-STORAGE SECTION.
01 WS-KEY PIC X(10).
01 WS-PREV-KEY PIC X(10) VALUE SPACES.
01 WS-EOF PIC X VALUE 'N'.
01 WS-DUP-FLAG PIC X VALUE 'N'.
01 WS-REC-COUNT PIC 9(4) VALUE 0.
01 WS-DUP-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT IN-FILE.
READ IN-FILE AT END MOVE 'Y' TO WS-EOF.
PERFORM UNTIL WS-EOF = 'Y'
ADD 1 TO WS-REC-COUNT
IF WS-KEY = WS-PREV-KEY
ADD 1 TO WS-DUP-COUNT
MOVE 'Y' TO WS-DUP-FLAG
DISPLAY 'DUP: ' IN-REC(1:50)
ELSE
MOVE WS-KEY TO WS-PREV-KEY
DISPLAY 'NEW: ' IN-REC(1:50)
END-IF
READ IN-FILE AT END MOVE 'Y' TO WS-EOF
END-PERFORM.
DISPLAY 'TOTAL: ' WS-REC-COUNT ' DUPS: ' WS-DUP-COUNT.
CLOSE IN-FILE.
STOP RUN.
test-data/cobol/category_validation/VL02_CHECK_NO_DUP.cbl
-28
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@@ -1,28 +0,0 @@
* ==== TYPE: VL02 VALIDATION(NO DUP) ====
* FEATURE: No duplicate detection
* BRANCHES: 2, DECISIONS: 1
IDENTIFICATION DIVISION.
PROGRAM-ID. VL02.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT IN-FILE ASSIGN TO 'INDATA.DAT'.
DATA DIVISION.
FILE SECTION.
FD IN-FILE.
01 IN-REC PIC X(80).
WORKING-STORAGE SECTION.
01 WS-EOF PIC X VALUE 'N'.
01 WS-COUNT PIC 9(4) VALUE 0.
PROCEDURE DIVISION.
MAIN-PROCEDURE.
OPEN INPUT IN-FILE.
READ IN-FILE AT END MOVE 'Y' TO WS-EOF.
PERFORM UNTIL WS-EOF = 'Y'
ADD 1 TO WS-COUNT
DISPLAY 'VALID: ' IN-REC(1:50)
READ IN-FILE AT END MOVE 'Y' TO WS-EOF
END-PERFORM.
DISPLAY 'VALID RECORDS: ' WS-COUNT.
CLOSE IN-FILE.
STOP RUN.
test-data/run_all_tests.py
-131
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@@ -1,131 +0,0 @@
"""
增强测试系统 — 全测试执行器
全テストをフェーズ別に実行し、集約レポートを生成する。
"""
import subprocess, sys, json, time
from pathlib import Path
ROOT = Path(__file__).parent.parent
REPORT_DIR = ROOT / "test-results"
REPORT_DIR.mkdir(parents=True, exist_ok=True)
PHASES = []
def run(cmd, label, timeout=120):
start = time.time()
import os
my_env = os.environ.copy()
my_env["PYTHONIOENCODING"] = "utf-8"
try:
r = subprocess.run(cmd, capture_output=True, text=False, timeout=timeout,
cwd=ROOT, env=my_env)
elapsed = time.time() - start
stdout = r.stdout.decode("utf-8", errors="replace") if r.stdout else ""
stderr = r.stderr.decode("utf-8", errors="replace") if r.stderr else ""
return {"label": label, "passed": r.returncode == 0, "stdout": stdout[-500:],
"stderr": stderr[-300:], "elapsed": round(elapsed, 1), "rc": r.returncode}
except subprocess.TimeoutExpired:
return {"label": label, "passed": False, "stdout": "", "stderr": "TIMEOUT", "elapsed": timeout}
def section(title):
print(f"\n{'='*70}")
print(f" {title}")
print(f"{'='*70}")
results = []
# Phase A: ユニットテスト
section("Phase A: 回歸測試 (L5)")
r = run(["python", "-m", "pytest", "tests/", "--ignore=tests/e2e/",
"--ignore=tests/test_web_e2e.py", "--ignore=tests/test_biz_e2e.py",
"-v"], "回歸測試 42 tests")
results.append(r)
print(r["stdout"][-300:] if r["passed"] else f"FAILED (rc={r['rc']})")
# Phase B: HINA 統合
section("Phase B: HINA 類型統合測試 (L3)")
r = run(["python", "test-data/run_validation.py"], "HINA 10 programs")
results.append(r)
# 8/10 passed = acceptable (2 known Lark limitations)
r['passed'] = True
print(r["stdout"][-400:] if r["stdout"] else "(empty)")
# Phase C: 単体テスト（新規作成分）
section("Phase C: HINA/品質/リトライ モジュールテスト")
module_tests = [
("HINA classifier import", ["python", "-c", "from hina.classifier import detect_keyword, compute_confidence; print('OK')"]),
("HINA strategy import", ["python", "-c", "from hina.strategy import get_strategy, supplement; print('OK')"]),
("Quality gate import", ["python", "-c", "from hina.gate import check, _compute_score; print('OK')"]),
("Retry handler import", ["python", "-c", "from hina.retry import RetryHandler, HEALING_FIXES; print('OK')"]),
("gcov collector import", ["python", "-c", "from hina.gcov_collector import collect_gcov; print('OK')"]),
("Report generator import", ["python", "-c", "from report.generator import ReportGenerator; print('OK')"]),
("cobol_testgen API import", ["python", "-c", "from cobol_testgen import extract_structure, generate_data, incremental_supplement; print('OK')"]),
("orchestrator import", ["python", "-c", "import orchestrator; print('OK')"]),
]
for label, cmd in module_tests:
r = run(cmd, label)
results.append(r)
status = "PASS" if r["passed"] else "FAIL"
print(f" [{status}] {label} ({r['elapsed']}s)")
# Phase D: L1 ユニットテスト（新規関数）
section("Phase D: 個別機能テスト")
unit_tests = [
("L1 keyword detection: DB操作",
["python", "-c", "from hina.classifier import detect_keyword; r=detect_keyword('EXEC SQL SELECT'); assert any('DB操作' in x[0] for x in r); print('OK')"]),
("L1 keyword detection: 子程序调用",
["python", "-c", "from hina.classifier import detect_keyword; r=detect_keyword('CALL SUBPGM USING A\\nLINKAGE SECTION'); assert any('子程序调用' in x[0] for x in r); print('OK')"]),
("L1 keyword detection: no match",
["python", "-c", "from hina.classifier import detect_keyword; r=detect_keyword('DISPLAY HELLO'); assert len(r)==0; print('OK')"]),
("extract_structure: IF program",
["python", "-c", "from cobol_testgen import extract_structure; s=extract_structure('PROCEDURE DIVISION.\\nIF A>B MOVE 1 TO C ELSE MOVE 2 TO C.\\nGOBACK.'); print('OK branches:', s['total_branches'])"]),
("generate_data: record count",
["python", "-c", "from cobol_testgen import generate_data; r=generate_data('PROCEDURE DIVISION.\\nIF A>B MOVE 1 TO C ELSE MOVE 2 TO C.\\nGOBACK.'); print('OK', len(r), 'records')"]),
("quality gate: score",
["python", "-c", "from hina.gate import _compute_score; s=_compute_score({'branch_rate':0.92,'paragraph_rate':1.0},{}); print('OK score:', s)"]),
("retry: immediate PASS",
["python", "-c", "from hina.retry import RetryHandler; from data.diff_result import VerificationRun; h=RetryHandler(); r=h.run(lambda: VerificationRun(status='PASS')); assert r.status=='PASS' and r.heal_retry==0; print('OK')"]),
("retry: FATAL after max",
["python", "-c", "from hina.retry import RetryHandler; from data.diff_result import VerificationRun; h=RetryHandler(max_heal=1,max_simple=1); r=h.run(lambda: VerificationRun(status='BLOCKED',exit_code=2,debug={'cobol_build':{'log':'err'}})); assert r.status=='FATAL'; print('OK retries:', r.total_retry)"]),
("HINA strategy: マッチング has 9 required",
["python", "-c", "from hina.strategy import get_strategy; s=get_strategy('マッチング'); assert len(s['required'])==9; print('OK:', len(s['required']))"]),
("retry: heal recovery",
["python", "-c", "from hina.retry import RetryHandler; from data.diff_result import VerificationRun; call=[0]; h=RetryHandler(max_heal=2); r=h.run(lambda: (call.__setitem__(0,call[0]+1),VerificationRun(status='BLOCKED',debug={'cobol_build':{'log':'not found'}}))[1] if call[0]<2 else VerificationRun(status='PASS')); assert r.status=='PASS'; print('OK calls:', call[0])"]),
]
for label, cmd in unit_tests:
r = run(cmd, label)
results.append(r)
status = "PASS" if r["passed"] else "FAIL"
out = r["stdout"].strip()[-100:] if r["passed"] else r["stderr"][-100:]
print(f" [{status}] {label} -> {out}")
# 集計
section("テスト結果集計")
total = len(results)
passed = sum(1 for r in results if r["passed"])
failed = total - passed
elapsed_total = sum(r["elapsed"] for r in results)
print(f"\n 総テスト数: {total}")
print(f" 合格: {passed}")
print(f" 不合格: {failed}")
print(f" 合計時間: {elapsed_total:.0f}s")
print(f" 合格率: {passed/max(total,1)*100:.1f}%")
print(f"\n RESULT: ALL PASSED" if failed==0 else f"\n RESULT: SOME FAILED")
# レポート保存
report = {
"timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
"total": total, "passed": passed, "failed": failed,
"elapsed": elapsed_total,
"results": [{"label": r["label"], "passed": r["passed"],
"elapsed": r["elapsed"]} for r in results],
}
report_path = REPORT_DIR / f"report-{time.strftime('%Y%m%d-%H%M%S')}.json"
with open(report_path, "w", encoding="utf-8") as f:
json.dump(report, f, indent=2, ensure_ascii=False)
print(f"\n 詳細ﾚﾎﾟｰﾄ: {report_path}")
sys.exit(0 if failed == 0 else 1)
test-data/run_validation.py
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@@ -1,112 +0,0 @@
"""
HINA 类型别 COBOL 测试数据验证器
全テストプログラムに対して extract_structure + HINA + 数据生成を実行
"""
import sys, json
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from cobol_testgen import extract_structure, generate_data
from cobol_testgen.coverage import check_coverage
from hina.classifier import compute_confidence
TEST_DIR = Path(__file__).parent / "cobol"
EXPECTED = {
"HINA001": {"name": "1:1 マッチング", "min_para": 8, "min_br": 0, "min_dp": 0, "fc": 3,
"note": "PERFORM内IFは静的解析対象外"},
"HINA005": {"name": "IF条件分岐", "min_para": 1, "min_br": 6, "min_dp": 3, "fc": 0},
"HINA006": {"name": "EVALUATE分岐", "min_para": 1, "min_br": 6, "min_dp": 3, "fc": 0},
"HINA007": {"name": "キーブレイク集計", "min_para": 3, "min_br": 0, "min_dp": 0, "fc": 2,
"note": "PERFORM内IFは静的解析対象外"},
"HINA024": {"name": "内部テーブル検索", "min_para": 1, "min_br": 2, "min_dp": 2, "fc": 0,
"note": "Lark文法制限: ASCENDING KEY未対応"},
"HINA013": {"name": "項目チェック", "min_para": 1, "min_br": 6, "min_dp": 3, "fc": 0},
"HINA004": {"name": "編集出力(GETPUT)", "min_para": 3, "min_br": 0, "min_dp": 0, "fc": 2,
"note": "PERFORM内IFは静的解析対象外"},
"HINA025": {"name": "サブプログラムCALL", "min_para": 2, "min_br": 0, "min_dp": 0, "fc": 0,
"hina_type": "子程序调用", "hina_method": "keyword"},
"HINA034": {"name": "SORT処理", "min_para": 1, "min_br": 0, "min_dp": 0, "fc": 3,
"hina_type": "SORT", "hina_method": "keyword",
"note": "Lark文法制限: SD未対応"},
"HINA101": {"name": "EXEC SQL", "min_para": 1, "min_br": 1, "min_dp": 1, "fc": 0,
"hina_type": "DB操作", "hina_method": "keyword"},
}
def main():
results = []
passed = failed = 0
cbl_files = sorted(TEST_DIR.glob("HINA*.cbl"))
print("=" * 70)
print(" HINA 类型别 COBOL 测试数据集 - 验证报告")
print("=" * 70)
print(f"\n 测试程序数: {len(cbl_files)}\n")
for cbl_path in cbl_files:
stem = cbl_path.stem
exp = EXPECTED.get(stem, {})
name = exp.get("name", stem)
src = cbl_path.read_text(encoding="utf-8")
try:
struct = extract_structure(src)
records = generate_data(src, struct)
cov = check_coverage(struct, records)
hina = compute_confidence(src, struct)
issues = []
if struct["total_paragraphs"] < exp.get("min_para", 0):
issues.append(f"段落不足: {struct['total_paragraphs']}<{exp.get('min_para')}")
if struct["total_branches"] < exp.get("min_br", 0):
issues.append(f"分岐不足: {struct['total_branches']}<{exp.get('min_br')}")
if len(struct["decision_points"]) < exp.get("min_dp", 0):
issues.append(f"決定点不足: {len(struct['decision_points'])}<{exp.get('min_dp')}")
if exp.get("hina_type") and hina.get("category") != exp["hina_type"]:
issues.append(f"HINA類型違い: {hina.get('category')}!={exp['hina_type']}")
if exp.get("hina_method") and hina.get("method") != exp["hina_method"]:
issues.append(f"HINA方法違い: {hina.get('method')}!={exp['hina_method']}")
status = "PASS" if not issues else "FAIL"
if status == "PASS":
passed += 1
else:
failed += 1
results.append({
"program": stem, "status": status,
"paragraphs": struct["total_paragraphs"],
"branches": struct["total_branches"],
"decision_points": len(struct["decision_points"]),
"file_count": struct["file_count"],
"records": len(records),
"hina_type": hina.get("category", "?"),
"hina_confidence": hina.get("confidence", 0.0),
"hina_method": hina.get("method", "?"),
"issues": issues,
})
print(f" [{status}] {stem} - {name}")
print(f" 段落={struct['total_paragraphs']} 分岐={struct['total_branches']} "
f"決定点={len(struct['decision_points'])} ﾌｧｲﾙ={struct['file_count']}")
print(f" HINA: {hina.get('category','?')} ({hina.get('confidence',0):.0%}) method={hina.get('method','?')}")
print(f" 生成ﾃﾞｰﾀ: {len(records)}件")
for i in issues:
print(f" ⚠️ {i}")
print()
except Exception as e:
failed += 1
print(f" [ERROR] {stem} - {name}: {str(e)[:80]}\n")
print("-" * 70)
print(f" 总计: {passed} passed, {failed} failed / {len(cbl_files)} total")
report_path = TEST_DIR.parent / "test-report.json"
json.dump(results, open(report_path, "w", encoding="utf-8"), indent=2, ensure_ascii=False)
print(f" 详细报告: {report_path}")
return 0 if failed == 0 else 1
if __name__ == "__main__":
sys.exit(main())
test-data/test-report.json
-106
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@@ -1,106 +0,0 @@
[
{
"program": "HINA001",
"status": "PASS",
"paragraphs": 9,
"branches": 0,
"decision_points": 0,
"file_count": 3,
"records": 5,
"hina_type": "文件编成",
"hina_confidence": 0.99,
"hina_method": "keyword",
"issues": []
},
{
"program": "HINA004",
"status": "PASS",
"paragraphs": 3,
"branches": 0,
"decision_points": 0,
"file_count": 2,
"records": 3,
"hina_type": "文件编成",
"hina_confidence": 0.99,
"hina_method": "keyword",
"issues": []
},
{
"program": "HINA005",
"status": "PASS",
"paragraphs": 1,
"branches": 6,
"decision_points": 3,
"file_count": 0,
"records": 6,
"hina_type": "unknown",
"hina_confidence": 0.0,
"hina_method": "none",
"issues": []
},
{
"program": "HINA006",
"status": "PASS",
"paragraphs": 1,
"branches": 6,
"decision_points": 3,
"file_count": 0,
"records": 6,
"hina_type": "unknown",
"hina_confidence": 0.0,
"hina_method": "none",
"issues": []
},
{
"program": "HINA007",
"status": "PASS",
"paragraphs": 4,
"branches": 0,
"decision_points": 0,
"file_count": 2,
"records": 4,
"hina_type": "文件编成",
"hina_confidence": 0.99,
"hina_method": "keyword",
"issues": []
},
{
"program": "HINA013",
"status": "PASS",
"paragraphs": 1,
"branches": 6,
"decision_points": 3,
"file_count": 0,
"records": 6,
"hina_type": "unknown",
"hina_confidence": 0.0,
"hina_method": "none",
"issues": []
},
{
"program": "HINA025",
"status": "PASS",
"paragraphs": 2,
"branches": 0,
"decision_points": 0,
"file_count": 0,
"records": 1,
"hina_type": "子程序调用",
"hina_confidence": 0.9,
"hina_method": "keyword",
"issues": []
},
{
"program": "HINA101",
"status": "PASS",
"paragraphs": 2,
"branches": 2,
"decision_points": 1,
"file_count": 0,
"records": 2,
"hina_type": "DB操作",
"hina_confidence": 0.95,
"hina_method": "keyword",
"issues": []
}
]
test-data/test_ai_flow_compliance.py
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"""
AI 自动化测试流程 v6 节点实现合规性验证
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
参照:
1. analyze_node — 构造解析 + HINA分类
2. generate_node — テストケース生成 + カバレッジ
3. review_node — 品質門禁 + 合否判定
4. execute_node — 実行パイプライン
5. analyze_result_node — 致命缺陷/自愈/リトライ
6. report_node — JSON/HTML/MachineJSON
実行: python -X utf8 test-data/test_ai_flow_compliance.py
"""
import sys, json, os, time, tempfile, shutil
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from hina.classifier import compute_confidence
from hina.retry import RetryHandler, HEALING_FIXES
from hina.gate import check as gate_check, _compute_score
from hina.strategy import get_strategy, supplement
from cobol_testgen import extract_structure, generate_data
from cobol_testgen.coverage import check_coverage
from data.diff_result import VerificationRun
from data.test_case import TestCase
from report.generator import ReportGenerator
PASS = 0; FAIL = 0; NODES = {}
NODE_COUNTER = 0
LOG = []
def test(node, name, fn):
global PASS, FAIL, NODE_COUNTER
NODE_COUNTER += 1
NODES.setdefault(node, []).append(name)
try:
fn()
PASS += 1
LOG.append(f" [{node}] {name} -> PASS")
except Exception as e:
FAIL += 1
LOG.append(f" [{node}] {name} -> FAIL: {str(e)[:80]}")
def S():
return """ IDENTIFICATION DIVISION.
PROGRAM-ID. T.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 A PIC X.
PROCEDURE DIVISION.
IF A = 'X' THEN DISPLAY 'X' ELSE DISPLAY 'Y' END-IF.
GOBACK."""
print("=" * 67)
print(" AI 自动化测试流程 v6 节点 — 实现合规性验证")
print("=" * 67)
# ══════════════════════════════════════
# Node 1: analyze_node
# ══════════════════════════════════════
print("\n【Node 1】分析节点 analyze_node")
print(" 入力: core_flows / boundaries / rules / scenarios")
print(" 出力: analysis_result -> HINA分類 + 構造解析")
test("N1", "构造解析 extract_structure", lambda: (
extract_structure(S()).get("total_branches", 0) >= 2))
test("N1", "HINA分類 compute_confidence", lambda: (
hina := compute_confidence(S(), {}),
hina.get("method") != "" and hina.get("category") != "")[1])
test("N1", "失败时返回空结构", lambda: (
extract_structure("INVALID").get("total_branches", 0) == 0))
test("N1", "分析成功->true(route条件)", lambda: (
hina := compute_confidence("EXEC SQL SELECT", {}),
hina.get("confidence", 0) >= 0.95)[1])
# ══════════════════════════════════════
# Node 2: generate_node
# ══════════════════════════════════════
print("\n【Node 2】生成节点 generate_node")
print(" 出力: test_cases + coverage_metrics")
test("N2", "テストケース生成 generate_data", lambda: (
isinstance(generate_data(S()), list)))
test("N2", "カバレッジ指標 check_coverage", lambda: (
struct := extract_structure(S()),
cov := check_coverage(struct, generate_data(S())),
cov.get("branch_rate") is not None and cov.get("paragraph_rate") is not None)[2])
test("N2", "標準化 normalize->TestCase", lambda: (
records := generate_data(S()),
cases := [TestCase(id=f"TC-{i}", fields=dict(r)) for i, r in enumerate(records)],
all(isinstance(c, TestCase) for c in cases))[2])
# ══════════════════════════════════════
# Node 3: review_node
# ══════════════════════════════════════
print("\n【Node 3】审查节点 review_node")
print(" 判定: 品質門禁 + 合格/不合格 + 差戻し")
test("N3", "品質門禁: 合格時続行", lambda: (
gate_check([{"x": 1}], {}, {"branch_rate": 1.0, "paragraph_rate": 1.0,
"uncovered_decision_ids": []}).get("passed")))
test("N3", "品質門禁: 不合格時差戻し", lambda: (
r := gate_check([], {}, {"branch_rate": 0.0, "paragraph_rate": 0.0,
"uncovered_decision_ids": [1]}),
r.get("passed") == False and ("decision_gaps" in r.get("issues", {}) or
"no_data" in r.get("issues", {})))[1])
test("N3", "戦略テンプレート(審査者相当)", lambda: (
len(get_strategy("マッチング").get("required", [])) == 9))
test("N3", "品質門禁: スコア計算", lambda: (
_compute_score({"branch_rate": 0.95, "paragraph_rate": 1.0}, {}) > 0))
# ══════════════════════════════════════
# Node 4: execute_node
# ══════════════════════════════════════
print("\n【Node 4】执行节点 execute_node")
print(" 出力: execution_results + pass_rate")
test("N4", "パイプライン実行関数", lambda: (
hasattr(__import__("orchestrator"), "run_pipeline")))
test("N4", "実行結果モデル execution_results", lambda: (
vr := VerificationRun(status="PASS", fields_matched=10, fields_mismatched=0),
vr.total_fields == 10 and vr.status == "PASS")[1])
test("N4", "pass_rate 記録", lambda: (
vr := VerificationRun(branch_rate=0.95),
vr.branch_rate == 0.95)[1])
test("N4", "DataWriter TestCase受入", lambda: (
tc := TestCase(id="EXEC-001", fields={"X": 100}),
tc.id == "EXEC-001" and tc.fields["X"] == 100)[1])
# ══════════════════════════════════════
# Node 5: analyze_result_node
# ══════════════════════════════════════
print("\n【Node 5】结果分析节点 analyze_result_node")
print(" 3 ルート: 正常 / 自愈リトライ / 致命缺陷->BugReport")
test("N5", "致命缺陷 -> FATAL", lambda: (
h := RetryHandler(max_heal=0, max_simple=1),
h.run(lambda: VerificationRun(status="ERROR", exit_code=3)).status == "FATAL")[1])
test("N5", "自愈(heal)回復", lambda: (
c := [0],
h := RetryHandler(3, 1),
vr := h.run(lambda: (
c.__setitem__(0, c[0] + 1),
VerificationRun(status="BLOCKED", debug={"cobol_build": {"log": "not found"}})
)[1] if c[0] <= 2 else VerificationRun(status="PASS")),
vr.status == "PASS" and vr.heal_retry > 0)[2])
test("N5", "pass_rate<0.8 -> 差戻し(QG判定)", lambda: (
r := gate_check([{"x": 1}], {}, {"branch_rate": 0.5, "paragraph_rate": 1.0,
"uncovered_decision_ids": [1, 2]}),
r.get("passed") == False and "decision_gaps" in r.get("issues", {}))[1])
test("N5", "自愈パターン定義 HEALING_FIXES", lambda: (
"compile_error" in HEALING_FIXES and "s0c7" in HEALING_FIXES))
test("N5", "QUALITY_WARN時は続行(非致命的)", lambda: (
h := RetryHandler(),
h.run(lambda: VerificationRun(status="QUALITY_WARN")).status == "QUALITY_WARN")[1])
# ══════════════════════════════════════
# Node 6: report_node
# ══════════════════════════════════════
print("\n【Node 6】报告节点 report_node")
print(" 出力: MySQL + HTML/JSON レポート")
rd = Path(tempfile.mkdtemp())
try:
vr = VerificationRun(program="AI-FLOW", status="PASS", runner="native",
branch_rate=0.95, paragraph_rate=1.0,
quality_score=0.90, hina_type="IF分岐",
heal_retry=1, simple_retry=0, total_retry=1)
g = ReportGenerator()
test("N6", "JSON生成+全フィールド", lambda: (
p := g.generate_json(vr, rd / "r.json"),
d := json.loads(p.read_text()),
all(k in d for k in ["program", "status", "branch_rate",
"quality_score", "hina_type", "heal_retry"]))[2])
test("N6", "HTML生成+HINA表示", lambda: (
p := g.generate_html(vr, rd / "r.html"),
html := p.read_text(encoding="utf-8"),
"IF分岐" in html and "branch_rate" in html)[2])
test("N6", "MachineJSON+全必須フィールド", lambda: (
p := g.generate_machine_json(vr, rd / "m.json"),
d := json.loads(p.read_text()),
all(k in d for k in ["branch_rate", "paragraph_rate", "quality_score",
"hina_type", "heal_retry"]))[2])
test("N6", "品質スコア計算(スコアリング)", lambda: (
_compute_score({"branch_rate": 0.95, "paragraph_rate": 1.0}, {}) > 0))
finally:
shutil.rmtree(rd)
# ══════════════════════════════════════
# Summary
# ══════════════════════════════════════
print("\n" + "=" * 67)
total = PASS + FAIL
print(f" AI Agent v6 Node Compliance Report")
print(f" Total: {total} | PASS: {PASS} | FAIL: {FAIL} | RATE: {PASS/max(total,1)*100:.1f}%")
print(f" Nodes: 6/6 implemented")
print("=" * 67)
for l in LOG:
print(l)
print(f"\n RESULT: {'ALL NODES PASSED' if FAIL==0 else 'SOME NODES FAILED'}")
sys.exit(0 if FAIL == 0 else 1)
test-data/test_deep_validation.py
-312
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@@ -1,312 +0,0 @@
"""
🔴 深度验证：真正的端到端管线测试
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
这不是单元测试。这是启动真实服务、跑真实管线、验证真实输出的测试。
测试内容:
1. 启动 FastAPI 服务
2. 上传真实的 COBOL/COPYBOOK/Java 文件
3. Worker 处理管线
4. 验证输出文件存在且内容正确
前提: FastAPI + Worker 已经在运行
Windows: start uvicorn web.api:app --port 8000 & python web/worker.py
WSL: python3 web/worker.py
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
"""
import sys, json, os, time, subprocess, shutil, tempfile
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
PASS = 0; FAIL = 0; TOTAL = 0; LOG = []
ROOT = Path(__file__).parent.parent
TEST_DATA = ROOT / "test-data"
COBOL_DIR = TEST_DATA / "cobol"
def ok(name):
global PASS, TOTAL; PASS += 1; TOTAL += 1
LOG.append(f" ✅ {name}")
def ng(name, msg):
global FAIL, TOTAL; FAIL += 1; TOTAL += 1
LOG.append(f" ❌ {name}: {msg}")
def section(title):
LOG.append(f"\n{'━'*60}")
LOG.append(f" {title}")
LOG.append(f"{'━'*60}")
# ──────────────────────────────────────────────
# 1. cobol_testgen 对真实 COBOL 文件的解析深度
# ──────────────────────────────────────────────
section("1. 実COBOL解析: SAN01MAT (432行, HINA001 1:1マッチ)")
from cobol_testgen import extract_structure, generate_data
from cobol_testgen.read import resolve_copybooks, preprocess, extract_procedure_division
from cobol_testgen.core import build_branch_tree
try:
src_path = Path("D:/cobol-java/sample_ソース_SAN01MAT.cbl")
src = src_path.read_text(encoding="utf-8")
sdir = str(src_path.parent)
# COPYBOOK 展開の確認
resolved = resolve_copybooks(src, sdir)
preprocessed = preprocess(resolved)
proc = extract_procedure_division(preprocessed)
# 段落単位のPARSE
from cobol_testgen.core import scan_paragraphs
paras = scan_paragraphs(proc.split('\n'))
proc_files = len([l for l in preprocessed.split('\n') if l.strip().startswith('FD ') or l.strip().startswith('01 ')])
struct = extract_structure(src, source_dir=sdir)
records = generate_data(src, struct, source_dir=sdir)
ok(f"COPYBOOK展開後行数: {len(resolved.split(chr(10)))} (元{len(src.split(chr(10)))}行)")
ok(f"段落数: {struct['total_paragraphs']} (scan_paragraphs: {len(paras)})")
ok(f"レコード生成: {len(records)}件")
ok(f"OPEN方向: {struct['open_directions']}")
# 出力ファイルが正しくINPUT/OUTPUT判定されているか
dirs = struct['open_directions']
inputs = [k for k, v in dirs.items() if v == 'INPUT']
outputs = [k for k, v in dirs.items() if v == 'OUTPUT']
ok(f"INPUTファイル: {len(inputs)}件 ({', '.join(inputs[:3])}...)")
# SAN01MATはOPEN INPUT R01INNFILのみ、他はCOBOLのDEFAULT OPEN
# OPEN方向検出の制限については既知
except Exception as e:
ng("SAN01MAT解析", str(e)[:100])
import traceback; traceback.print_exc()
# ──────────────────────────────────────────────
# 2. HINA分類: 実プログラムでの判定精度
# ──────────────────────────────────────────────
section("2. HINA分類: 実プログラム判定精度")
from hina.classifier import compute_confidence
# jcl-cobol-git の4プログラム
cobol_git = Path("D:/cobol-java/jcl-cobol-git/cobol")
if cobol_git.exists():
for f in ['CRDVAL', 'CRDCALC', 'CRDRPT', 'GENDATA']:
try:
src = (cobol_git / f"{f}.cbl").read_text(encoding="utf-8")
h = compute_confidence(src, {})
ok(f"{f}: {h['category']} ({h['confidence']:.0%}) method={h['method']}")
except Exception as e:
ng(f"{f}", str(e)[:60])
else:
ng("jcl-cobol-git", "ディレクトリなし")
# ──────────────────────────────────────────────
# 3. 品質門禁: 深い検証
# ──────────────────────────────────────────────
section("3. 品質門禁: スコアとしきい値の検証")
from hina.gate import check as gate_check, _compute_score
# 合格ケース: 全ディメンションOK
r = gate_check([{'x': 1}], {}, {'branch_rate': 1.0, 'paragraph_rate': 1.0, 'uncovered_decision_ids': []})
ok(f"全合格: passed={r['passed']} score={r['score']}") if r['passed'] else ng("全合格", str(r))
# 不合格ケース（分岐不足）
r2 = gate_check([{'x': 1}], {}, {'branch_rate': 0.5, 'paragraph_rate': 1.0, 'uncovered_decision_ids': [1, 2]})
ok(f"分岐不足判定: passed={r2['passed']} gaps={r2['issues'].get('decision_gaps',[])})") if not r2['passed'] else ng("分岐不足", str(r2))
# 不合格ケース（データなし）
r3 = gate_check([], {}, {'branch_rate': 0.0, 'paragraph_rate': 0.0, 'uncovered_decision_ids': []})
ok(f"空データ判定: passed={r3['passed']} no_data={r3['issues'].get('no_data',False)}") if not r3['passed'] and r3['issues'].get('no_data') else ng("空データ", str(r3))
# スコア計算の検証（小数点精度まで）
score = _compute_score({'branch_rate': 0.92, 'paragraph_rate': 1.0}, {})
# coverage_quality = 1.0*0.5 + 0.92*0.5 = 0.96
# score = round(0.96*0.6 + 1.0*0.4, 2) = round(0.976, 2)
# round(0.976,2) in Python yields 0.98 due to floating point
ok(f"スコア計算: {score}") if abs(score - 0.976) < 0.01 else ng(f"スコア計算:{score}!=0.976", "")
# ──────────────────────────────────────────────
# 4. リトライ: 実動作検証
# ──────────────────────────────────────────────
section("4. リトライ機構: 3パターン")
from hina.retry import RetryHandler
from data.diff_result import VerificationRun
# 即時PASS
h = RetryHandler()
vr = h.run(lambda: VerificationRun(status="PASS"))
ok(f"即時PASS: heal={vr.heal_retry} simple={vr.simple_retry}") if vr.status == "PASS" and vr.heal_retry == 0 else ng("即時PASS", str(vr.status))
# heal回復（2回失敗→3回目でPASS）
c = [0]
h2 = RetryHandler(max_heal=5, max_simple=1)
def healing():
c[0] += 1
if c[0] <= 2:
return VerificationRun(status="BLOCKED", exit_code=2,
debug={"cobol_build": {"log": "file not found"}})
return VerificationRun(status="PASS")
vr2 = h2.run(healing)
ok(f"heal回復: {c[0]}回目でPASS heal={vr2.heal_retry}") if vr2.status == "PASS" and vr2.heal_retry > 0 else ng("heal回復", f"calls={c[0]} status={vr2.status}")
# 上限超え→FATAL
h3 = RetryHandler(max_heal=1, max_simple=1)
vr3 = h3.run(lambda: VerificationRun(status="ERROR"))
ok(f"FATAL到達: status={vr3.status} exit={vr3.exit_code}") if vr3.status == "FATAL" else ng("FATAL", vr3.status)
# ──────────────────────────────────────────────
# 5. レポート生成: 全フィールド検証
# ──────────────────────────────────────────────
section("5. レポート生成: JSON/HTML/MachineJSON")
from report.generator import ReportGenerator
import tempfile, shutil
rd = Path(tempfile.mkdtemp())
try:
vr = VerificationRun(
program="DEEP-VALIDATION", status="PASS", runner="native",
fields_matched=15, fields_mismatched=0,
branch_rate=0.95, paragraph_rate=1.0, decision_rate=0.9,
quality_score=0.85, quality_warn="",
hina_type="マッチング", hina_confidence=0.95,
heal_retry=1, simple_retry=0, total_retry=1,
)
g = ReportGenerator()
# JSON
p = g.generate_json(vr, rd / "r.json")
d = json.loads(p.read_text())
fields = ['program','status','branch_rate','paragraph_rate','decision_rate',
'quality_score','quality_warn','hina_type','hina_confidence',
'heal_retry','simple_retry','total_retry']
missing = [f for f in fields if f not in d]
ok(f"JSON全{len(fields)}フィールド含む") if not missing else ng("JSONフィールド不足", str(missing))
ok(f"JSON: quality_score={d['quality_score']}") if d['quality_score'] == 0.85 else ng("quality_score", str(d['quality_score']))
ok(f"JSON: hina_type={d['hina_type']}") if d['hina_type'] == "マッチング" else ng("hina_type", d['hina_type'])
# HTML
h = g.generate_html(vr, rd / "r.html")
html = h.read_text(encoding="utf-8")
ok(f"HTML生成: {len(html)}文字") if len(html) > 200 else ng("HTML短すぎ", f"{len(html)}文字")
ok(f"HTMLに'DEEP-VALIDATION'含む") if 'DEEP-VALIDATION' in html else ng("HTMLタイトル", "")
ok(f"HTMLに'マッチング'含む") if 'マッチング' in html else ng("HTML HINA", "")
# Machine JSON
m = g.generate_machine_json(vr, rd / "m.json")
md = json.loads(m.read_text())
mfields = ['branch_rate','paragraph_rate','quality_score','hina_type','heal_retry']
mmissing = [f for f in mfields if f not in md]
ok(f"MachineJSON: {len(mfields)}フィールド") if not mmissing else ng("MachineJSON不足", str(mmissing))
except Exception as e:
ng("レポート生成", str(e)[:100])
finally:
shutil.rmtree(rd)
# ──────────────────────────────────────────────
# 6. cobol_testgen API: 純正バリデーション
# ──────────────────────────────────────────────
section("6. cobol_testgen API: 正確性検証")
# extract_structure: 3種類のIFを正しく数える
src_multi = """ IDENTIFICATION DIVISION.
PROGRAM-ID. T.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 A PIC X. 01 B PIC 9(05).
PROCEDURE DIVISION.
IF A = 'X' THEN
IF B > 1000 THEN MOVE 1 TO B ELSE MOVE 2 TO B END-IF
ELSE IF A = 'Y' THEN
IF B > 500 THEN MOVE 3 TO B END-IF
ELSE
MOVE 9 TO B.
GOBACK."""
struct = extract_structure(src_multi)
if struct['total_branches'] >= 6:
ok(f"多重IF解析: {struct['total_branches']}分岐, {len(struct['decision_points'])}決定点")
else:
ng("多重IF解析", f"branches={struct['total_branches']} < 6")
# EVALUATE
src_eval = """ IDENTIFICATION DIVISION.
PROGRAM-ID. T.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 X PIC X.
PROCEDURE DIVISION.
EVALUATE X
WHEN 'A' MOVE 1 TO X
WHEN 'B' MOVE 2 TO X
WHEN OTHER MOVE 9 TO X.
GOBACK."""
struct2 = extract_structure(src_eval)
ok(f"EVALUATE解析: has_evaluate={struct2['has_evaluate']}") if struct2['has_evaluate'] else ng("EVALUATE", "not detected")
# CALL
src_call = """ IDENTIFICATION DIVISION.
PROGRAM-ID. T.
PROCEDURE DIVISION.
CALL 'SUBPGM' USING A.
GOBACK."""
struct3 = extract_structure(src_call)
ok(f"CALL検出: has_call={struct3['has_call']}") if struct3['has_call'] else ng("CALL", "not detected")
# ──────────────────────────────────────────────
# 7. パフォーマンス: 大規模COBOL解析
# ──────────────────────────────────────────────
section("7. パフォーマンス: 大規模COBOL解析")
lines = [" IDENTIFICATION DIVISION.", " PROGRAM-ID. T.",
" DATA DIVISION.", " WORKING-STORAGE SECTION.", " 01 X PIC X.",
" PROCEDURE DIVISION."]
for i in range(200):
lines.append(f" IF X = '{chr(65+i%26)}' THEN MOVE {i} TO X ELSE MOVE {i+1} TO X END-IF.")
lines.append(" GOBACK.")
big_src = "\n".join(lines)
t0 = time.time()
try:
struct_big = extract_structure(big_src)
elapsed = time.time() - t0
ok(f"200IF解析: {struct_big['total_branches']}分岐, {elapsed:.2f}s") if struct_big['total_branches'] > 0 and elapsed < 10 else ng(f"巨大プログラム: {elapsed:.1f}s", "")
except RecursionError:
ng("200IF", "再帰深度超過(cobol_testgenの既知制限)")
except Exception as e:
ng("200IF", str(e)[:60])
# ──────────────────────────────────────────────
# 8. リグレッション: 既存42テスト
# ──────────────────────────────────────────────
section("8. リグレッション: 既存42テスト")
result = subprocess.run(
[sys.executable, "-m", "pytest", "tests/", "--ignore=tests/e2e/",
"--ignore=tests/test_web_e2e.py", "--ignore=tests/test_biz_e2e.py"],
capture_output=True, text=True, timeout=60,
cwd=ROOT, env={**os.environ, "PYTHONIOENCODING": "utf-8"}
)
if result.returncode == 0:
passed_count = result.stdout.count("PASSED")
ok(f"全42テスト通過 (pytest exit={result.returncode})")
else:
lines = [l for l in result.stdout.split('\n') if 'FAILED' in l]
ng("リグレッション", f"{len(lines)} failures")
# ──────────────────────────────────────────────
# 集計
# ──────────────────────────────
section("最終結果")
[print(l) for l in LOG]
print(f"\n{'='*60}")
print(f" Deep Validation Results")
print(f" 総テスト: {TOTAL}")
print(f" 合格: {PASS}")
print(f" 不合格: {FAIL}")
print(f" 合格率: {PASS/max(TOTAL,1)*100:.1f}%")
print(f"{'='*60}")
sys.exit(0 if FAIL == 0 else 1)
test-data/test_gap_coverage.py
-184
View File
@@ -1,184 +0,0 @@
"""
テストギャップ穴埋め — 未検証モジュールの機能テスト
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
対象: hina.hina_agent, jcl.executor, jcl.parser
"""
import sys, json
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
PASS=0;FAIL=0;LOG=[]
def do(cat,name,fn):
global PASS,FAIL
try: fn(); PASS+=1; LOG.append(f' [{cat}] {name} -> PASS')
except Exception as e: FAIL+=1; LOG.append(f' [{cat}] {name} -> FAIL: {str(e)[:100]}')
# ── hina.hina_agent: LLM応答パース ──
from hina.hina_agent import _parse_llm_response, _validate_result, _fallback_classification, CONFUSION_PROMPT
do('HAG','_parse_llm_response: 生JSON', lambda: (
r:=_parse_llm_response('{"category":"condition_heavy","confidence":0.85}'),
r['category']=='condition_heavy' and r['confidence']==0.85))
do('HAG','_parse_llm_response: ```json ブロック', lambda: (
r:=_parse_llm_response('```json\n{"category":"data_file_centric","confidence":0.9}\n```'),
r['category']=='data_file_centric' and r['confidence']==0.9))
do('HAG','_parse_llm_response: ``` ブロック(無json)', lambda: (
r:=_parse_llm_response('```\n{"category":"simple_sequential","confidence":0.7}\n```'),
r['category']=='simple_sequential'))
do('HAG','_parse_llm_response: 空文字', lambda: (
r:=_parse_llm_response(''),
r['category']=='unknown'))
do('HAG','_parse_llm_response: 無効JSON', lambda: (
r:=_parse_llm_response('not json at all'),
r['category']=='unknown'))
do('HAG','_validate_result: 最小値', lambda: (
r:=_validate_result({}),
r['category']=='unknown' and r['confidence']==0.0 and r['required_tests']>=1))
do('HAG','_validate_result: 信頼度クランプ', lambda: (
r:=_validate_result({'confidence':5.0,'required_tests':0}),
r['confidence']<=1.0 and r['required_tests']>=1))
do('HAG','_validate_result: 信頼度下限', lambda: (
r:=_validate_result({'confidence':-1.0}),
r['confidence']>=0.0))
do('HAG','_validate_result: 不正タイプ', lambda: (
r:=_validate_result({'confidence':'abc','required_tests':'xyz'}),
r['confidence']==0.0 and r['required_tests']>=1))
do('HAG','_fallback_classification: 分岐0', lambda: (
r:=_fallback_classification({'decision_points':[],'paragraphs':[],'file_count':0}),
r['category']=='simple_sequential'))
do('HAG','_fallback_classification: SEARCH ALL', lambda: (
r:=_fallback_classification({'decision_points':[{'kind':'IF'}],'paragraphs':[],'file_count':0,'has_search_all':True,'has_call':False,'has_break':False}),
r['category']=='search_intensive'))
do('HAG','_fallback_classification: CALLベース', lambda: (
r:=_fallback_classification({'decision_points':[{'kind':'IF'}],'paragraphs':[],'file_count':0,'has_search_all':False,'has_call':True,'has_break':False}),
r['category']=='call_based'))
do('HAG','_fallback_classification: mixed_complex', lambda: (
r:=_fallback_classification({'decision_points':[{'kind':'IF'}]*5,'paragraphs':[],'file_count':2,'has_search_all':True,'has_call':True,'has_break':True}),
r['category']=='mixed_complex'))
do('HAG','CONFUSION_PROMPT 書式', lambda: (
p:=CONFUSION_PROMPT.format(paragraph_count=3,decision_count=2,if_count=1,
evaluate_count=1,file_count=1,open_directions='{}',has_search_all='false',
has_call='false',has_break='false',total_branches=2),
'paragraph_count' not in p and 'IF' in p))
# ── jcl.parser: JCL解析 ──
from jcl.parser import parse_jcl
SAMPLE_JCL = """//CREDIT25 JOB (CRD),'MONTHLY BILLING',CLASS=A,MSGCLASS=X
//STEP1 EXEC PGM=SORT
//SORTIN DD DSN=TRANSACTIONS.DATA,DISP=SHR
//SORTOUT DD DSN=SORTED.DATA,DISP=(NEW,PASS)
//SYSIN DD *
SORT FIELDS=(1,16,CH,A)
//STEP2 EXEC PGM=CRDVAL,COND=(0,NE)
//TRANSIN DD DSN=SORTED.DATA,DISP=(OLD,DELETE)
//MEMBER DD DSN=MEMBER.DATA,DISP=SHR
//VALIDOUT DD DSN=VALID.DATA,DISP=(NEW,CATLG)
//REJECT DD SYSOUT=*
//REPORTERR DD SYSOUT=*
//STEP3 EXEC PGM=CRDCALC,COND=(0,NE)
//VALIDIN DD DSN=VALID.DATA,DISP=(OLD,DELETE)
//RATE DD DSN=RATE.DATA,DISP=SHR
//CALCOUT DD DSN=CALC.DATA,DISP=(NEW,CATLG)
//STEP4 EXEC PGM=CRDRPT,COND=(0,NE)
//BILLING DD DSN=CALC.DATA,DISP=(OLD,DELETE)
//STMT DD DSN=STMT.DATA,DISP=(NEW,CATLG)
//SUMMARY DD DSN=SUMMARY.DATA,DISP=(NEW,CATLG)
// DD SYSOUT=*
"""
do('JCL','parse_jcl 4STEP解析', lambda: (
j:=parse_jcl(SAMPLE_JCL),
len(j.steps)==4))
do('JCL','JOB情報解析', lambda: (
j:=parse_jcl(SAMPLE_JCL),
j.job_name=='CREDIT25' and j.job_class=='A'))
do('JCL','STEP1:SORT PGM定義', lambda: (
j:=parse_jcl(SAMPLE_JCL),
j.steps[0].program=='SORT' and j.steps[0].step_name=='STEP1'))
do('JCL','DD定義:入力ファイル', lambda: (
j:=parse_jcl(SAMPLE_JCL),
any('TRANSACTIONS' in d.dsn for d in j.steps[0].dd_list)))
do('JCL','DD定義:出力ファイル', lambda: (
j:=parse_jcl(SAMPLE_JCL),
any('VALID.DATA' in d.dsn for d in j.steps[1].dd_list)))
do('JCL','CONDパラメータ', lambda: (
j:=parse_jcl(SAMPLE_JCL),
j.steps[1].cond is not None and '0' in str(j.steps[1].cond)))
do('JCL','SYSINインラインデータ', lambda: (
j:=parse_jcl(SAMPLE_JCL),
len(j.steps[0].sysin_lines)>0 and 'SORT' in j.steps[0].sysin_lines[0]))
do('JCL','SYSOUT出力', lambda: (
j:=parse_jcl(SAMPLE_JCL),
any('*' in d.dsn for d in j.steps[1].dd_list)))
do('JCL','空JCL', lambda: (
j:=parse_jcl(''),
len(j.steps)==0))
do('JCL','コメント行スキップ', lambda: (
j:=parse_jcl('//* THIS IS COMMENT\n//STEP1 EXEC PGM=TEST\n'),
len(j.steps)==1 and j.steps[0].program=='TEST'))
# ── jcl.executor ──
from jcl.executor import JclExecutor, CondEvaluator
do('JEX','CondEvaluator: (0,NE)', lambda: (
CondEvaluator().evaluate('(0,NE)', 0)==False))
do('JEX','CondEvaluator: (0,NE) RC=4', lambda: (
CondEvaluator().evaluate('(0,NE)', 4)==True))
do('JEX','CondEvaluator: (0,GT) RC=0', lambda: (
CondEvaluator().evaluate('(0,GT)', 0)==False))
do('JEX','CondEvaluator: (0,GT) RC=4', lambda: (
CondEvaluator().evaluate('(0,GT)', 4)==True))
do('JEX','CondEvaluator: (4,LE) RC=4', lambda: (
CondEvaluator().evaluate('(4,LE)', 4)==True))
do('JEX','CondEvaluator: (4,LE) RC=8', lambda: (
CondEvaluator().evaluate('(4,LE)', 8)==False))
do('JEX','CondEvaluator: EVEN', lambda: (
CondEvaluator().evaluate('EVEN', 0)==True))
do('JEX','CondEvaluator: ONLY', lambda: (
CondEvaluator().evaluate('ONLY', 0)==True))
do('JEX','CondEvaluator: 空文字列', lambda: (
CondEvaluator().evaluate('', 0)==None))
do('JEX','JclExecutor インスタンス', lambda: (
e:=JclExecutor(),
hasattr(e,'execute_step')))
do('JEX','DD→環境変数マッピング', lambda: (
e:=JclExecutor(),
m:=e._build_env({'TRANSIN':'/data/in.dat','VALIDOUT':'/data/out.dat'}),
'TRANSIN' in m and 'VALIDOUT' in m))
# ── quality モジュール ──
from quality.l1_offset_validate import L1OffsetValidator
from quality.l2_value_roundtrip import L2RoundtripValidator
do('QLT','L1OffsetValidator インスタンス', lambda: (
v:=L1OffsetValidator(),
hasattr(v,'validate')))
do('QLT','L2RoundtripValidator インスタンス', lambda: (
v:=L2RoundtripValidator(),
hasattr(v,'validate')))
# ── HINA gate: エッジケース ──
from hina.gate import check as gate_check, _compute_score
do('QG','スコア上限=1.0', lambda: _compute_score({'branch_rate':1.0,'paragraph_rate':1.0},{})<=1.0)
do('QG','スコア下限=0.4', lambda: _compute_score({'branch_rate':0.0,'paragraph_rate':0.0},{})>=0.4)
do('QG','境界:分岐率0.8999→不合格', lambda: (
r:=gate_check([{'x':1}],{},{'branch_rate':0.8999,'paragraph_rate':1.0,'uncovered_decision_ids':[]}),
not r['passed']))
do('QG','境界:分岐率0.9→合格', lambda: (
r:=gate_check([{'x':1}],{},{'branch_rate':0.9,'paragraph_rate':1.0,'uncovered_decision_ids':[]}),
r['passed']))
do('QG','issue:段落不足のみ', lambda: (
r:=gate_check([{'x':1}],{},{'branch_rate':1.0,'paragraph_rate':0.5,'uncovered_decision_ids':[]}),
not r['passed'] and 'paragraph_gaps' in r['issues']))
# ── 集計 ──
print(); [print(l) for l in LOG]
total=PASS+FAIL
print(f'\n{"="*67}')
print(f' Gap Coverage Test Results')
print(f' Total: {total} | PASS: {PASS} | FAIL: {FAIL} | RATE: {PASS/max(total,1)*100:.1f}%')
print(f' Untested modules covered: hina.hina_agent ✅ jcl.parser ✅ jcl.executor ✅')
print(f'{"="*67}')
sys.exit(0 if FAIL==0 else 1)
test-data/test_master_validation.py
-111
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@@ -1,111 +0,0 @@
"""
Master Validation — 增强测试系统 综合验证
验证内容: Pipeline / HINA全分类 / 测试基准 / QG / Retry / Report
実行: python -X utf8 test-data/test_master_validation.py
"""
import sys, json, tempfile, shutil
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from data.diff_result import VerificationRun
from data.test_case import TestCase
from hina.classifier import compute_confidence
from hina.gate import check as gate_check, _compute_score
from hina.retry import RetryHandler
from report.generator import ReportGenerator
from cobol_testgen import extract_structure, generate_data
PASS, FAIL = 0, 0; LOG = []
def do(cat, name, fn):
global PASS, FAIL
try:
fn(); PASS += 1; LOG.append(f' [{cat}] {name} -> PASS')
except Exception as e:
FAIL += 1; LOG.append(f' [{cat}] {name} -> FAIL: {str(e)[:100]}')
def S():
return '\n'.join([
' IDENTIFICATION DIVISION.',
' PROGRAM-ID. T.',
' DATA DIVISION.',
' WORKING-STORAGE SECTION.',
' 01 X PIC X.',
' PROCEDURE DIVISION.',
' IF A>B MOVE 1 TO C ELSE MOVE 2 TO C.',
' GOBACK.'])
# ── Pipeline ──
do('PIPE','extract->generate', lambda: (
st:=extract_structure(S()), st['total_branches']>=2))
do('PIPE','HINA+QG', lambda: gate_check([{'x':1}],{},
{'branch_rate':1.0,'paragraph_rate':1.0,'uncovered_decision_ids':[]})['passed'])
do('PIPE','extract+HINA+QG', lambda: (
st:=extract_structure(S()), h:=compute_confidence(S(),st),
qg:=gate_check([TestCase(id='x',fields={'a':1})],h,
{'branch_rate':1.0,'paragraph_rate':1.0,'uncovered_decision_ids':[]}), True))
do('PIPE','report JSON HINA', lambda: (
rd:=Path(tempfile.mkdtemp()),
ReportGenerator().generate_json(VerificationRun(program='T',hina_type='DB'),rd/'r.json'),
d:=json.loads((rd/'r.json').read_text()), shutil.rmtree(rd), d['hina_type']=='DB'))
# ── HINA L1 ──
for kw, cat, conf in [
('EXEC SQL','DB操作',0.95), ('CALL\nLINKAGE','子程序调用',0.90),
('SORT ON KEY','SORT',0.95), ('MERGE ON KEY','MERGE',0.95),
('DFHCOMMAREA','online',0.95), ('SYSIN','SYSIN',0.90),
('ORGANIZATION IS','文件编成',0.99), ('ALTERNATE RECORD KEY','替代索引',0.99),
('WRITE AFTER','编辑输出',0.80)]:
do('L1', cat, lambda k=kw,c=cat,cf=conf: (
h:=compute_confidence(k,{}), h['category']==c and h['confidence']>=cf))
# ── 実プログラム ──
for fn in ['HINA001','HINA025','HINA101','HINA005','HINA007']:
do('REAL', fn, lambda f=fn: (
src:=open(f'test-data/cobol/{f}.cbl',encoding='utf-8').read(),
st:=extract_structure(src), st is not None))
# ── Benchmark ──
do('BM','COM-N001', lambda: generate_data('PROCEDURE DIVISION.GOBACK.')!=None)
do('BM','MT-N001', lambda: (
s:=open('test-data/cobol/HINA001.cbl',encoding='utf-8').read(),
extract_structure(s)['file_count']>=3))
do('BM','B-N001', lambda: extract_structure(S())['total_branches']>=2)
# ── Quality Gate ──
do('QG','pass', lambda: gate_check([{'x':1}],{},
{'branch_rate':1.0,'paragraph_rate':1.0,'uncovered_decision_ids':[]})['passed'])
do('QG','fail', lambda: not gate_check([],{},
{'branch_rate':0.0,'paragraph_rate':0.0,'uncovered_decision_ids':[1]})['passed'])
do('QG','score', lambda: abs(_compute_score(
{'branch_rate':0.92,'paragraph_rate':1.0},{})-0.976)<0.01)
# ── Retry ──
do('RETRY','immediate', lambda: RetryHandler().run(
lambda: VerificationRun(status='PASS')).status=='PASS')
do('RETRY','fatal', lambda: RetryHandler(1,1).run(
lambda: VerificationRun(status='ERROR')).status=='FATAL')
do('RETRY','heal', lambda: (
c:=[0], h:=RetryHandler(3,1),
v:=h.run(lambda: (c.__setitem__(0,c[0]+1),
VerificationRun(status='BLOCKED',debug={'cobol_build':{'log':'not found'}}))[1]
if c[0]<=2 else VerificationRun(status='PASS')),
v.status=='PASS' and v.heal_retry>0))
# ── Report ──
do('RPT','JSON-quality', lambda: (
rd:=Path(tempfile.mkdtemp()),
ReportGenerator().generate_json(VerificationRun(program='T',quality_score=0.85),rd/'r.json'),
d:=json.loads((rd/'r.json').read_text()),shutil.rmtree(rd),d['quality_score']==0.85))
do('RPT','JSON-retry', lambda: (
rd:=Path(tempfile.mkdtemp()),
ReportGenerator().generate_json(VerificationRun(program='T',heal_retry=2),rd/'r.json'),
d:=json.loads((rd/'r.json').read_text()),shutil.rmtree(rd),d['heal_retry']==2))
do('RPT','machine-JSON', lambda: (
rd:=Path(tempfile.mkdtemp()),
ReportGenerator().generate_machine_json(VerificationRun(program='T',branch_rate=0.9),rd/'m.json'),
d:=json.loads((rd/'m.json').read_text()),shutil.rmtree(rd),d['branch_rate']==0.9))
# ── Summary ──
print(); [print(l) for l in LOG]
total = PASS+FAIL; rate = PASS/max(total,1)*100
print(f'\n═ Total: {total} | PASS: {PASS} | FAIL: {FAIL} | RATE: {rate:.1f}% ═')
sys.exit(0 if FAIL==0 else 1)
test-data/test_platform_user_stories.py
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@@ -1,465 +0,0 @@
"""
cobol-java-v3 平台用户故事测试
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
测试对象: cobol-java-v3 平台自身（不是COBOL程序）
测试范围: 正常 / 异常 / 边界 / 缺陷 4类用户故事
执行: python -X utf8 test-data/test_platform_user_stories.py
"""
import sys, os, json, time, tempfile, shutil, traceback
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from data.diff_result import VerificationRun, FieldResult
from data.test_case import TestCase, TestSuite, SparkConfig
from data.field_tree import FieldTree
PASS = 0
FAIL = 0
ERRORS = []
def section(title):
print(f"\n{'─'*70}")
print(f" {title}")
print(f"{'─'*70}")
def test(name, category):
def decorator(fn):
global PASS, FAIL
try:
fn()
PASS += 1
print(f" [{category}] {name} → ✅ PASS")
except Exception as e:
FAIL += 1
tb = traceback.format_exc()[-300:]
ERRORS.append(f"{name}: {e}")
print(f" [{category}] {name} → ❌ FAIL: {e}")
print(f" {tb.split(chr(10))[-3]}")
return fn
return decorator
# ════════════════════════════════════════════
# 正常系 — Normal
# ════════════════════════════════════════════
section("N: 正常系ユーザーストーリー")
@test("VerificationRun 作成と全フィールド設定", "NORMAL")
def _():
vr = VerificationRun(program="TESTPGM", runner="native")
assert vr.program == "TESTPGM"
assert vr.runner == "native"
assert vr.timestamp != ""
vr.branch_rate = 0.95
vr.paragraph_rate = 1.0
vr.hina_type = "マッチング"
vr.quality_score = 0.85
vr.heal_retry = 1
assert vr.branch_rate == 0.95
assert vr.hina_type == "マッチング"
@test("TestCase 作成とフィールド設定", "NORMAL")
def _():
tc = TestCase(id="TC-001", fields={"BR-AMT": 1500, "BR-STATUS": "A"})
assert tc.id == "TC-001"
assert tc.fields["BR-AMT"] == 1500
assert tc.fields["BR-STATUS"] == "A"
assert tc.coverage_targets == []
@test("FieldResult 作成とステータス", "NORMAL")
def _():
fr = FieldResult(field_name="BR-AMT", status="PASS", cobol_value="1500", java_value="1500.00")
assert fr.field_name == "BR-AMT"
assert fr.status == "PASS"
fr.status = "MISMATCH"
assert fr.status == "MISMATCH"
@test("Config デフォルト値", "NORMAL")
def _():
from config import Config
c = Config()
assert c.quality_gate_mode == "warn"
assert c.runner_mode == "native"
assert c.dialect == "ibm"
assert c.gcov_enabled == False
assert c.max_quality_retries == 4
@test("Config from_toml 正常", "NORMAL")
def _():
from config import Config
c = Config.from_toml(path=Path(__file__).parent.parent / "aurak.toml")
assert c.project_name != "" or c.runner_mode != ""
@test("VerificationRun total_fields 計算", "NORMAL")
def _():
vr = VerificationRun(fields_matched=10, fields_mismatched=2)
assert vr.total_fields == 12
@test("HINA classifier L1: DB操作", "NORMAL")
def _():
from hina.classifier import detect_keyword
r = detect_keyword("EXEC SQL SELECT * FROM TABLE END-EXEC")
assert any("DB操作" in x[0] for x in r)
assert any(x[1] >= 0.95 for x in r)
@test("HINA classifier L1: CALL", "NORMAL")
def _():
from hina.classifier import detect_keyword
r = detect_keyword("CALL 'SUBPGM' USING A.\nLINKAGE SECTION.")
assert any("子程序调用" in x[0] for x in r)
@test("HINA strategy マッチングテンプレート", "NORMAL")
def _():
from hina.strategy import get_strategy
s = get_strategy("マッチング")
assert len(s["required"]) == 9
@test("Quality gate: 合格", "NORMAL")
def _():
from hina.gate import check
r = check([{"a": 1}], {}, {"branch_rate": 0.95, "paragraph_rate": 1.0, "uncovered_decision_ids": []})
assert r["passed"] == True
@test("RetryHandler: 即PASS", "NORMAL")
def _():
from hina.retry import RetryHandler
h = RetryHandler()
vr = h.run(lambda: VerificationRun(status="PASS"))
assert vr.status == "PASS"
assert vr.heal_retry == 0
@test("ReportGenerator: HTML生成", "NORMAL")
def _():
from report.generator import ReportGenerator
vr = VerificationRun(program="TEST", runner="native")
rd = Path(tempfile.mkdtemp())
try:
g = ReportGenerator()
p = g.generate_html(vr, rd / "test.html")
assert p.exists()
html = p.read_text(encoding="utf-8")
assert "TEST" in html
finally:
shutil.rmtree(rd)
@test("ReportGenerator: HTML カバレッジ表示", "NORMAL")
def _():
from report.generator import ReportGenerator
vr = VerificationRun(program="T1", paragraph_rate=0.9, branch_rate=0.85)
rd = Path(tempfile.mkdtemp())
try:
p = ReportGenerator().generate_html(vr, rd / "t.html")
html = p.read_text(encoding="utf-8")
assert "段落覆盖率" in html
assert "分支覆盖率" in html
finally:
shutil.rmtree(rd)
@test("ReportGenerator: HTML HINA表示", "NORMAL")
def _():
from report.generator import ReportGenerator
vr = VerificationRun(program="T2", hina_type="マッチング", hina_confidence=0.95)
rd = Path(tempfile.mkdtemp())
try:
p = ReportGenerator().generate_html(vr, rd / "t.html")
assert "HINA" in p.read_text(encoding="utf-8")
finally:
shutil.rmtree(rd)
@test("ReportGenerator: JSON 新フィールド", "NORMAL")
def _():
from report.generator import ReportGenerator
vr = VerificationRun(program="T3", branch_rate=0.9, quality_score=0.85)
rd = Path(tempfile.mkdtemp())
try:
p = ReportGenerator().generate_json(vr, rd / "t.json")
d = json.loads(p.read_text())
assert d["branch_rate"] == 0.9
assert d["quality_score"] == 0.85
finally:
shutil.rmtree(rd)
@test("cobol_testgen extract_structure: IF", "NORMAL")
def _():
from cobol_testgen import extract_structure
s = extract_structure("PROCEDURE DIVISION.\nIF A>B MOVE 1 TO C ELSE MOVE 2 TO C.\nGOBACK.")
assert "paragraphs" in s
assert "decision_points" in s
# ════════════════════════════════════════════
# 異常系 — Abnormal
# ════════════════════════════════════════════
section("A: 異常系ユーザーストーリー")
@test("空COBOLソース→extract_structure", "ABNORMAL")
def _():
from cobol_testgen import extract_structure
s = extract_structure("")
assert s is not None
assert s.get("total_branches", 0) == 0
@test("PROCEDURE DIVISIONなし→extract_structure", "ABNORMAL")
def _():
from cobol_testgen import extract_structure
s = extract_structure("IDENTIFICATION DIVISION.\nPROGRAM-ID. X.\nDATA DIVISION.\nWORKING-STORAGE SECTION.\n01 A PIC X(10).")
assert s is not None
assert "paragraphs" in s
@test("Quality gate: 空データ", "ABNORMAL")
def _():
from hina.gate import check
r = check([], {}, {"branch_rate": 0.0, "paragraph_rate": 0.0, "uncovered_decision_ids": []})
assert r["passed"] == False
assert "no_data" in r.get("issues", {})
@test("Quality gate: 分岐不足", "ABNORMAL")
def _():
from hina.gate import check
r = check([{"x": 1}], {}, {"branch_rate": 0.5, "paragraph_rate": 1.0, "uncovered_decision_ids": [1, 2]})
assert r["passed"] == False
assert "decision_gaps" in r.get("issues", {})
@test("RetryHandler: 全FAIL→FATAL", "ABNORMAL")
def _():
from hina.retry import RetryHandler
from data.diff_result import VerificationRun
h = RetryHandler(max_heal=1, max_simple=1)
vr = h.run(lambda: VerificationRun(status="ERROR", exit_code=3))
assert vr.status == "FATAL"
assert vr.exit_code == 4
@test("Config: 必須fieldなし", "ABNORMAL")
def _():
from config import Config
c = Config.from_toml(path="nonexistent.toml")
assert c.runner_mode == "native"
assert c.quality_gate_mode == "warn"
@test("extract_structure: 不正COBOL構文", "ABNORMAL")
def _():
from cobol_testgen import extract_structure
s = extract_structure("THIS IS NOT VALID COBOL @@@ @@@")
assert s is not None
@test("generate_data: 分岐なしプログラム", "ABNORMAL")
def _():
from cobol_testgen import generate_data
s = "PROCEDURE DIVISION.\nGOBACK."
r = generate_data(s)
assert isinstance(r, list)
assert len(r) == 0
@test("incremental_supplement: 存在しないID", "ABNORMAL")
def _():
from cobol_testgen import incremental_supplement
r = incremental_supplement(None, [-1])
assert isinstance(r, list)
@test("VerificationRun: 空フィールド", "ABNORMAL")
def _():
vr = VerificationRun()
assert vr.total_fields == 0
assert vr.status == "PASS"
@test("HINA classifier: キーワードなし", "ABNORMAL")
def _():
from hina.classifier import compute_confidence
r = compute_confidence("PROCEDURE DIVISION.\nDISPLAY 'HELLO'.")
assert r["category"] == "unknown"
assert r["confidence"] == 0.0
@test("HINA strategy: 未知のタイプ", "ABNORMAL")
def _():
from hina.strategy import get_strategy
s = get_strategy("UNKNOWN_TYPE_XXX")
assert s["required"] == []
@test("gcov_collector: ファイルなし", "ABNORMAL")
def _():
from hina.gcov_collector import collect_gcov
r = collect_gcov(Path("nonexistent.cbl"), Path("/dev/null"))
assert r["available"] == False
assert "reason" in r
# ════════════════════════════════════════════
# 境界系 — Boundary
# ════════════════════════════════════════════
section("B: 境界系ユーザーストーリー")
@test("超巨大プログラム: 1000個IF", "BOUNDARY")
def _():
from cobol_testgen import extract_structure
lines = ["PROCEDURE DIVISION."]
for i in range(1000):
lines.append(f"IF A > {i} THEN MOVE {i} TO X ELSE MOVE {i} TO Y END-IF.")
lines.append("GOBACK.")
src = "\n".join(lines)
t0 = time.time()
s = extract_structure(src)
elapsed = time.time() - t0
print(f" → 1000 IF: {elapsed:.1f}s, 安定")
assert s is not None
assert elapsed < 10 # 10秒以内に完了
@test("超長フィールド名: 1000文字", "BOUNDARY")
def _():
from cobol_testgen import extract_structure
long = "A" * 1000
src = f"""IDENTIFICATION DIVISION.
PROGRAM-ID. X.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 {long} PIC X(10).
PROCEDURE DIVISION.
GOBACK."""
s = extract_structure(src)
assert s is not None
@test("TestSuite 0件", "BOUNDARY")
def _():
ts = TestSuite()
assert ts.has_spark == False
assert len(ts.test_cases) == 0
@test("SparkConfig 大量レコード", "BOUNDARY")
def _():
from data.test_case import SparkConfig
sc = SparkConfig(num_records=100000)
assert sc.num_records == 100000
@test("VerificationRun 全フィールド最大値", "BOUNDARY")
def _():
vr = VerificationRun(fields_matched=9999, fields_mismatched=9999)
assert vr.total_fields == 19998
vr.branch_rate = 1.0
vr.quality_score = 1.0
assert vr.branch_rate == 1.0
@test("100並列TestCases作成", "BOUNDARY")
def _():
cases = [TestCase(id=f"TC-{i:04d}", fields={"X": i}) for i in range(100)]
assert len(cases) == 100
assert cases[0].id == "TC-0000"
assert cases[99].id == "TC-0099"
# ════════════════════════════════════════════
# 欠陥系 — Defect (過去修正したバグの回帰)
# ════════════════════════════════════════════
section("D: 欠陥系ユーザーストーリー (回帰テスト)")
@test("DEFECT-001:complete_tests→DataWriter", "DEFECT")
def _():
"""P1修复: complete_tests 必须传递给 DataWriter"""
from data.test_case import TestCase
tc = TestCase(id="CTG-0001", fields={"TX-AMT": 100})
assert tc.id == "CTG-0001"
assert tc.fields["TX-AMT"] == 100
# DataWriter 接受 TestCase[]
from data.test_case import TestSuite
ts = TestSuite(test_cases=[tc])
assert len(ts.test_cases) == 1
@test("DEFECT-002:质量门禁循环中同步更新", "DEFECT")
def _():
"""P2修复: 增量补充后complete_tests需要更新"""
from data.test_case import TestCase
base = [TestCase(id=f"B{i}", fields={"v": i}) for i in range(3)]
delta = [TestCase(id=f"D{i}", fields={"v": i+10}) for i in range(2)]
combined = base + delta
assert len(combined) == 5
assert combined[3].id == "D0"
@test("DEFECT-003:分层重试 heal恢复", "DEFECT")
def _():
"""分层重试: heal修复后应成功"""
from hina.retry import RetryHandler
from data.diff_result import VerificationRun
called = [0]
def fn():
called[0] += 1
if called[0] <= 2:
return VerificationRun(status="BLOCKED", exit_code=2,
debug={"cobol_build": {"log": "not found"}})
return VerificationRun(status="PASS")
h = RetryHandler(max_heal=3, max_simple=1)
vr = h.run(fn)
assert vr.status == "PASS"
assert vr.heal_retry > 0
@test("DEFECT-004:COPYBOOKファイル名不一致", "DEFECT")
def _():
"""修复: COPY BBBBBFC (5B+FC) の解決"""
from cobol_testgen.read import resolve_copybooks
src = " COPY BBBBBFC REPLACING ==(A)== BY ==R01==."
# copybookファイルがなくてもクラッシュしない
result = resolve_copybooks(src, "/nonexistent")
assert result is not None
@test("DEFECT-005:Lark VALUE句解析", "DEFECT")
def _():
"""修复: VALUE '文字' のLark解析"""
from cobol_testgen import extract_structure
src = "IDENTIFICATION DIVISION.\nPROGRAM-ID. X.\nDATA DIVISION.\nWORKING-STORAGE SECTION.\n01 A PIC X(10) VALUE 'TEST'.\nPROCEDURE DIVISION.\nGOBACK."
s = extract_structure(src)
assert s is not None
@test("DEFECT-006:OPEN方向OUTPUT誤認識", "DEFECT")
def _():
"""修复: OPEN方向キーワードがファイル名に含まれない"""
from cobol_testgen.read import scan_open_statements
src = "OPEN INPUT TRANS-FILE.\nOPEN OUTPUT OUTPUT-FILE."
dirs = scan_open_statements(src)
# 'OUTPUT'は方向キーワードとして除外され、ファイル名にはならない
assert 'OUTPUT' not in dirs # キーワードはフィルタされる
assert 'OUTPUT-FILE' in dirs
assert dirs['OUTPUT-FILE'] == 'OUTPUT'
@test("DEFECT-007:Enum値一致判定", "DEFECT")
def _():
"""HINA分類のmethodキー存在確認"""
from hina.classifier import compute_confidence
r = compute_confidence("EXEC SQL SELECT\nEND-EXEC.")
assert "method" in r
assert r["method"] == "keyword"
r2 = compute_confidence("DISPLAY 'X'.")
assert r2["method"] == "none"
@test("DEFECT-008:machine_json全フィールド", "DEFECT")
def _():
"""P5修复: machine_jsonに全フィールド含む"""
from report.generator import ReportGenerator
vr = VerificationRun(program="TEST", branch_rate=0.9, paragraph_rate=0.8,
quality_score=0.85, hina_type="M", hina_confidence=0.95)
rd = Path(tempfile.mkdtemp())
try:
p = ReportGenerator().generate_machine_json(vr, rd / "m.json")
d = json.loads(p.read_text())
assert "branch_rate" in d
assert "paragraph_rate" in d
assert "quality_score" in d
assert "hina_type" in d
finally:
shutil.rmtree(rd)
# ════════════════════════════════════════════
# 集計
# ════════════════════════════════════════════
section("テスト結果集計")
total = PASS + FAIL
print(f"\n 総テスト数: {total}")
print(f" 合格: {PASS}")
print(f" 不合格: {FAIL}")
print(f" 合格率: {PASS/max(total,1)*100:.1f}%")
print(f"\n RESULT: {'ALL PASSED' if FAIL==0 else 'SOME FAILED'}")
if ERRORS:
print(f"\n 失敗詳細:")
for e in ERRORS:
print(f" ❌ {e}")
sys.exit(0 if FAIL == 0 else 1)
test_llm.py
-17
View File
@@ -1,17 +0,0 @@
import json, os, sys
sys.path.insert(0, ".")
os.environ["LLM_API_KEY"] = "sk-ca4961087c7f4aefa8ed0fc6f3d02329"
os.environ["LLM_API_BASE"] = "https://api.deepseek.com/v1"
from agents.llm import LLMClient
import time
c = LLMClient(model="deepseek-chat", timeout=30)
t0 = time.time()
r = c.call([
{"role":"system","content":"Parse this COBOL COPYBOOK into JSON: {\"fields\":[{\"name\":\"...\",\"level\":N,\"pic\":\"...\",\"usage\":\"DISPLAY|COMP-3\",\"length\":N}]}"},
{"role":"user","content": open("uploads/ec17bf32/copybook.cpy").read()}
])
print(f"LLM call OK ({time.time()-t0:.1f}s)")
print(r[:500])
test_pipeline.py
-52
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@@ -1,52 +0,0 @@
import json, os, sys, traceback
sys.path.insert(0, ".")
os.environ["LLM_API_KEY"] = "sk-ca4961087c7f4aefa8ed0fc6f3d02329"
os.environ["LLM_API_BASE"] = "https://api.deepseek.com/v1"
from config import Config
from orchestrator import run_pipeline
cfg = Config()
cfg.llm_model = "deepseek-chat"
cfg.runner_mode = "native"
print("STEP 1: Reading copybook...")
cp = "uploads/ec17bf32/copybook.cpy"
with open(cp) as f:
text = f.read()
print(f" Copybook text ({len(text)} chars):\n{text}")
print("\nSTEP 2: Agent1Parser (LLM)...")
from agents.agent1_parser import Agent1Parser
from agents.llm import LLMClient
try:
llm = LLMClient(model="deepseek-chat", timeout=30)
tree = Agent1Parser(llm).parse(text)
fields = tree.flatten()
print(f" Fields parsed: {list(fields.keys())}")
for name, f in fields.items():
print(f" {name}: level={f.level}, pic={f.pic}, usage={f.usage}, offset={f.offset}, len={f.length}")
except Exception as e:
print(f" ERROR: {e}")
traceback.print_exc()
print("\nSTEP 3: Full orchestrator...")
try:
vr = run_pipeline(cfg, cp, "uploads/ec17bf32/program.cbl",
"uploads/ec17bf32/java", "uploads/ec17bf32/mapping.yaml")
print(f" Status: {vr.status} (exit_code={vr.exit_code})")
print(f" Program: {vr.program}")
print(f" Matched: {vr.fields_matched}")
print(f" Mismatched: {vr.fields_mismatched}")
print(f" Duration: {vr.duration_s:.1f}s")
print(f" Debug keys: {list(vr.debug.keys())}")
print(f" Debug details:")
for k, v in vr.debug.items():
if v:
if isinstance(v, dict):
print(f" {k}: {'OK' if v.get('ok') else 'FAIL'} {str(v.get('log',''))[-200:]}")
else:
print(f" {k}: {v}")
except Exception as e:
print(f" ERROR: {e}")
traceback.print_exc()
tests/agents/test_agents.py
-151
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@@ -1,151 +0,0 @@
"""AG-01~12: Agents 模块"""
import sys, os, json, tempfile
from pathlib import Path
from unittest.mock import MagicMock, patch
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from agents.llm import LLMClient
from agents.agent1_parser import Agent1Parser
from agents.agent2_data import Agent2Data
from agents.agent3_diagnostic import Agent3Diagnostic
from data.diff_result import FieldResult
def _llm_client(cache_dir=None):
if cache_dir is None:
cache_dir = tempfile.mkdtemp()
return LLMClient(model="test", cache_dir=cache_dir)
def _mock_response(content="resp"):
m = MagicMock()
m.json.return_value = {"choices": [{"message": {"content": content}}]}
m.raise_for_status.return_value = None
return m
# ── AG-01~05: LLMClient ──
def test_llm_call_returns_string():
"""AG-01: call 返回字符串"""
client = _llm_client()
with patch("httpx.post", return_value=_mock_response("hello")):
assert client.call([{"role": "user", "content": "hi"}]) == "hello"
def test_llm_cache_hit():
"""AG-02: 相同消息 → 缓存命中"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
with patch("httpx.post", return_value=_mock_response("resp1")):
client.call([{"role": "user", "content": "ping"}])
with patch("httpx.post") as mock_post:
result = client.call([{"role": "user", "content": "ping"}])
assert result == "resp1"
mock_post.assert_not_called()
def test_llm_timeout():
"""AG-03: 超时 → 抛出异常"""
client = _llm_client()
with patch("httpx.post", side_effect=Exception("timeout")):
import pytest
with pytest.raises(Exception):
client.call([{"role": "user", "content": "hi"}], retries=0)
def test_llm_retry_success():
"""AG-04: 首次失败, 重试成功"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
call_n = [0]
def _side(*a, **kw):
call_n[0] += 1
if call_n[0] == 1:
raise Exception("first fail")
return _mock_response("ok")
with patch("httpx.post", side_effect=_side):
result = client.call([{"role": "user", "content": "retry"}], retries=1)
assert result == "ok"
def test_llm_retry_exhausted():
"""AG-05: 重试用完 → 抛出"""
client = _llm_client()
with patch("httpx.post", side_effect=Exception("fail")):
import pytest
with pytest.raises(Exception):
client.call([{"role": "user", "content": "x"}], retries=0)
# ── AG-06~08: Agent1Parser ──
def test_agent1_parse_valid():
"""AG-06: 合法 COPYBOOK 字段"""
llm = MagicMock()
llm.call.return_value = json.dumps({
"fields": [
{"name": "WS-A", "level": 5, "pic": "9(4)", "length": 4, "offset": 0},
]
})
tree = Agent1Parser(llm).parse("text")
assert "WS-A" in tree.flatten()
def test_agent1_parse_bad_json():
"""AG-07: 非法 JSON → parse_error"""
llm = MagicMock()
llm.call.return_value = "not json"
tree = Agent1Parser(llm).parse("x")
assert tree.copybook_name == "parse_error"
def test_agent1_parse_empty():
"""AG-08: JSON 缺 fields"""
llm = MagicMock()
llm.call.return_value = json.dumps({})
tree = Agent1Parser(llm).parse("x")
assert len(tree.fields) >= 0
# ── AG-09~11: Agent2Data ──
def test_agent2_design_normal():
"""AG-09: 正常 → TestSuite"""
llm = MagicMock()
llm.call.return_value = json.dumps({"test_cases": [{"id": "TC-1", "fields": {"A": 1}}]})
from data.field_tree import FieldTree, Field
suite = Agent2Data(llm).design(FieldTree(fields=[Field(name="A", level=5, pic="9(4)")]))
assert suite is not None
def test_agent2_design_fallback():
"""AG-10: LLM 返回非法 JSON → try/except 进入 fallback"""
llm = MagicMock()
llm.call.return_value = "not-json"
from data.field_tree import FieldTree
suite = Agent2Data(llm).design(FieldTree(fields=[]))
# json.loads 抛出 JSONDecodeError, 被 except 捕获, 返回 TC-FALLBACK
assert len(suite.test_cases) >= 1
assert suite.test_cases[0].id == "TC-FALLBACK"
def test_agent2_design_spark():
"""AG-11: spark_mode → SparkConfig"""
llm = MagicMock()
llm.call.return_value = json.dumps({"test_cases": []})
from data.field_tree import FieldTree
suite = Agent2Data(llm).design(FieldTree(fields=[]), spark_mode=True)
assert suite.has_spark is True
# ── AG-12: Agent3Diagnostic ──
def test_agent3_analyze():
"""AG-12: MISMATCH → 诊断"""
llm = MagicMock()
llm.call.return_value = "rounding error"
fr = FieldResult(field_name="BR-AMT", status="MISMATCH",
cobol_value="1500000", java_value="1499999.99")
r = Agent3Diagnostic(llm).analyze(fr)
assert isinstance(r, str) and len(r) > 0
tests/agents/test_llm_deep.py
-265
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@@ -1,265 +0,0 @@
"""LLMClient deep resilience testing — HTTP status codes, cache failures, concurrency, retries."""
import sys, os, json, time, threading, tempfile
from pathlib import Path
from unittest.mock import MagicMock, patch
import httpx
import pytest
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from agents.llm import LLMClient
def _llm_client(cache_dir=None):
if cache_dir is None:
cache_dir = tempfile.mkdtemp()
return LLMClient(model="test", cache_dir=cache_dir)
def _mock_response(content="resp"):
m = MagicMock()
m.json.return_value = {"choices": [{"message": {"content": content}}]}
m.raise_for_status.return_value = None
return m
def _make_http_error(status_code, message=None):
"""Build an httpx.HTTPStatusError that raise_for_status can raise."""
request = httpx.Request("POST", "http://localhost/chat/completions")
response = httpx.Response(status_code=status_code, request=request)
return httpx.HTTPStatusError(
message or f"{status_code} error",
request=request,
response=response,
)
# ══════════════════════════════════════════════════════════════════════
# HTTP Status Code Handling
# ══════════════════════════════════════════════════════════════════════
def test_401_unauthorized():
"""401 Unauthorized -> exception propagates with correct status code"""
client = _llm_client()
error = _make_http_error(401, "Unauthorized")
resp = _mock_response()
resp.raise_for_status.side_effect = error
with patch("httpx.post", return_value=resp):
with pytest.raises(httpx.HTTPStatusError) as exc:
client.call([{"role": "user", "content": "hi"}], retries=0)
assert exc.value.response.status_code == 401
def test_429_rate_limit():
"""429 Rate Limit -> exception propagates after retries exhausted"""
client = _llm_client()
error = _make_http_error(429, "Too Many Requests")
resp = _mock_response()
resp.raise_for_status.side_effect = error
with patch("httpx.post", return_value=resp):
with pytest.raises(httpx.HTTPStatusError) as exc:
client.call([{"role": "user", "content": "hi"}], retries=1)
assert exc.value.response.status_code == 429
def test_503_service_unavailable():
"""503 Service Unavailable -> exception propagates with correct status code"""
client = _llm_client()
error = _make_http_error(503, "Service Unavailable")
resp = _mock_response()
resp.raise_for_status.side_effect = error
with patch("httpx.post", return_value=resp):
with pytest.raises(httpx.HTTPStatusError) as exc:
client.call([{"role": "user", "content": "hi"}], retries=0)
assert exc.value.response.status_code == 503
def test_network_timeout():
"""httpx.TimeoutException -> exception propagates"""
client = _llm_client()
with patch("httpx.post", side_effect=httpx.TimeoutException("Connection timed out")):
with pytest.raises(httpx.TimeoutException):
client.call([{"role": "user", "content": "hi"}], retries=0)
# ══════════════════════════════════════════════════════════════════════
# Cache Behaviors
# ══════════════════════════════════════════════════════════════════════
def test_cache_disk_full_falls_through():
"""Cache disk full (_set raises OSError) -> call() retries and still returns value"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
original_set = client._set
set_attempts = [0]
def flaky_set(k, v):
set_attempts[0] += 1
if set_attempts[0] <= 1:
raise OSError("No space left on device")
original_set(k, v)
with patch("httpx.post", return_value=_mock_response("hello")):
with patch.object(client, "_set", side_effect=flaky_set):
result = client.call([{"role": "user", "content": "hi"}], retries=1)
assert result == "hello"
# First _set call failed (caught by retry), second succeeded
assert set_attempts[0] == 2
def test_cache_corrupted_file():
"""Corrupted cache .json -> cache miss, API called instead"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
messages = [{"role": "user", "content": "corrupt-test"}]
# Write a corrupted JSON file where the cache entry would be
k = client._key(messages)
cache_path = Path(tmp) / f"{k}.json"
cache_path.write_text("not valid json{{{")
with patch("httpx.post", return_value=_mock_response("from-api")) as mock_post:
result = client.call(messages, retries=0)
assert result == "from-api"
mock_post.assert_called_once()
def test_multiple_cache_files():
"""Multiple distinct messages create separate cache files with correct key structure"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
msgs_a = [{"role": "user", "content": "alpha"}]
msgs_b = [{"role": "user", "content": "beta"}]
with patch("httpx.post", side_effect=[_mock_response("resp-a"), _mock_response("resp-b")]):
client.call(msgs_a, retries=0)
client.call(msgs_b, retries=0)
cached = list(Path(tmp).iterdir())
assert len(cached) == 2
keys = {p.stem for p in cached}
assert client._key(msgs_a) in keys
assert client._key(msgs_b) in keys
# Each file is valid JSON with the expected structure
for p in cached:
data = json.loads(p.read_text())
assert "response" in data
def test_empty_cache_dir_on_init():
"""Init with fresh empty directory -> mkdir creates it; re-init with existing dir works"""
with tempfile.TemporaryDirectory() as tmp:
cache_sub = Path(tmp) / "nested" / "cache"
assert not cache_sub.exists()
client = LLMClient(model="test", cache_dir=str(cache_sub))
assert cache_sub.exists()
assert cache_sub.is_dir()
# Second init with same directory (exist_ok=True) should not fail
client2 = LLMClient(model="test", cache_dir=str(cache_sub))
assert cache_sub.exists()
# ══════════════════════════════════════════════════════════════════════
# Concurrency
# ══════════════════════════════════════════════════════════════════════
def test_concurrent_same_message():
"""Two threads calling call() with same message -> both return same result"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
messages = [{"role": "user", "content": "concurrent"}]
call_count_lock = threading.Lock()
api_call_count = [0]
def api_side(*a, **kw):
with call_count_lock:
api_call_count[0] += 1
time.sleep(0.05) # small delay so threads overlap
return _mock_response("shared-result")
results = [None, None]
errors = [None, None]
barrier = threading.Barrier(2, timeout=5)
def _call(idx):
try:
barrier.wait() # both threads start simultaneously
results[idx] = client.call(messages, retries=0)
except Exception as e:
errors[idx] = e
with patch("httpx.post", side_effect=api_side):
t1 = threading.Thread(target=_call, args=(0,))
t2 = threading.Thread(target=_call, args=(1,))
t1.start()
t2.start()
t1.join()
t2.join()
assert errors[0] is None, f"Thread 0 error: {errors[0]}"
assert errors[1] is None, f"Thread 1 error: {errors[1]}"
assert results[0] == "shared-result"
assert results[1] == "shared-result"
# With the barrier both threads race through _get before either writes,
# so both make an API call. Correctness (same result) is the key assertion.
assert api_call_count[0] == 2
# ══════════════════════════════════════════════════════════════════════
# Retry Behavior
# ══════════════════════════════════════════════════════════════════════
def test_retry_3_two_fail_then_success():
"""retries=3, first 2 call attempts fail, 3rd succeeds -> result from 3rd"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
call_n = [0]
def _side(*a, **kw):
call_n[0] += 1
if call_n[0] <= 2:
raise Exception(f"fail #{call_n[0]}")
return _mock_response("ok-on-3rd")
with patch("httpx.post", side_effect=_side):
result = client.call([{"role": "user", "content": "x"}], retries=3)
assert result == "ok-on-3rd"
assert call_n[0] == 3 # exactly 3 attempts made
def test_retries_0_immediate_failure():
"""retries=0, first call fails -> immediate exception"""
client = _llm_client()
with patch("httpx.post", side_effect=ValueError("api exploded")):
with pytest.raises(ValueError, match="api exploded"):
client.call([{"role": "user", "content": "x"}], retries=0)
def test_cache_hit_then_eviction_then_retry():
"""Cache hit -> eviction -> cache miss -> API first fail -> retry succeed"""
with tempfile.TemporaryDirectory() as tmp:
client = _llm_client(tmp)
messages = [{"role": "user", "content": "evict-and-retry"}]
k = client._key(messages)
cache_path = Path(tmp) / f"{k}.json"
# Prime cache with a known value
cache_path.write_text(json.dumps({"response": "cached"}))
# Verify cache hit (no API call made)
with patch("httpx.post") as mock_post:
r1 = client.call(messages, retries=0)
assert r1 == "cached"
mock_post.assert_not_called()
# Evict the cache file
cache_path.unlink()
# Now: cache miss -> first API call fails -> retry succeeds
call_n = [0]
def _side(*a, **kw):
call_n[0] += 1
if call_n[0] == 1:
raise Exception("first fail after eviction")
return _mock_response("after-eviction-ok")
with patch("httpx.post", side_effect=_side):
r2 = client.call(messages, retries=1)
assert r2 == "after-eviction-ok"
tests/cobol_testgen/__init__.py
View File
tests/cobol_testgen/test_cond.py
-241
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@@ -1,241 +0,0 @@
"""CO-01~10: cobol_testgen cond 模块 — 条件表达式解析 + MC/DC"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.cond import (
parse_single_condition, parse_compound_condition,
collect_leaves, evaluate_tree, mcdc_sets, is_field,
)
from cobol_testgen.models import CondLeaf, CondAnd, CondOr, CondNot
# ── CO-01~02: parse_single_condition ──
def test_parse_single_numeric():
"""CO-01: 数值比较 AMOUNT > 100"""
r = parse_single_condition("AMOUNT > 100")
assert r is not None
assert r[0] == "AMOUNT"
assert r[1] == ">"
assert r[2] == "100"
def test_parse_single_string():
"""CO-02: 文字列比较 B = 'Y'"""
r = parse_single_condition("B = 'Y'")
assert r is not None
assert r[0] == "B"
assert r[1] == "="
assert r[2] == "Y"
def test_parse_single_subscript():
"""带下标的字段 WS-ITEM(SUB) = 'A'"""
r = parse_single_condition("WS-ITEM(SUB) = 'A'")
assert r is not None
assert r[2] == "A"
def test_parse_single_88_level():
"""88-level 条件名分解"""
fields = [{"is_88": True, "name": "STATUS-APPROVED", "parent": "WS-TRAN-STATUS", "value": "A"}]
r = parse_single_condition("STATUS-APPROVED", fields)
assert r is not None
assert r[0] == "WS-TRAN-STATUS"
assert r[2] == "A"
def test_parse_single_compound_returns_none():
"""包含 AND/OR 返回 None"""
assert parse_single_condition("A > 0 AND B < 5") is None
def test_parse_single_unknown_returns_none():
"""无法解析的表达式返回 None"""
assert parse_single_condition("NOT A") is None
# ── CO-03~05: parse_compound_condition ──
def test_compound_and():
"""CO-03: A > 0 AND B < 5 → CondAnd"""
r = parse_compound_condition("A > 0 AND B < 5")
assert r is not None
assert isinstance(r, CondAnd)
assert isinstance(r.left, CondLeaf)
assert isinstance(r.right, CondLeaf)
def test_compound_or():
"""CO-04: A = 1 OR B = 2 → CondOr"""
r = parse_compound_condition("A = 1 OR B = 2")
assert r is not None
assert isinstance(r, CondOr)
assert isinstance(r.left, CondLeaf)
assert isinstance(r.right, CondLeaf)
def test_compound_nested_and_or():
"""CO-05: (A > 0 AND B < 5) OR C = 1 → AND优先于OR"""
r = parse_compound_condition("(A > 0 AND B < 5) OR C = 1")
assert r is not None
assert isinstance(r, CondOr)
assert isinstance(r.left, CondAnd)
assert isinstance(r.right, CondLeaf)
def test_compound_not():
"""NOT 前缀"""
r = parse_compound_condition("NOT A = 1")
assert r is not None
assert isinstance(r, CondNot)
assert isinstance(r.child, CondLeaf)
def test_compound_empty():
"""空字符串返回 None"""
assert parse_compound_condition("") is None
def test_compound_paren_wrap():
"""外层括号剥离"""
r = parse_compound_condition("(A > 0)")
assert isinstance(r, CondLeaf)
# ── collect_leaves ──
def test_collect_leaves_and():
"""AND 树收集所有叶子"""
tree = CondAnd(CondLeaf("A", ">", "0"), CondLeaf("B", "<", "5"))
leaves = collect_leaves(tree)
assert len(leaves) == 2
def test_collect_leaves_not():
"""NOT 树收集子叶子"""
tree = CondNot(CondLeaf("A", "=", "1"))
leaves = collect_leaves(tree)
assert len(leaves) == 1
# ── evaluate_tree ──
def test_evaluate_leaf_true():
"""叶子节点求值"""
leaf = CondLeaf("A", ">", "0")
assert evaluate_tree(leaf, {leaf: True}) is True
assert evaluate_tree(leaf, {leaf: False}) is False
def test_evaluate_and_true():
"""AND 全部 True → True"""
l1 = CondLeaf("A", ">", "0")
l2 = CondLeaf("B", "<", "5")
tree = CondAnd(l1, l2)
assert evaluate_tree(tree, {l1: True, l2: True}) is True
def test_evaluate_and_false():
"""AND 任一 False → False"""
l1 = CondLeaf("A", ">", "0")
l2 = CondLeaf("B", "<", "5")
tree = CondAnd(l1, l2)
assert evaluate_tree(tree, {l1: True, l2: False}) is False
def test_evaluate_or_true():
"""OR 任一 True → True"""
l1 = CondLeaf("A", "=", "1")
l2 = CondLeaf("B", "=", "2")
tree = CondOr(l1, l2)
assert evaluate_tree(tree, {l1: True, l2: False}) is True
def test_evaluate_or_false():
"""OR 全部 False → False"""
l1 = CondLeaf("A", "=", "1")
l2 = CondLeaf("B", "=", "2")
tree = CondOr(l1, l2)
assert evaluate_tree(tree, {l1: False, l2: False}) is False
def test_evaluate_not():
"""NOT 反转"""
leaf = CondLeaf("A", "=", "1")
tree = CondNot(leaf)
assert evaluate_tree(tree, {leaf: True}) is False
assert evaluate_tree(tree, {leaf: False}) is True
# ── CO-06~08: mcdc_sets ──
def test_mcdc_single_leaf_returns_none():
"""CO-06: 单条件 (IF A > 100) → None (不需要 MC/DC)"""
tree = CondLeaf("A", ">", "100")
assert mcdc_sets(tree) is None
def test_mcdc_and():
"""CO-07: AND (A > 0 AND B < 5) → 3 sets (MC/DC)"""
tree = CondAnd(CondLeaf("A", ">", "0"), CondLeaf("B", "<", "5"))
sets = mcdc_sets(tree)
assert sets is not None
# AND 需要 3 个测试对: TT→T, TF→F, FT→F
# 实际上 mcdc_sets 返回约束集，包含 True/False 决策
decisions = set(d for _, d in sets)
assert True in decisions
assert False in decisions
# 各叶子应有独立影响
all_constraints = [c for constraints, _ in sets for c in constraints]
fields_involved = set(c[0] for c in all_constraints)
assert "A" in fields_involved
assert "B" in fields_involved
def test_mcdc_or():
"""CO-08: OR (A = 1 OR B = 2) → 3 sets (MC/DC)"""
tree = CondOr(CondLeaf("A", "=", "1"), CondLeaf("B", "=", "2"))
sets = mcdc_sets(tree)
assert sets is not None
decisions = set(d for _, d in sets)
assert True in decisions
assert False in decisions
# ── is_field ──
def test_is_field_match():
"""字段名匹配"""
fields = [{"name": "WS-AMOUNT"}, {"name": "WS-STATUS"}]
assert is_field("WS-AMOUNT", fields) is True
def test_is_field_subscript():
"""带下标字段名匹配"""
fields = [{"name": "WS-ITEM-STATUS"}]
assert is_field("WS-ITEM-STATUS(WS-INDEX)", fields) is True
def test_is_field_no_match():
"""未知字段名返回 False"""
fields = [{"name": "WS-AMOUNT"}]
assert is_field("WS-OTHER", fields) is False
# ── satisfying_value ──
def test_satisfying_value_greater():
"""数值 > 条件: 返回值应大于给定值"""
from cobol_testgen.cond import satisfying_value
info = {"type": "numeric", "digits": 7, "decimal": 0}
r = satisfying_value(info, ">", "100", want_true=True)
assert int(r) > 100
def test_satisfying_value_equal_false():
"""= 条件 want=False: 返回不同值"""
from cobol_testgen.cond import satisfying_value
info = {"type": "numeric", "digits": 7, "decimal": 0}
r = satisfying_value(info, "=", "100", want_true=False)
assert int(r) != 100
tests/cobol_testgen/test_cond_deep.py
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@@ -1,843 +0,0 @@
"""CO-DP-01~13: cobol_testgen cond 模块 — 深度条件测试 (MC/DC, 嵌套, 88-level, 性能)"""
import sys, os, time
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.cond import (
parse_single_condition, parse_compound_condition,
collect_leaves, evaluate_tree, mcdc_sets, satisfying_value,
)
from cobol_testgen.models import CondLeaf, CondAnd, CondOr, CondNot
# ══════════════════════════════════════════════════════════════════
# CO-DP-01: 3-layer nested AND/OR
# ══════════════════════════════════════════════════════════════════
def test_deep_nested_and_or_parse():
"""CO-DP-01: (A > 0 AND B < 5) OR (C = 1 AND NOT D > 10) — 3层嵌套解析"""
text = "(A > 0 AND B < 5) OR (C = 1 AND NOT D > 10)"
tree = parse_compound_condition(text)
assert tree is not None
# Root is CondOr
assert isinstance(tree, CondOr), f"Expected CondOr, got {type(tree).__name__}"
# Left leg: (A > 0 AND B < 5) → CondAnd
left = tree.left
assert isinstance(left, CondAnd), f"Left child expected CondAnd, got {type(left).__name__}"
assert isinstance(left.left, CondLeaf)
assert left.left.field == "A"
assert left.left.op == ">"
assert left.left.value == "0"
assert isinstance(left.right, CondLeaf)
assert left.right.field == "B"
assert left.right.op == "<"
assert left.right.value == "5"
# Right leg: (C = 1 AND NOT D > 10) → CondAnd(CondLeaf, CondNot(CondLeaf))
right = tree.right
assert isinstance(right, CondAnd), f"Right child expected CondAnd, got {type(right).__name__}"
assert isinstance(right.left, CondLeaf)
assert right.left.field == "C"
assert right.left.op == "="
assert right.left.value == "1"
assert isinstance(right.right, CondNot), f"Expected CondNot wrapping D, got {type(right.right).__name__}"
assert isinstance(right.right.child, CondLeaf)
assert right.right.child.field == "D"
assert right.right.child.op == ">"
assert right.right.child.value == "10"
# collect_leaves should return 4 leaves (NOT's child is still a leaf)
leaves = collect_leaves(tree)
assert len(leaves) == 4, f"Expected 4 leaves, got {len(leaves)}"
fields = [l.field for l in leaves]
assert "A" in fields and "B" in fields and "C" in fields and "D" in fields
def test_deep_nested_and_or_evaluate():
"""CO-DP-01b: evaluate_tree for 3-layer nested AND/OR"""
text = "(A > 0 AND B < 5) OR (C = 1 AND NOT D > 10)"
tree = parse_compound_condition(text)
leaves = collect_leaves(tree)
# Map field names to leaf objects
leaf_map = {l.field: l for l in leaves}
a = leaf_map["A"]
b = leaf_map["B"]
c = leaf_map["C"]
d = leaf_map["D"]
# (T AND T) OR (F AND NOT F) = T OR (F AND T) = T OR F = T
assert evaluate_tree(tree, {a: True, b: True, c: False, d: False}) is True
# (F AND T) OR (F AND NOT F) = F OR (F AND T) = F OR F = F
assert evaluate_tree(tree, {a: False, b: True, c: False, d: False}) is False
# (F AND F) OR (T AND NOT F) = F OR (T AND T) = F OR T = T
assert evaluate_tree(tree, {a: False, b: False, c: True, d: False}) is True
# (T AND T) OR (F AND NOT T) = T OR (F AND F) = T OR F = T
assert evaluate_tree(tree, {a: True, b: True, c: False, d: True}) is True
# (F AND F) OR (F AND NOT F) = F OR (F AND T) = F OR F = F
assert evaluate_tree(tree, {a: False, b: False, c: False, d: False}) is False
# (T AND T) OR (T AND NOT F) = T OR (T AND T) = T OR T = T
assert evaluate_tree(tree, {a: True, b: True, c: True, d: False}) is True
# (F AND T) OR (T AND NOT T) = F OR (T AND F) = F OR F = F
assert evaluate_tree(tree, {a: False, b: True, c: True, d: True}) is False
def test_deep_nested_and_or_mcdc():
"""CO-DP-01c: mcdc_sets for 3-layer nested AND/OR — should find >= 5 sets"""
text = "(A > 0 AND B < 5) OR (C = 1 AND NOT D > 10)"
tree = parse_compound_condition(text)
sets = mcdc_sets(tree)
assert sets is not None, "mcdc_sets should not return None for 4-leaf compound tree"
# With 4 leaves we expect at least 5 unique constraint sets
# (one "base" case + one showing independent effect per leaf at minimum)
assert len(sets) >= 5, f"Expected >= 5 MC/DC sets, got {len(sets)}"
assert len(sets) <= 8, f"Expected <= 8 MC/DC sets for 4-leaf, got {len(sets)}"
# Verify both True and False decision outcomes are present
decisions = set(d for _, d in sets)
assert True in decisions, "Should have True decision outcomes"
assert False in decisions, "Should have False decision outcomes"
# Verify all 4 leaves have their field referenced in constraints
all_field_names = set()
for constraints, _ in sets:
for c in constraints:
all_field_names.add(c[0])
for fname in ("A", "B", "C", "D"):
assert fname in all_field_names, f"Leaf {fname} not found in any MC/DC constraint"
# ══════════════════════════════════════════════════════════════════
# CO-DP-02: 88-level multi-value
# ══════════════════════════════════════════════════════════════════
def test_88_multi_value_resolve():
"""CO-DP-02: 88-level with multiple VALUES 'A' 'B' 'C' resolves to first value"""
fields = [
{
"is_88": True,
"name": "STATUS-VALID",
"parent": "WS-STATUS",
"value": "A",
"values": ["A", "B", "C"],
}
]
r = parse_single_condition("STATUS-VALID", fields)
assert r is not None, "88-level multi-value should resolve"
assert r[0] == "WS-STATUS", f"Expected parent WS-STATUS, got {r[0]}"
assert r[1] == "=", f"Expected operator '=', got {r[1]}"
# Current implementation uses f.get('value') which is the first value
assert r[2] == "A", f"Expected value 'A' (first in multi-value), got {r[2]}"
def test_88_multi_value_compound_parse():
"""CO-DP-02b: 88-level multi-value within compound expression"""
fields = [
{
"is_88": True,
"name": "STATUS-VALID",
"parent": "WS-STATUS",
"value": "A",
"values": ["A", "B", "C"],
},
{
"is_88": True,
"name": "AMOUNT-LARGE",
"parent": "WS-AMOUNT",
"value": "100",
},
]
tree = parse_compound_condition("STATUS-VALID AND AMOUNT-LARGE", fields)
assert tree is not None
assert isinstance(tree, CondAnd)
# Left: 88-level resolved to CondLeaf
assert isinstance(tree.left, CondLeaf)
assert tree.left.field == "WS-STATUS"
assert tree.left.value == "A"
assert tree.left.op == "="
# Right: 88-level resolved to CondLeaf
assert isinstance(tree.right, CondLeaf)
assert tree.right.field == "WS-AMOUNT"
assert tree.right.value == "100"
assert tree.right.op == "="
def test_88_multi_value_no_single_value():
"""CO-DP-02c: 88-level with only values[] (no single 'value') — current behavior"""
# Simulate a field that has values list but no single value key
fields = [
{
"is_88": True,
"name": "COLOR-RED",
"parent": "WS-COLOR",
"value": "RED",
}
]
r = parse_single_condition("COLOR-RED", fields)
assert r is not None
assert r[2] == "RED"
# Without a 'value' key, parse_single_condition returns empty string
fields_no_val = [
{
"is_88": True,
"name": "COLOR-RED",
"parent": "WS-COLOR",
"values": ["RED"],
}
]
# 'value' key missing entirely → f.get('value', '') returns ''
r2 = parse_single_condition("COLOR-RED", fields_no_val)
assert r2 is not None
assert r2[2] == "", f"Without value key, expected '', got '{r2[2]}'"
# ══════════════════════════════════════════════════════════════════
# CO-DP-03: Arithmetic expressions in conditions
# ══════════════════════════════════════════════════════════════════
def test_arithmetic_expr_add_mul():
"""CO-DP-03: A + B > C * 2 — arithmetic expression as leaf"""
r = parse_single_condition("A + B > C * 2")
assert r is not None, "Arithmetic expression A + B > C * 2 should parse"
# The field part is the whole left expression
assert "A + B" in r[0] or r[0] == "A + B", f"Expected left expr, got {r[0]}"
assert r[1] == ">", f"Expected operator '>', got {r[1]}"
assert "C * 2" in r[2] or r[2] == "C * 2", f"Expected right expr 'C * 2', got {r[2]}"
def test_arithmetic_expr_sub_eq():
"""CO-DP-03b: A - B = 5 — arithmetic expression with subtraction"""
r = parse_single_condition("A - B = 5")
assert r is not None, "Arithmetic expression A - B = 5 should parse"
assert r[1] == "=", f"Expected operator '=', got {r[1]}"
assert r[2] == "5", f"Expected value '5', got {r[2]}"
def test_arithmetic_expr_in_compound():
"""CO-DP-03c: Arithmetic expr in compound: X + Y > 10 OR A = 1"""
tree = parse_compound_condition("X + Y > 10 OR A = 1")
assert tree is not None
assert isinstance(tree, CondOr), f"Expected CondOr, got {type(tree).__name__}"
assert isinstance(tree.left, CondLeaf)
assert isinstance(tree.right, CondLeaf)
# Left leaf is the arithmetic expression
assert "X + Y" in tree.left.field or tree.left.field == "X + Y", \
f"Expected left expr 'X + Y', got '{tree.left.field}'"
assert tree.left.op == ">"
assert tree.right.field == "A"
assert tree.right.value == "1"
def test_arithmetic_expr_div():
"""CO-DP-03d: X / Y = 2 — division in condition"""
r = parse_single_condition("X / Y = 2")
assert r is not None, "X / Y = 2 should parse"
assert r[1] == "="
assert r[2] == "2"
# ══════════════════════════════════════════════════════════════════
# CO-DP-04: satisfying_value for ALL operators
# ══════════════════════════════════════════════════════════════════
def test_satisfying_value_numeric_all():
"""CO-DP-04: satisfying_value numeric — all 6 operators × want_true/False"""
info = {"type": "numeric", "digits": 7, "decimal": 0}
# --- want_true=True ---
# > should return value + 1
gt = satisfying_value(info, ">", "100", want_true=True)
assert int(gt) > 100, f"> want_true=True: expected >100, got {gt}"
# >= should return same (pass through)
ge = satisfying_value(info, ">=", "100", want_true=True)
assert int(ge) >= 100, f">= want_true=True: expected >=100, got {ge}"
# = should return same (pass through)
eq = satisfying_value(info, "=", "100", want_true=True)
assert int(eq) == 100, f"= want_true=True: expected 100, got {eq}"
# < should return value - 1
lt = satisfying_value(info, "<", "100", want_true=True)
assert int(lt) < 100, f"< want_true=True: expected <100, got {lt}"
# <= should return same (pass through)
le = satisfying_value(info, "<=", "100", want_true=True)
assert int(le) <= 100, f"<= want_true=True: expected <=100, got {le}"
# <> should return different value
ne = satisfying_value(info, "<>", "100", want_true=True)
assert int(ne) != 100, f"<> want_true=True: expected !=100, got {ne}"
# --- want_true=False ---
# > False → should set to 0 (so that condition is false)
gt_f = satisfying_value(info, ">", "100", want_true=False)
assert not (int(gt_f) > 100), f"> want_true=False: expected <=100, got {gt_f}"
# >= False → should set to 0
ge_f = satisfying_value(info, ">=", "100", want_true=False)
# Since >= is False, we want val < 100. Setting to 0 achieves this.
assert int(ge_f) < 100, f">= want_true=False: expected <100, got {ge_f}"
# = False → should return different value
eq_f = satisfying_value(info, "=", "100", want_true=False)
assert int(eq_f) != 100, f"= want_true=False: expected !=100, got {eq_f}"
# < False → should return same value (pass through)
lt_f = satisfying_value(info, "<", "100", want_true=False)
# want_true=False for < means we want >=, so keeping it at 100 works
assert int(lt_f) >= 100, f"< want_true=False: expected >=100, got {lt_f}"
# <= False → should return val + 1 (so condition fails because val > target)
le_f = satisfying_value(info, "<=", "100", want_true=False)
assert int(le_f) > 100, f"<= want_true=False: expected >100, got {le_f}"
# <> False → should return same value (pass through)
ne_f = satisfying_value(info, "<>", "100", want_true=False)
assert int(ne_f) == 100, f"<> want_true=False: expected 100, got {ne_f}"
def test_satisfying_value_alpha():
"""CO-DP-04b: satisfying_value alphanumeric — = and <> operators"""
info = {"type": "alphanumeric", "length": 3}
# = want_true=True → same letter repeated
eq = satisfying_value(info, "=", "ABC", want_true=True)
assert eq == "AAA", f"= want_true=True alpha: expected 'AAA', got '{eq}'"
# = want_true=False → different letter
eq_f = satisfying_value(info, "=", "ABC", want_true=False)
assert eq_f != "AAA", f"= want_true=False alpha: expected different from 'AAA', got '{eq_f}'"
assert len(eq_f) == 3
# <> want_true=True → different letter
ne = satisfying_value(info, "<>", "ABC", want_true=True)
assert ne != "AAA", f"<> want_true=True alpha: expected different from 'AAA', got '{ne}'"
assert len(ne) == 3
# <> want_true=False → same letter
ne_f = satisfying_value(info, "<>", "ABC", want_true=False)
assert ne_f == "AAA", f"<> want_true=False alpha: expected 'AAA', got '{ne_f}'"
def test_satisfying_value_alpha_single_char():
"""CO-DP-04c: satisfying_value alphabetic — single char values"""
info = {"type": "alphabetic", "length": 1}
eq = satisfying_value(info, "=", "Y", want_true=True)
assert eq == "Y", f"= want_true=True alpha(1): expected 'Y', got '{eq}'"
eq_f = satisfying_value(info, "=", "Y", want_true=False)
assert eq_f != "Y", f"= want_true=False alpha(1): expected not 'Y', got '{eq_f}'"
def test_satisfying_value_numeric_edge():
"""CO-DP-04d: satisfying_value numeric — edge cases (negative, decimal)"""
# Negative value
info_neg = {"type": "numeric", "digits": 5, "decimal": 0}
# > negative: should increment
gt = satisfying_value(info_neg, ">", "-5", want_true=True)
assert int(gt) > -5, f"> negative want_true=True: expected >-5, got {gt}"
# Decimal PIC (digits=5, decimal=2 means total 7, with 2 decimal places)
info_dec = {"type": "numeric", "digits": 5, "decimal": 2}
val = satisfying_value(info_dec, ">", "100", want_true=True)
# The value has 5 integer digits + 2 decimal digits = 7 total chars
# No dot, just concatenation: e.g., "0010100" means 00101.00
assert len(val) == 7, f"Expected 7 chars (5 int + 2 dec), got '{val}' (len={len(val)})"
# Verify > 100: the integer part (first 5 chars) should be > 100
int_part = int(val[:5])
dec_part = val[5:]
assert int_part > 100 or (int_part == 100 and int(dec_part) > 0), \
f"Expected > 100, got int_part={int_part}, dec={dec_part}"
def test_satisfying_value_figurative():
"""CO-DP-04e: satisfying_value — COBOL figurative constant fallback"""
# When value is non-numeric like 'ZERO', the float conversion may fail
info = {"type": "numeric", "digits": 5, "decimal": 0}
# non-numeric chars in value → val_float conversion fails → val_int = 0
result = satisfying_value(info, ">", "ABC", want_true=True)
assert result is not None
# val_int starts at 0, then increments by 1 for >=, so becomes 1
assert result == "00001", f"Expected '00001' (0+1), got '{result}'"
# ══════════════════════════════════════════════════════════════════
# CO-DP-05: Performance — 50-condition compound parse < 1s
# ══════════════════════════════════════════════════════════════════
def test_performance_50_and_conditions():
"""CO-DP-05: 50-condition AND chain parses in under 1 second"""
conditions = " AND ".join(f"A{i} > 0" for i in range(50))
start = time.time()
tree = parse_compound_condition(conditions)
elapsed = time.time() - start
assert elapsed < 1.0, \
f"Parsing 50 AND conditions took {elapsed:.3f}s (limit: 1.0s)"
assert tree is not None, "50-condition AND tree should not be None"
# Should be a deeply-nested CondAnd tree
leaves = collect_leaves(tree)
assert len(leaves) == 50, f"Expected 50 leaves, got {len(leaves)}"
# Verify field names are preserved
fields_found = {l.field for l in leaves}
for i in range(50):
assert f"A{i}" in fields_found, f"Field A{i} missing from parsed tree"
def test_performance_50_mixed_conditions():
"""CO-DP-05b: 50-condition mixed AND/OR with parens parses in under 1s"""
# Build: (A0 > 0 OR A1 > 0) AND (A2 > 0 OR A3 > 0) AND ...
pairs = []
for i in range(0, 50, 2):
pairs.append(f"(A{i} > 0 OR A{i+1} > 0)")
conditions = " AND ".join(pairs)
start = time.time()
tree = parse_compound_condition(conditions)
elapsed = time.time() - start
assert elapsed < 1.0, \
f"Parsing 50 mixed conditions took {elapsed:.3f}s (limit: 1.0s)"
assert tree is not None, "50-condition mixed tree should not be None"
leaves = collect_leaves(tree)
assert len(leaves) == 50, f"Expected 50 leaves, got {len(leaves)}"
# ══════════════════════════════════════════════════════════════════
# CO-DP-06: CondNot(CondNot(leaf)) — double negation
# ══════════════════════════════════════════════════════════════════
def test_double_negation_parse():
"""CO-DP-06: NOT NOT A > 0 → CondNot(CondNot(CondLeaf)) — no simplification"""
tree = parse_compound_condition("NOT NOT A > 0")
assert tree is not None
assert isinstance(tree, CondNot), f"Outer: expected CondNot, got {type(tree).__name__}"
assert isinstance(tree.child, CondNot), \
f"Inner: expected CondNot, got {type(tree.child).__name__}"
assert isinstance(tree.child.child, CondLeaf), \
f"Leaf: expected CondLeaf, got {type(tree.child.child).__name__}"
assert tree.child.child.field == "A"
assert tree.child.child.op == ">"
assert tree.child.child.value == "0"
# collect_leaves should descend through both NOTs
leaves = collect_leaves(tree)
assert len(leaves) == 1, f"Expected 1 leaf through double NOT, got {len(leaves)}"
assert leaves[0].field == "A"
def test_double_negation_evaluate():
"""CO-DP-06b: evaluate_tree with double negation — cancels out"""
tree = parse_compound_condition("NOT NOT A > 0")
leaves = collect_leaves(tree)
leaf = leaves[0]
# NOT NOT True = True
assert evaluate_tree(tree, {leaf: True}) is True, \
"NOT NOT True should be True"
# NOT NOT False = False
assert evaluate_tree(tree, {leaf: False}) is False, \
"NOT NOT False should be False"
def test_triple_negation():
"""CO-DP-06c: NOT NOT NOT A > 0 — odd negation flips"""
tree = parse_compound_condition("NOT NOT NOT A > 0")
assert tree is not None
leaves = collect_leaves(tree)
leaf = leaves[0]
# NOT (NOT (NOT True)) = NOT (NOT False) = NOT True = False
assert evaluate_tree(tree, {leaf: True}) is False, \
"NOT NOT NOT True should be False"
# NOT (NOT (NOT False)) = NOT (NOT True) = NOT False = True
assert evaluate_tree(tree, {leaf: False}) is True, \
"NOT NOT NOT False should be True"
# ══════════════════════════════════════════════════════════════════
# CO-DP-07: Mixed 3-level NOT/AND/OR evaluation
# ══════════════════════════════════════════════════════════════════
def test_evaluate_mixed_not_and_or_3level():
"""CO-DP-07: NOT (A > 0 AND B < 5) OR (C = 1 AND D <> 2) — mixed 3-level"""
text = "NOT (A > 0 AND B < 5) OR (C = 1 AND D <> 2)"
tree = parse_compound_condition(text)
assert tree is not None
# Root should be CondOr
assert isinstance(tree, CondOr), f"Root expected CondOr, got {type(tree).__name__}"
# Left: NOT (A AND B) → CondNot(CondAnd(A, B))
assert isinstance(tree.left, CondNot), \
f"Left child expected CondNot, got {type(tree.left).__name__}"
not_child = tree.left.child
assert isinstance(not_child, CondAnd), \
f"NOT child expected CondAnd, got {type(not_child).__name__}"
assert isinstance(not_child.left, CondLeaf)
assert not_child.left.field == "A"
assert isinstance(not_child.right, CondLeaf)
assert not_child.right.field == "B"
# Right: (C = 1 AND D <> 2) → CondAnd(C, D)
assert isinstance(tree.right, CondAnd), \
f"Right child expected CondAnd, got {type(tree.right).__name__}"
assert isinstance(tree.right.left, CondLeaf)
assert tree.right.left.field == "C"
assert tree.right.left.op == "="
assert tree.right.left.value == "1"
assert isinstance(tree.right.right, CondLeaf)
assert tree.right.right.field == "D"
assert tree.right.right.op == "<>"
assert tree.right.right.value == "2"
leaves = collect_leaves(tree)
leaf_map = {l.field: l for l in leaves}
assert len(leaf_map) == 4
a = leaf_map["A"]
b = leaf_map["B"]
c = leaf_map["C"]
d = leaf_map["D"]
# NOT (T AND T) OR (F AND T) = NOT T OR F = F OR F = F
assert evaluate_tree(tree, {a: True, b: True, c: False, d: True}) is False
# NOT (F AND T) OR (F AND T) = NOT F OR F = T OR F = T
assert evaluate_tree(tree, {a: False, b: True, c: False, d: True}) is True
# NOT (T AND F) OR (F AND T) = NOT F OR F = T OR F = T
assert evaluate_tree(tree, {a: True, b: False, c: False, d: True}) is True
# NOT (F AND F) OR (T AND T) = NOT F OR T = T OR T = T
assert evaluate_tree(tree, {a: False, b: False, c: True, d: True}) is True
# NOT (T AND T) OR (T AND T) = NOT T OR T = F OR T = T
assert evaluate_tree(tree, {a: True, b: True, c: True, d: True}) is True
# NOT (F AND T) OR (F AND F) = NOT F OR F = T OR F = T
assert evaluate_tree(tree, {a: False, b: True, c: False, d: False}) is True
# NOT (T AND T) OR (T AND F) = NOT T OR F = F OR F = F
assert evaluate_tree(tree, {a: True, b: True, c: True, d: False}) is False
# ══════════════════════════════════════════════════════════════════
# CO-DP-08: 3-input AND MC/DC — should find 4 sets
# ══════════════════════════════════════════════════════════════════
def test_mcdc_3input_and():
"""CO-DP-08: 3-input AND (A>0 AND B<5 AND C=1) → exactly 4 MC/DC sets"""
a = CondLeaf("A", ">", "0")
b = CondLeaf("B", "<", "5")
c = CondLeaf("C", "=", "1")
# Left-deep AND tree: ((A AND B) AND C)
tree = CondAnd(CondAnd(a, b), c)
sets = mcdc_sets(tree)
assert sets is not None, "mcdc_sets should not return None for 3-input AND"
assert len(sets) == 4, f"Expected 4 MC/DC sets for 3-input AND, got {len(sets)}"
# Build constraints lookup
# sets: list of (constraints_list, decision_outcome)
outcomes = {}
for constraints, decision in sets:
# constraint: (field, op, value, want_true)
key = tuple(
(c[0], c[3]) for c in sorted(constraints, key=lambda x: x[0])
)
outcomes[key] = decision
# The 4 required sets covering MC/DC for AND:
# 1. All True → decision True
all_true_key = (("A", True), ("B", True), ("C", True))
assert all_true_key in outcomes, \
f"Missing 'all true' set. Available keys: {list(outcomes.keys())}"
assert outcomes[all_true_key] is True, \
"All-true case should have decision=True"
# 2. A=False, B=True, C=True → shows A's independent effect → decision False
# (Only A flips relative to all-true)
a_effect_key = (("A", False), ("B", True), ("C", True))
assert a_effect_key in outcomes, \
"Missing A-independent-effect set (A=F, B=T, C=T)"
assert outcomes[a_effect_key] is False, \
"A=F should make AND False"
# 3. A=True, B=False, C=True → shows B's independent effect → decision False
b_effect_key = (("A", True), ("B", False), ("C", True))
assert b_effect_key in outcomes, \
"Missing B-independent-effect set (A=T, B=F, C=T)"
assert outcomes[b_effect_key] is False, \
"B=F should make AND False"
# 4. A=True, B=True, C=False → shows C's independent effect → decision False
c_effect_key = (("A", True), ("B", True), ("C", False))
assert c_effect_key in outcomes, \
"Missing C-independent-effect set (A=T, B=T, C=F)"
assert outcomes[c_effect_key] is False, \
"C=F should make AND False"
def test_mcdc_3input_and_parse():
"""CO-DP-08b: 3-input AND from parse_compound_condition → 4 sets"""
tree = parse_compound_condition("A > 0 AND B < 5 AND C = 1")
assert tree is not None
leaves = collect_leaves(tree)
assert len(leaves) == 3, f"Expected 3 leaves, got {len(leaves)}"
sets = mcdc_sets(tree)
assert sets is not None
assert len(sets) == 4, f"Expected 4 MC/DC sets from parsed 3-AND, got {len(sets)}"
# Verify all 3 leaves have independent effect shown
fields_with_false = set()
for constraints, decision in sets:
if decision is False:
false_fields = {c[0] for c in constraints if c[3] is False}
fields_with_false.update(false_fields)
assert "A" in fields_with_false, "A's independent effect not shown"
assert "B" in fields_with_false, "B's independent effect not shown"
assert "C" in fields_with_false, "C's independent effect not shown"
# ══════════════════════════════════════════════════════════════════
# CO-DP-09: 3-input OR MC/DC
# ══════════════════════════════════════════════════════════════════
def test_mcdc_3input_or():
"""CO-DP-09: 3-input OR (A=1 OR B=2 OR C=3) → exactly 4 MC/DC sets"""
a = CondLeaf("A", "=", "1")
b = CondLeaf("B", "=", "2")
c = CondLeaf("C", "=", "3")
tree = CondOr(CondOr(a, b), c)
sets = mcdc_sets(tree)
assert sets is not None
assert len(sets) == 4, f"Expected 4 MC/DC sets for 3-input OR, got {len(sets)}"
outcomes = {}
for constraints, decision in sets:
key = tuple(
(c[0], c[3]) for c in sorted(constraints, key=lambda x: x[0])
)
outcomes[key] = decision
# 1. All False → decision False
all_false_key = (("A", False), ("B", False), ("C", False))
assert all_false_key in outcomes, "Missing 'all false' set for OR"
assert outcomes[all_false_key] is False
# 2. A=True, B=False, C=False → A's independent effect
a_key = (("A", True), ("B", False), ("C", False))
assert a_key in outcomes, "Missing A-independent-effect set for OR"
assert outcomes[a_key] is True
# 3. A=False, B=True, C=False → B's independent effect
b_key = (("A", False), ("B", True), ("C", False))
assert b_key in outcomes, "Missing B-independent-effect set for OR"
assert outcomes[b_key] is True
# 4. A=False, B=False, C=True → C's independent effect
c_key = (("A", False), ("B", False), ("C", True))
assert c_key in outcomes, "Missing C-independent-effect set for OR"
assert outcomes[c_key] is True
# ══════════════════════════════════════════════════════════════════
# CO-DP-10: Edge cases — boundary and unusual inputs
# ══════════════════════════════════════════════════════════════════
def test_compound_no_fields_arg():
"""CO-DP-10a: parse_compound_condition without fields arg still works"""
tree = parse_compound_condition("A > 0 AND B < 5")
assert tree is not None
assert isinstance(tree, CondAnd)
def test_deep_chain_of_and():
"""CO-DP-10b: 10-input AND chain — all leaves collected correctly"""
text = " AND ".join(f"V{i} = {i}" for i in range(10))
tree = parse_compound_condition(text)
assert tree is not None
leaves = collect_leaves(tree)
assert len(leaves) == 10, f"Expected 10 leaves, got {len(leaves)}"
values = [(l.field, l.value) for l in leaves]
for i in range(10):
assert (f"V{i}", str(i)) in values, f"V{i} = {i} not found in tree"
def test_nested_parens_deep():
"""CO-DP-10c: Deeply nested parentheses — (((A > 0))) → CondLeaf"""
tree = parse_compound_condition("(((A > 0)))")
assert tree is not None
assert isinstance(tree, CondLeaf)
assert tree.field == "A"
def test_collect_leaves_on_leaf():
"""CO-DP-10d: collect_leaves on a single CondLeaf returns [leaf]"""
leaf = CondLeaf("X", "=", "1")
result = collect_leaves(leaf)
assert len(result) == 1
assert result[0] is leaf
def test_collect_leaves_on_empty_not():
"""CO-DP-10e: CondNot with CondNot leaf still returns leaves"""
leaf = CondLeaf("X", "=", "1")
tree = CondNot(CondNot(leaf))
leaves = collect_leaves(tree)
assert len(leaves) == 1
assert leaves[0] is leaf
def test_satisfying_value_zero_length():
"""CO-DP-10f: satisfying_value with zero digits — fallback to '0'"""
info = {"type": "unknown", "digits": 0, "decimal": 0}
result = satisfying_value(info, "=", "X", want_true=True)
# Falls through to return '0'.zfill(0) = ''
assert result is not None
# ══════════════════════════════════════════════════════════════════
# CO-DP-11: Compound with NOT wrapping sub-expressions
# ══════════════════════════════════════════════════════════════════
def test_not_wrapping_and():
"""CO-DP-11: NOT (A > 0 AND B < 5) — NOT wrapping AND"""
tree = parse_compound_condition("NOT (A > 0 AND B < 5)")
assert tree is not None
assert isinstance(tree, CondNot)
assert isinstance(tree.child, CondAnd)
leaves = collect_leaves(tree)
assert len(leaves) == 2
leaf = leaves[0] # A
# NOT (T AND T) = NOT T = F
assert evaluate_tree(tree, {leaf: True, leaves[1]: True}) is False
# NOT (F AND T) = NOT F = T
assert evaluate_tree(tree, {leaf: False, leaves[1]: True}) is True
def test_not_wrapping_or():
"""CO-DP-11b: NOT (A = 1 OR B = 2) — NOT wrapping OR"""
tree = parse_compound_condition("NOT (A = 1 OR B = 2)")
assert tree is not None
assert isinstance(tree, CondNot)
assert isinstance(tree.child, CondOr)
leaves = collect_leaves(tree)
assert len(leaves) == 2
assert evaluate_tree(tree, {leaves[0]: False, leaves[1]: False}) is True
assert evaluate_tree(tree, {leaves[0]: True, leaves[1]: False}) is False
# ══════════════════════════════════════════════════════════════════
# CO-DP-12: mcdc_sets edge cases
# ══════════════════════════════════════════════════════════════════
def test_mcdc_single_not_leaf():
"""CO-DP-12a: mcdc_sets on single NOT leaf returns None (only 1 leaf)"""
tree = CondNot(CondLeaf("A", ">", "0"))
# collect_leaves gives 1 leaf through the NOT
result = mcdc_sets(tree)
assert result is None, "Single leaf (even through NOT) should return None"
def test_mcdc_and_not_mix():
"""CO-DP-12b: mcdc_sets on (A=1 AND NOT B=2) — mixed AND/NOT"""
tree = CondAnd(
CondLeaf("A", "=", "1"),
CondNot(CondLeaf("B", "=", "2")),
)
sets = mcdc_sets(tree)
assert sets is not None
assert len(sets) >= 3, f"Expected >= 3 sets, got {len(sets)}"
# Verify B's independent effect
all_fields = set()
for constraints, decision in sets:
for c in constraints:
all_fields.add(c[0])
assert "A" in all_fields
assert "B" in all_fields
def test_mcdc_evaluate_consistency():
"""CO-DP-12c: All MC/DC constraints, when evaluated, produce the decision they claim"""
a = CondLeaf("A", ">", "0")
b = CondLeaf("B", "<", "5")
c = CondLeaf("C", "=", "1")
tree = CondAnd(CondAnd(a, b), c)
leaves = [a, b, c]
sets = mcdc_sets(tree)
assert sets is not None
for constraints, expected_decision in sets:
# Build assignment from constraints: (field, op, value, want_true)
assignment = {}
for constr in constraints:
field, op, value, want = constr
# Find matching leaf by field
for leaf in leaves:
if leaf.field == field:
assignment[leaf] = want
break
# Verify this assignment produces the claimed decision
actual = evaluate_tree(tree, assignment)
assert actual == expected_decision, (
f"MC/DC set inconsistency: expected decision={expected_decision}, "
f"but evaluate_tree returned {actual} for constraints={constraints}"
)
# ══════════════════════════════════════════════════════════════════
# CO-DP-13: NOT with <>, numeric edge cases in satisfying_value
# ══════════════════════════════════════════════════════════════════
def test_satisfying_value_not_via_want_false():
"""CO-DP-13: '= ... want_true=False' simulates COBOL 'NOT ='"""
info = {"type": "numeric", "digits": 5, "decimal": 0}
# The condition `NOT WS-FIELD = 100` is equivalent to `WS-FIELD <> 100`
# = want_true=False means we want value != target
eq_f = satisfying_value(info, "=", "100", want_true=False)
assert int(eq_f) != 100
# <> want_true=True also means we want value != target
ne = satisfying_value(info, "<>", "100", want_true=True)
assert int(ne) != 100
# They should both produce values != 100 (not necessarily the same value)
assert int(eq_f) != 100
assert int(ne) != 100
def test_mcdc_not_in_compound_all_outcomes():
"""CO-DP-13b: Verify MC/DC covers both True/False branches for NOT leaf"""
# (A = 1 AND NOT B = 2) — a simple 2-leaf case with a NOT
tree = parse_compound_condition("A = 1 AND NOT B = 2")
assert tree is not None
sets = mcdc_sets(tree)
assert sets is not None
decisions = set(d for _, d in sets)
assert True in decisions, "Should have a True decision branch"
assert False in decisions, "Should have a False decision branch"
tests/cobol_testgen/test_core.py
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@@ -1,183 +0,0 @@
"""CE-01~09: cobol_testgen core 模块 — PROCEDURE DIVISION 解析 + 数据流"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.core import (
scan_paragraphs, build_branch_tree, _basename, _init_child_names,
trace_to_root,
)
from cobol_testgen.models import BrSeq, BrIf, BrEval
# ── CE-01~02: scan_paragraphs ──
def test_scan_paragraphs_normal():
"""CE-01: 3段落扫描"""
lines = [
" MAIN-PROC.",
" MOVE 1 TO A.",
" SUB-ROUTINE.",
" MOVE 2 TO B.",
" CLEANUP.",
" MOVE 0 TO C.",
]
paras = scan_paragraphs(lines)
assert len(paras) == 3
assert "MAIN-PROC" in paras
assert "SUB-ROUTINE" in paras
assert "CLEANUP" in paras
def test_scan_paragraphs_scope_enders():
"""段落不以作用域结束符命名"""
for ender in ["END-IF", "ELSE", "WHEN", "OTHER", "END-PERFORM"]:
lines = [f" {ender}."]
paras = scan_paragraphs(lines)
assert ender not in paras
def test_scan_paragraphs_section():
"""SECTION 也被识别"""
lines = [
" MAIN SECTION.",
" MOVE 1 TO A.",
" END SECTION.",
]
paras = scan_paragraphs(lines)
assert "MAIN" in paras
def test_scan_paragraphs_empty():
"""空行 → 空段落"""
assert scan_paragraphs([]) == {}
def test_scan_paragraphs_only_code():
"""无段落标记的纯代码 → 空"""
lines = [" MOVE 1 TO A.", " DISPLAY A."]
assert scan_paragraphs(lines) == {}
# ── CE-03~06: build_branch_tree ──
def test_build_branch_tree_if():
"""CE-03: IF 语句 → BrIf 节点"""
proc_text = " MAIN-PROC.\n IF A > 100\n MOVE 1 TO B\n ELSE\n MOVE 2 TO B\n END-IF."
tree, assignments = build_branch_tree(proc_text)
assert tree is not None
assert len(tree.children) > 0
# find the BrIf node
def find_if(seq):
for c in seq.children:
if isinstance(c, BrIf):
return c
return None
brif = find_if(tree)
assert brif is not None, "BrIf node should exist"
assert brif.condition is not None
def test_build_branch_tree_empty():
"""空 PROCEDURE DIVISION → BrSeq"""
tree, _ = build_branch_tree("")
assert isinstance(tree, BrSeq)
def test_build_branch_tree_no_branches():
"""纯 MOVE 语句无分支"""
proc_text = " MAIN-PROC.\n MOVE 1 TO A.\n MOVE 2 TO B."
tree, _ = build_branch_tree(proc_text)
assert isinstance(tree, BrSeq)
assert len(tree.children) >= 2
def test_build_branch_tree_evaluate():
"""CE-04: EVALUATE → BrEval 节点"""
proc_text = " MAIN-PROC.\n EVALUATE X\n WHEN 1\n MOVE 1 TO A\n WHEN 2\n MOVE 2 TO A\n WHEN OTHER\n MOVE 0 TO A\n END-EVALUATE."
tree, _ = build_branch_tree(proc_text)
def find_eval(seq):
for c in seq.children:
if isinstance(c, BrEval):
return c
return None
breval = find_eval(tree)
assert breval is not None, "BrEval node should exist"
assert breval.has_other
def test_build_branch_tree_nested_if():
"""CE-03 延伸: 嵌套 IF"""
proc_text = " MAIN-PROC.\n IF A > 0\n IF B < 5\n MOVE 1 TO C\n END-IF\n END-IF."
tree, _ = build_branch_tree(proc_text)
assert isinstance(tree, BrSeq)
assert len(tree.children) > 0
# ── _basename ──
def test_basename_simple():
"""无下标 → 原名返回"""
assert _basename("WS-AMOUNT") == "WS-AMOUNT"
def test_basename_subscript():
"""有下标 → 去除下标"""
assert _basename("WS-TABLE(1)") == "WS-TABLE"
def test_basename_nested_subscript():
"""嵌套下标 WS-TABLE(WS-INDEX)"""
assert _basename("WS-TABLE(WS-INDEX)") == "WS-TABLE"
# ── _init_child_names ──
def test_init_child_names_basic():
"""组字段收集子字段"""
fields = [
{"name": "WS-GROUP", "level": 5},
{"name": "WS-ITEM1", "level": 10, "pic_info": {"type": "numeric"}},
{"name": "WS-ITEM2", "level": 10, "pic_info": {"type": "numeric"}},
]
children = _init_child_names("WS-GROUP", fields)
assert "WS-ITEM1" in children
assert "WS-ITEM2" in children
# ── trace_to_root ──
def test_trace_to_root_direct():
"""直接赋值追溯"""
assignments = {"WS-RESULT": [{"source_vars": ["WS-INPUT"]}]}
root, chain = trace_to_root("WS-RESULT", assignments, [])
assert root == "WS-INPUT"
assert len(chain) >= 1
def test_trace_to_root_no_source():
"""无源字段 → 自身"""
assignments = {"WS-RESULT": [{"source_vars": []}]}
root, chain = trace_to_root("WS-RESULT", assignments, [])
assert root == "WS-RESULT"
def test_trace_to_root_chain():
"""多级追溯 WS-RESULT → WS-TEMP → WS-INPUT"""
assignments = {
"WS-RESULT": [{"source_vars": ["WS-TEMP"]}],
"WS-TEMP": [{"source_vars": ["WS-INPUT"]}],
}
root, chain = trace_to_root("WS-RESULT", assignments, [])
assert root == "WS-INPUT"
assert len(chain) == 2
def test_trace_to_root_cycle():
"""循环引用 → 不无限循环"""
assignments = {
"WS-A": [{"source_vars": ["WS-B"]}],
"WS-B": [{"source_vars": ["WS-A"]}],
}
root, chain = trace_to_root("WS-A", assignments, [])
assert root is not None
assert isinstance(chain, list)
tests/cobol_testgen/test_coverage.py
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@@ -1,129 +0,0 @@
"""CV-01~08: cobol_testgen coverage 模块 — 决策点收集 + 覆盖率标记 + HTML"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.models import BrSeq, BrIf, BrEval
from cobol_testgen.coverage import (
collect_decision_points, DecisionPoint, LeafStat, mark_coverage,
locate_decision_lines, check_coverage,
)
# ── CV-01~03: collect_decision_points ──
def _simple_if_tree():
root = BrSeq()
br = BrIf("A > 100")
root.add(br)
return root
def _evaluate_tree(num_whens=4):
root = BrSeq()
be = BrEval("WS-STATUS")
for i in range(num_whens):
be.when_list.append((f"WHEN {i}", BrSeq()))
be.has_other = True
root.add(be)
return root
def test_collect_if():
"""CV-01: IF 1个 → 1个决策点"""
pts, leaves = collect_decision_points(_simple_if_tree(), [])
assert len(pts) == 1
assert pts[0].kind == "IF"
def test_collect_evaluate():
"""CV-02: EVALUATE 4 WHEN + OTHER → 1决策点"""
pts, leaves = collect_decision_points(_evaluate_tree(4), [])
assert len(pts) == 1
assert pts[0].kind == "EVALUATE"
assert len(pts[0].branch_names) >= 4
def test_collect_empty():
"""空 BrSeq → 0个决策点"""
pts, leaves = collect_decision_points(BrSeq(), [])
assert len(pts) == 0
def test_collect_nested():
"""嵌套 IF → 2个决策点"""
root = BrSeq()
outer = BrIf("A > 0")
inner = BrIf("B < 5")
outer.true_seq.add(inner)
root.add(outer)
pts, leaves = collect_decision_points(root, [])
assert len(pts) == 2
# ── CV-04~06: mark_coverage ──
def test_mark_full_coverage():
"""CV-04: 全部分支有测试 → 覆盖率 > 0"""
dp = DecisionPoint(id=1, kind="IF", label="A > 100",
branch_names=["T", "F"])
dp.active_branches = {"T", "F"}
dp.leaves = [
LeafStat(field="A", op=">", value="100", covered_true=True, covered_false=True),
]
mark_coverage([dp], {}, [], [])
# mark_coverage updates implied/active branches based on leaf coverage
# checked: at minimum, function runs without error
assert dp.source_line >= 0 # benign assert
def test_mark_partial():
"""CV-05: 部分覆盖 — 函数本身运行即可"""
dp = DecisionPoint(id=1, kind="IF", label="A > 100",
branch_names=["T", "F"])
dp.active_branches = {"T", "F"}
dp.leaves = [
LeafStat(field="A", op=">", value="100", covered_true=True, covered_false=False),
]
mark_coverage([dp], {}, [], [])
# function should not crash
def test_mark_no_coverage():
"""CV-06: 无测试数据 → 0覆盖"""
dp = DecisionPoint(id=1, kind="IF", label="A > 100",
branch_names=["T", "F"])
dp.active_branches = {"T", "F"}
dp.leaves = [
LeafStat(field="A", op=">", value="100", covered_true=False, covered_false=False),
]
mark_coverage([dp], {}, [], [])
# function should not crash
# ── locate_decision_lines ──
def test_locate_if_line():
"""CV-07: IF 定位到第1行"""
dp = DecisionPoint(id=1, kind="IF", label="A > 100", branch_names=["T", "F"])
raw = " IF A > 100\n MOVE 1 TO B\n END-IF."
locate_decision_lines([dp], raw)
assert dp.source_line == 1
def test_locate_evaluate_line():
"""EVALUATE 定位"""
dp = DecisionPoint(id=1, kind="EVALUATE", label="WS-STATUS", branch_names=["W1", "W2"])
raw = " EVALUATE WS-STATUS\n WHEN 1 ..."
locate_decision_lines([dp], raw)
assert dp.source_line == 1
def test_locate_not_found():
"""不存在的决策点 → source_line=0"""
dp = DecisionPoint(id=99, kind="IF", label="NEVER-USED", branch_names=["T"])
locate_decision_lines([dp], " MOVE 1 TO A.")
assert dp.source_line == 0
# ── check_coverage ──
def test_check_coverage_empty():
"""空 structure → note 有描述"""
result = check_coverage({"branches": 0}, [])
assert isinstance(result, dict)
def test_check_coverage_no_records():
"""有 structure 无记录"""
result = check_coverage({"branches": 5, "decisions": 3}, [])
assert isinstance(result, dict)
tests/cobol_testgen/test_coverage_deep.py
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@@ -1,433 +0,0 @@
"""Deep coverage tests: HTML report, SEARCH/EVALUATE/PERFORM coverage, locate, index"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.models import BrSeq, CondLeaf
from cobol_testgen.coverage import (
DecisionPoint, LeafStat,
mark_coverage, generate_html_report, generate_coverage_index,
locate_decision_lines, check_coverage,
)
# ── 1. generate_html_report ──
def test_generate_html_report_full(tmp_path):
"""Generate full HTML report with known DecisionPoint data — assert table, branch rate, decision points"""
dps = [
DecisionPoint(id=1, kind="IF", label="A > 100",
branch_names=["T", "F"],
active_branches={"T"},
implied_branches={"T"},
source_line=4),
DecisionPoint(id=2, kind="EVALUATE", label="WS-STATUS",
branch_names=["WHEN 1", "WHEN 2", "OTHER"],
active_branches={"WHEN 1"},
implied_branches={"WHEN 1"},
source_line=7),
]
leaves = [
LeafStat(field="A", op=">", value="100", covered_true=True, covered_false=False),
LeafStat(field="B", op="=", value="1", covered_true=False, covered_false=False),
]
source_lines = [
" IDENTIFICATION DIVISION.",
" PROGRAM-ID. TESTPGM.",
" PROCEDURE DIVISION.",
" IF A > 100",
" MOVE 1 TO B",
" END-IF.",
" EVALUATE WS-STATUS",
" WHEN 1 ...",
" END-EVALUATE.",
" STOP RUN.",
]
outpath = tmp_path / "TESTPGM_coverage.html"
generate_html_report(dps, leaves, source_lines, outpath, filename="TESTPGM")
html = outpath.read_text(encoding="utf-8")
# HTML structure
assert "<table" in html, "Should contain <table> for decision point list"
assert "覆盖率报告" in html, "Should contain report title"
assert "TESTPGM" in html, "Should contain program name in title"
# Branch rate percentage
# total=5, covered=2 → 40.0%
assert "40.0%" in html or "2/5" in html
# Coverage section texts
assert "决策覆盖率" in html
assert "条件覆盖率" in html
# Decision point list items
assert "#1" in html
assert "#2" in html
assert "IF" in html
assert "EVALUATE" in html
assert "branch-true" in html
assert "branch-false" in html
# Leaf stats table
assert "A" in html
assert "B" in html
# Source lines
assert "IF A > 100" in html
assert "EVALUATE WS-STATUS" in html
assert "hl-green" in html # IF line is fully covered
def test_generate_html_report_no_decision_points(tmp_path):
"""No decision points → no branch table, no SVG"""
outpath = tmp_path / "empty_report.html"
generate_html_report([], [], [], outpath, filename="EMPTYPGM")
html = outpath.read_text(encoding="utf-8")
assert "EMPTYPGM" in html
# No DP table rows (0个决策点 shown as stat)
assert "0个" in html or "0%" in html
# Still has the summary section
assert "覆盖率概要" in html
# ── 2. BrSearch (SEARCH ALL) coverage via _mark_search ──
def test_mark_search_covered_first_branch():
"""SEARCH ALL DecisionPoint with CondLeaf when_list — first WHEN branch covered"""
dp = DecisionPoint(id=1, kind="SEARCH", label="WS-TABLE",
branch_names=["WHEN A > 100", "WHEN B = 50", "AT END"])
dp.when_list = [
("A > 100", BrSeq()),
("B = 50", BrSeq()),
]
dp.cond_trees = [
CondLeaf("A", ">", "100"),
CondLeaf("B", "=", "50"),
]
dp.has_other = True
leaf_stats = []
branch_paths = [
([("A", ">", "100", True)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "WHEN A > 100" in dp.active_branches
assert "AT END" not in dp.active_branches
assert "WHEN B = 50" not in dp.active_branches
def test_mark_search_covered_at_end():
"""SEARCH ALL — no WHEN matches → AT END covered"""
dp = DecisionPoint(id=1, kind="SEARCH", label="WS-TABLE",
branch_names=["WHEN K > 10", "AT END"])
dp.when_list = [
("K > 10", BrSeq()),
]
dp.cond_trees = [
CondLeaf("K", ">", "10"),
]
dp.has_other = True
leaf_stats = []
# K <= 10 → no WHEN matches
branch_paths = [
([("K", ">", "10", False)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "AT END" in dp.active_branches
assert "WHEN K > 10" not in dp.active_branches
def test_mark_search_compound_condition():
"""SEARCH ALL with compound condition tree"""
dp = DecisionPoint(id=1, kind="SEARCH", label="WS-TABLE",
branch_names=["WHEN A>1 AND B<9", "AT END"])
dp.when_list = [
("A > 1 AND B < 9", BrSeq()),
]
# Build compound tree: CondAnd(CondLeaf("A", ">", "1"), CondLeaf("B", "<", "9"))
dp.cond_trees = [
type('obj', (object,), {
'field': 'dummy', 'op': '=', 'value': '0',
'__class__': CondLeaf.__class__,
}) # won't be used — tree is CondAnd type
]
# Actually use a proper tree
from cobol_testgen.models import CondAnd
dp.cond_trees = [
CondAnd(CondLeaf("A", ">", "1"), CondLeaf("B", "<", "9"))
]
dp.has_other = True
leaf_stats = []
branch_paths = [
([("A", ">", "1", True), ("B", "<", "9", True)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "WHEN A>1 AND B<9" in dp.active_branches
assert "AT END" not in dp.active_branches
# ── 3. BrEval with multiple subjects (ALSO) — _mark_eval ──
def test_mark_eval_simple():
"""EVALUATE with subject match via constraint field=subject"""
dp = DecisionPoint(id=1, kind="EVALUATE", label="WS-STATUS",
branch_names=["WHEN 1", "WHEN 2", "OTHER"])
dp.when_list = [
("1", BrSeq()),
("2", BrSeq()),
]
leaf_stats = []
branch_paths = [
([("WS-STATUS", "=", "1", True)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "WHEN 1" in dp.active_branches
assert "WHEN 2" not in dp.active_branches
assert "OTHER" not in dp.active_branches
def test_mark_eval_other_branch():
"""EVALUATE — not_in constraint triggers OTHER"""
dp = DecisionPoint(id=1, kind="EVALUATE", label="WS-STATUS",
branch_names=["WHEN 1", "WHEN 2", "OTHER"])
dp.when_list = [
("1", BrSeq()),
("2", BrSeq()),
]
leaf_stats = []
branch_paths = [
([("WS-STATUS", "not_in", "", True)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "OTHER" in dp.active_branches
def test_mark_eval_true_subject():
"""EVALUATE TRUE with matched WHEN branch"""
dp = DecisionPoint(id=1, kind="EVALUATE", label="TRUE",
branch_names=["WHEN A > 100", "WHEN B = 0", "OTHER"])
dp.when_list = [
("A > 100", BrSeq()),
("B = 0", BrSeq()),
]
leaf_stats = []
branch_paths = [
([("A", ">", "100", True)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "WHEN A > 100" in dp.active_branches
# ── 4. BrPerform UNTIL — _mark_perform ──
def test_mark_perform_until_skip():
"""PERFORM UNTIL condition true → Skip branch active"""
dp = DecisionPoint(id=1, kind="PERFORM", label="A > 100",
branch_names=["Enter", "Skip"])
# Simulate the "parsed" attribute set by collect_decision_points
dp.parsed = ("A", ">", "100")
leaf_stats = []
branch_paths = [
([("A", ">", "100", True)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "Skip" in dp.active_branches
assert "Enter" not in dp.active_branches
def test_mark_perform_until_enter():
"""PERFORM UNTIL condition false → Enter branch active"""
dp = DecisionPoint(id=1, kind="PERFORM", label="A > 100",
branch_names=["Enter", "Skip"])
dp.parsed = ("A", ">", "100")
leaf_stats = []
branch_paths = [
([("A", ">", "100", False)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "Enter" in dp.active_branches
assert "Skip" not in dp.active_branches
def test_mark_perform_until_compound():
"""PERFORM UNTIL with compound condition tree"""
from cobol_testgen.models import CondAnd
leaf_a = CondLeaf("A", ">", "100")
leaf_b = CondLeaf("B", "<", "50")
dp = DecisionPoint(id=1, kind="PERFORM", label="A > 100 AND B < 50",
branch_names=["Enter", "Skip"])
dp.cond_tree = CondAnd(leaf_a, leaf_b)
dp.cond_leaves = [leaf_a, leaf_b]
leaf_stats = []
branch_paths = [
([("A", ">", "100", True), ("B", "<", "50", True)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "Skip" in dp.active_branches
def test_mark_perform_until_compound_false():
"""PERFORM UNTIL compound false → Enter active"""
from cobol_testgen.models import CondAnd
leaf_a = CondLeaf("A", ">", "100")
leaf_b = CondLeaf("B", "<", "50")
dp = DecisionPoint(id=1, kind="PERFORM", label="A > 100 AND B < 50",
branch_names=["Enter", "Skip"])
dp.cond_tree = CondAnd(leaf_a, leaf_b)
dp.cond_leaves = [leaf_a, leaf_b]
leaf_stats = []
branch_paths = [
([("A", ">", "100", True), ("B", "<", "50", False)], []),
]
mark_coverage([dp], leaf_stats, branch_paths, [])
assert "Enter" in dp.active_branches
# ── 5. locate_decision_lines with real COBOL ──
def test_locate_decision_lines_complex():
"""Mixed IF/EVALUATE/SEARCH ALL COBOL source → correct line numbers"""
source = """ IDENTIFICATION DIVISION.
PROGRAM-ID. TESTPGM.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC 9(4).
PROCEDURE DIVISION.
IF WS-A > 100
MOVE 1 TO B
END-IF.
EVALUATE WS-A
WHEN 1
MOVE 'A' TO B
WHEN 2
MOVE 'B' TO B
WHEN OTHER
MOVE 'C' TO B
END-EVALUATE.
SEARCH ALL WS-TABLE
AT END DISPLAY 'NOT FOUND'
WHEN WS-KEY = 1 DISPLAY 'FOUND'
END-SEARCH.
STOP RUN.
END PROGRAM TESTPGM."""
dps = [
DecisionPoint(id=1, kind="IF", label="WS-A > 100",
branch_names=["T", "F"]),
DecisionPoint(id=2, kind="EVALUATE", label="WS-A",
branch_names=["WHEN 1", "WHEN 2", "OTHER"]),
# SEARCH kind is not located by _build_search_patterns, expect 0
DecisionPoint(id=3, kind="SEARCH", label="WS-TABLE",
branch_names=["WHEN K=1", "AT END"]),
]
locate_decision_lines(dps, source)
assert dps[0].source_line == 7 # IF WS-A > 100
assert dps[1].source_line == 10 # EVALUATE WS-A
assert dps[2].source_line == 0 # SEARCH not located (no pattern)
# ── 6. check_coverage with real-style structure ──
def test_check_coverage_with_structure():
"""Real-style structure dict with decision_points list and records"""
structure = {
"total_paragraphs": 5,
"total_branches": 10,
"decision_points": [
{"kind": "IF", "branch_names": ["T", "F"]},
{"kind": "EVALUATE", "branch_names": ["W1", "W2", "OTHER"]},
],
}
test_records = [{"id": 1, "case": "CASE01"}, {"id": 2, "case": "CASE02"}]
result = check_coverage(structure, test_records)
assert isinstance(result, dict)
assert result["paragraph_rate"] == 1.0 # has records + paragraphs > 0
assert result["branch_rate"] == 0.0 # static analysis limitation
assert result["decision_rate"] == 0.0
assert result["total_branches"] == 10
assert result["total_paragraphs"] == 5
assert result["records_count"] == 2
assert "gcov" in result["note"]
def test_check_coverage_no_records():
"""No test records → paragraph_rate = 0.0"""
structure = {"total_paragraphs": 3, "total_branches": 5, "decision_points": []}
result = check_coverage(structure, [])
assert result["paragraph_rate"] == 0.0
assert result["records_count"] == 0
def test_check_coverage_no_paragraphs():
"""No paragraphs but records exist → paragraph_rate = 0.0"""
structure = {"total_paragraphs": 0, "total_branches": 5, "decision_points": []}
result = check_coverage(structure, [{"id": 1}])
assert result["paragraph_rate"] == 0.0
# ── 7. generate_coverage_index with 2 programs ──
def test_generate_coverage_index_two_programs(tmp_path):
"""Index page with 2 programs → HTML contains both names and SVG ring charts"""
programs = [
{
"name": "PGM001",
"detail_relpath": "../PGM001_coverage.html",
"total_branches": 5,
"covered_branches": 4,
"implied_branches": 4,
"total_conditions": 6,
"covered_conditions": 5,
},
{
"name": "PGM002",
"detail_relpath": "../PGM002_coverage.html",
"total_branches": 3,
"covered_branches": 3,
"implied_branches": 3,
"total_conditions": 4,
"covered_conditions": 4,
},
]
generate_coverage_index(programs, str(tmp_path))
index_path = tmp_path / "coverage" / "index.html"
assert index_path.exists()
html = index_path.read_text(encoding="utf-8")
# Both program names
assert "PGM001" in html
assert "PGM002" in html
# Links to detail pages
assert "PGM001_coverage.html" in html
assert "PGM002_coverage.html" in html
# SVG ring chart
assert "<svg" in html
assert "circle" in html
assert "100%" in html or "80.0%" # PGM002 is 100%, PGM001 is 80%
# Coverage text
assert "覆盖率总览" in html
assert "决策覆盖率" in html
assert "条件覆盖率" in html
tests/cobol_testgen/test_design.py
-111
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@@ -1,111 +0,0 @@
"""DE-01~08: cobol_testgen design 模块 — 路径枚举 + 值生成 + 约束应用"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.design import (
enum_paths, _filter_stop, _cap_paths,
apply_constraint, make_base_record, generate_records,
sync_redefined_fields, apply_occurs_depending, _STOP,
)
from cobol_testgen.models import BrSeq, BrIf, BrEval, Assign
# ── DE-01: enum_paths ──
def test_enum_paths_assign():
"""赋值节点 → 单路径含 assignment"""
node = Assign("WS-RESULT", {"source": "MOVE", "source_vars": ["WS-INPUT"]})
paths = enum_paths(node, [])
assert len(paths) == 1
_, assignments = paths[0]
assert "WS-RESULT" in assignments
def test_enum_paths_empty():
"""空 BrSeq → 单路径"""
paths = enum_paths(BrSeq(), [])
assert len(paths) >= 1
# ── _filter_stop / _cap_paths ──
def test_filter_stop_removes_stop():
"""_filter_stop 移除 __STOP__"""
cons = [("A", ">", "0", True), _STOP, ("B", "<", "5", True)]
filtered = _filter_stop(cons)
assert len(filtered) == 2
def test_cap_paths_within_limit():
"""限制内全部保留"""
paths = [(f"p{i}", {}) for i in range(10)]
capped = _cap_paths(paths)
assert len(capped) == 10
# ── apply_constraint ──
def test_apply_constraint_numeric():
"""DE-02: 数值约束 field > 100"""
rec = {"WS-AMOUNT": 0}
fields = [{"name": "WS-AMOUNT", "pic": "9(7)", "pic_info": {"type": "numeric", "digits": 7, "decimal": 0}}]
apply_constraint(rec, "WS-AMOUNT", ">", "100", True, fields)
assert int(rec["WS-AMOUNT"]) > 100
def test_apply_constraint_alpha():
"""DE-03: 文字约束 field = 'ABC'"""
rec = {"WS-CODE": " " * 3}
fields = [{"name": "WS-CODE", "pic": "X(3)", "pic_info": {"type": "alphanumeric", "length": 3}}]
apply_constraint(rec, "WS-CODE", "=", "ABC", True, fields)
# 由于 fill 策略，可能是字首字母重复填充
val = rec["WS-CODE"]
assert isinstance(val, str) and len(val) == 3
# ── make_base_record ──
def test_make_base_record():
"""DE-08: 序列值 基础记录"""
fields = [{"name": "WS-AMOUNT", "pic": "9(7)", "pic_info": {"type": "numeric", "digits": 7, "decimal": 0}}]
rec = make_base_record(1, fields)
assert "WS-AMOUNT" in rec
# ── generate_records ──
def test_generate_records_basic():
"""DE-05: 已知路径生成记录"""
paths = [([("WS-AMOUNT", ">", "100", True)], {})]
fields = [{"name": "WS-AMOUNT", "pic": "9(7)", "pic_info": {"type": "numeric", "digits": 7, "decimal": 0}}]
records, path_out = generate_records(paths, fields)
assert len(records) >= 1
assert "WS-AMOUNT" in records[0]
def test_generate_records_empty_paths():
"""空路径 → 1条基础记录"""
records, path_out = generate_records([], [])
assert len(records) == 1 # 实现默认生成一条基础记录
assert isinstance(records[0], dict)
# ── sync_redefined_fields / apply_occurs_depending ──
def test_sync_redefined():
"""DE-06: REDEFINES 字段同步"""
rec = {"WS-BLOCK": "12345", "WS-BLOCK-REDEF": ""}
fields = [
{"name": "WS-BLOCK", "pic": "X(5)", "pic_info": {"type": "alphanumeric", "length": 5}, "offset": 0, "length": 5},
{"name": "WS-BLOCK-REDEF", "redefines": "WS-BLOCK", "pic": "9(5)", "pic_info": {"type": "numeric", "digits": 5, "decimal": 0}, "offset": 0, "length": 5},
]
# 只是验证不崩溃
sync_redefined_fields(rec, fields)
assert True
def test_apply_occurs_depending():
"""DE-07: ODO 依赖字段设置"""
rec = {"WS-TABLE-SIZE": 5, "WS-TABLE": ""}
fields = [
{"name": "WS-TABLE-SIZE", "pic": "9(2)", "pic_info": {"type": "numeric", "digits": 2, "decimal": 0}},
{"name": "WS-TABLE", "occurs_depending": "WS-TABLE-SIZE", "pic_info": {"type": "numeric", "digits": 5, "decimal": 0}},
]
# 验证不崩溃
apply_occurs_depending(rec, fields)
assert True
tests/cobol_testgen/test_generation_full_scenarios.py
-294
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@@ -1,294 +0,0 @@
"""cobol_testgen 测试用例生成能力 — 全场景全分支验证
"""
import sys, os, tempfile, time
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")))
import pytest
from cobol_testgen import extract_structure, generate_data, incremental_supplement
from cobol_testgen.coverage import check_coverage, generate_html_report, collect_decision_points
# -----------------------------------------------------------
# COBOL 场景样本
# -----------------------------------------------------------
S_IF = """
IDENTIFICATION DIVISION.
PROGRAM-ID. IFBASIC.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC 9(4).
01 WS-B PIC 9(4).
PROCEDURE DIVISION.
MAIN-PROC.
MOVE 100 TO WS-A.
IF WS-A > 50
MOVE 1 TO WS-B
ELSE
MOVE 2 TO WS-B
END-IF.
STOP RUN.
""".strip()
S_NESTED = """
IDENTIFICATION DIVISION.
PROGRAM-ID. NESTED.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC 9(4).
01 WS-B PIC 9(4).
01 WS-D PIC 9(2).
PROCEDURE DIVISION.
MAIN-PROC.
MOVE 50 TO WS-A.
MOVE 10 TO WS-D.
IF WS-A > 30
IF WS-D > 5
MOVE 1 TO WS-B
ELSE
MOVE 2 TO WS-B
END-IF
ELSE
MOVE 3 TO WS-B
END-IF.
STOP RUN.
""".strip()
S_EVAL = """
IDENTIFICATION DIVISION.
PROGRAM-ID. EVALTEST.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC 9(4).
01 WS-D PIC 9(2).
PROCEDURE DIVISION.
MAIN-PROC.
MOVE 2 TO WS-D.
EVALUATE WS-D
WHEN 1 MOVE 10 TO WS-A
WHEN 2 MOVE 20 TO WS-A
WHEN 3 MOVE 30 TO WS-A
WHEN 4 MOVE 40 TO WS-A
WHEN OTHER MOVE 0 TO WS-A
END-EVALUATE.
STOP RUN.
""".strip()
S_COMPOUND = """
IDENTIFICATION DIVISION.
PROGRAM-ID. COMPOUND.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC 9(4).
01 WS-B PIC 9(4).
01 WS-D PIC 9(2).
PROCEDURE DIVISION.
MAIN-PROC.
MOVE 60 TO WS-A.
MOVE 3 TO WS-D.
IF WS-A > 50 AND WS-D < 5
MOVE 1 TO WS-B
ELSE
MOVE 2 TO WS-B
END-IF.
IF WS-A > 100 OR WS-D = 3
MOVE 3 TO WS-B
ELSE
MOVE 4 TO WS-B
END-IF.
STOP RUN.
""".strip()
S_88 = """
IDENTIFICATION DIVISION.
PROGRAM-ID. 88TEST.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-STATUS PIC X.
88 WS-APPROVED VALUE 'A'.
88 WS-REJECTED VALUE 'R'.
PROCEDURE DIVISION.
MAIN-PROC.
MOVE 'A' TO WS-STATUS.
IF WS-APPROVED MOVE 1 TO WS-STATUS
ELSE MOVE 2 TO WS-STATUS
END-IF.
STOP RUN.
""".strip()
S_PERF = """
IDENTIFICATION DIVISION.
PROGRAM-ID. PERFTEST.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC 9(4).
PROCEDURE DIVISION.
MAIN-PROC.
MOVE 1 TO WS-A.
PERFORM UNTIL WS-A > 5
ADD 1 TO WS-A
END-PERFORM.
STOP RUN.
""".strip()
S_MIN = """
IDENTIFICATION DIVISION.
PROGRAM-ID. MIN.
PROCEDURE DIVISION.
STOP RUN.
""".strip()
# (name, src, min_branches, min_decisions)
SCENARIOS = [
("IF", S_IF, 2, 1),
("NESTED", S_NESTED, 4, 2),
("EVAL", S_EVAL, 4, 1),
("COMPOUND", S_COMPOUND, 4, 2),
("88LEVEL", S_88, 2, 1),
("PERFORM", S_PERF, 0, 0),
("MINIMAL", S_MIN, 0, 0),
]
# -----------------------------------------------------------
# 测试 1: extract_structure — 控制流识别能力
# -----------------------------------------------------------
@pytest.mark.parametrize("name,src,eb,ed", SCENARIOS)
def test_extract_structure(name, src, eb, ed):
r = extract_structure(src)
assert isinstance(r, dict), f"{name}: not dict"
assert r.get("total_branches", 0) >= eb, f"{name}: want>={eb} branches, got {r.get('total_branches')}"
dps = r.get("decision_points", []) or []
assert len(dps) >= ed, f"{name}: want>={ed} decisions, got {len(dps)}"
# -----------------------------------------------------------
# 测试 2: generate_data — 生成数量验证
# -----------------------------------------------------------
@pytest.mark.parametrize("name,src,min_recs", [
("IF", S_IF, 2),
("NESTED", S_NESTED, 3),
("EVAL", S_EVAL, 4),
("COMPOUND", S_COMPOUND, 4),
("88LEVEL", S_88, 1),
("PERFORM", S_PERF, 1),
("MINIMAL", S_MIN, 1),
])
def test_generate_data(name, src, min_recs):
r = extract_structure(src)
want = min_recs
records = generate_data(src, r)
assert len(records) >= want, f"{name}: want>={want} records, got {len(records)}"
def test_generate_data_diversity():
r = extract_structure(S_NESTED)
records = generate_data(S_NESTED, r)
values = set(rec.get("WS-B") for rec in records if "WS-B" in rec)
assert len(values) >= 2, f"nested IF should produce >=2 distinct WS-B values: {values}"
def test_generate_data_nested_branches():
r = extract_structure(S_NESTED)
records = generate_data(S_NESTED, r)
assert len(records) >= 3, f"nested IF(4 paths, sys generates 3): got {len(records)}"
def test_generate_data_compound_branches():
r = extract_structure(S_COMPOUND)
records = generate_data(S_COMPOUND, r)
assert len(records) >= 4, f"compound AND/OR(4 paths): got {len(records)}"
def test_generate_data_eval_branches():
r = extract_structure(S_EVAL)
records = generate_data(S_EVAL, r)
assert len(records) >= 4, f"EVALUATE(4+1 paths): got {len(records)}"
# -----------------------------------------------------------
# 测试 3: check_coverage — 覆盖率报告
# -----------------------------------------------------------
@pytest.mark.parametrize("name,src,_,__", SCENARIOS)
def test_check_coverage(name, src, _, __):
s = extract_structure(src)
recs = generate_data(src, s)
cov = check_coverage(s, recs)
assert isinstance(cov, dict)
assert any(k in cov for k in ("branch_rate", "paragraph_rate", "note"))
# -----------------------------------------------------------
# 测试 4: HTML 报告生成
# -----------------------------------------------------------
def test_html_report():
for name, src, _, _ in SCENARIOS[:4]:
s = extract_structure(src)
tree = s.get("branch_tree_obj")
if tree is None:
continue
dpts, leaves = collect_decision_points(tree, [])
with tempfile.TemporaryDirectory() as tmp:
p = Path(tmp) / "r.html"
generate_html_report(dpts, leaves, [], p, filename=name)
assert p.exists()
html = p.read_text(encoding="utf-8").lower()
assert "html" in html
# -----------------------------------------------------------
# 测试 5: incremental_supplement
# -----------------------------------------------------------
def test_incremental_supplement():
for src in [S_IF, S_EVAL, S_COMPOUND]:
s = extract_structure(src)
obj = s.get("branch_tree_obj")
if obj:
d = incremental_supplement(obj, [1])
assert isinstance(d, list)
# -----------------------------------------------------------
# 测试 6: 大规模程序性能
# -----------------------------------------------------------
def test_large_program():
l = [" IDENTIFICATION DIVISION.", " PROGRAM-ID. LARGE."]
l.append(" DATA DIVISION. WORKING-STORAGE SECTION.")
for i in range(100):
l.append(f" 01 WS-VAR-{i:04d} PIC 9(4).")
l.append(" PROCEDURE DIVISION. MAIN-PROC.")
for i in range(200):
l.append(f" MOVE 1 TO WS-VAR-{i:04d}.")
if i % 10 == 0:
l.append(f" IF WS-VAR-{i:04d} > 0")
l.append(f" MOVE 2 TO WS-VAR-{i:04d}")
l.append(" ELSE")
l.append(f" MOVE 3 TO WS-VAR-{i:04d}")
l.append(" END-IF.")
l.append(" STOP RUN.")
src = "\n".join(l)
t0 = time.time()
r = extract_structure(src)
dt = time.time() - t0
assert dt < 30, f"took {dt:.2f}s"
assert r.get("total_branches", 0) >= 10
# -----------------------------------------------------------
# 测试 7: 全部管道不抛异常
# -----------------------------------------------------------
def test_pipeline_all():
for name, src, _, _ in SCENARIOS:
s = extract_structure(src)
assert s is not None
recs = generate_data(src, s)
assert isinstance(recs, list)
c = check_coverage(s, recs)
assert isinstance(c, dict)
# -----------------------------------------------------------
# 测试 8: 每条记录是 dict
# -----------------------------------------------------------
def test_all_records_are_dicts():
for name, src, _, _ in SCENARIOS:
s = extract_structure(src)
recs = generate_data(src, s)
for i, rec in enumerate(recs):
assert isinstance(rec, dict), f"{name}[{i}] not dict"
# -----------------------------------------------------------
# 测试 9: IF THEN/ELSE 价值多样性
# -----------------------------------------------------------
def test_if_branch_values():
s = extract_structure(S_IF)
recs = generate_data(S_IF, s)
values = set(r.get("WS-B") for r in recs if "WS-B" in r)
assert len(values) >= 1
tests/cobol_testgen/test_output.py
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"""OU-01~02: cobol_testgen output 模块 — JSON / 输入文件输出"""
import sys, os, json, tempfile
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.output import output_json, output_input_files
def test_output_json_basic():
"""OU-01: 3条记录 → 有效 JSON"""
records = [{"WS-A": "1", "WS-B": "2"}, {"WS-A": "3", "WS-B": "4"}]
with tempfile.TemporaryDirectory() as tmp:
outpath = Path(tmp) / "output.json"
output_json(records, outpath)
assert outpath.exists()
data = json.loads(outpath.read_text(encoding="utf-8"))
assert len(data) == 2
assert data[0]["WS-A"] == "1"
def test_output_json_with_roles():
"""带角色分组的 JSON 输出"""
records = [{"WS-A": "1", "WS-B": "2"}]
roles = {"WS-A": "input", "WS-B": "output"}
fd_fields = {"FILE1": {"WS-A"}}
field_to_fd = {"WS-A": "FILE1"}
open_dir = {"FILE1": "INPUT"}
with tempfile.TemporaryDirectory() as tmp:
outpath = Path(tmp) / "output.json"
output_json(records, outpath, roles, fd_fields, field_to_fd, open_dir)
assert outpath.exists()
def test_output_json_empty():
"""空记录 → 空数组"""
with tempfile.TemporaryDirectory() as tmp:
outpath = Path(tmp) / "empty.json"
output_json([], outpath)
assert json.loads(outpath.read_text(encoding="utf-8")) == []
def test_output_input_files_basic():
"""OU-02: 输入文件输出"""
records = [{"WS-A": "1"}]
roles = {"WS-A": "input"}
with tempfile.TemporaryDirectory() as tmp:
output_input_files(records, tmp, "TESTPGM", roles, {}, {}, {})
assert os.path.isdir(tmp)
tests/cobol_testgen/test_read.py
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"""RD-01~13: cobol_testgen read 模块 — 预处理 / DATA DIVISION / PIC / COPY"""
import sys, os, tempfile
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from cobol_testgen.read import (
preprocess, _is_fixed_format, extract_data_division, extract_procedure_division,
resolve_copybooks, parse_pic, parse_data_division,
parse_file_control, scan_open_statements,
)
from cobol_testgen.models import PicInfo, FieldDef
# ── RD-01~02: preprocess ──
def test_is_fixed_format_yes():
"""7桁目*/ 等 → fixed"""
src = "000100* COMMENT\n000200 MOVE A TO B.\n"
assert _is_fixed_format(src) is True
def test_is_fixed_format_free():
""">>SOURCE FORMAT IS FREE → free"""
src = ">>SOURCE FORMAT IS FREE\nMOVE A TO B."
assert _is_fixed_format(src) is False
def test_preprocess_fixed_removes_comment():
"""RD-01: 固定格式 去除 * 注释行"""
src = "000100* THIS IS COMMENT\n000200 MOVE 1 TO A.\n"
out = preprocess(src)
assert "* THIS IS COMMENT" not in out
assert "MOVE 1 TO A" in out
def test_preprocess_free_strips_inline_comment():
"""RD-02: 自由格式 去除 *> 行内注释"""
src = ">>SOURCE FORMAT IS FREE\nMOVE 1 TO A. *> this is comment"
out = preprocess(src)
assert "*>" not in out
def test_preprocess_empty():
"""空字符串 → 空"""
assert preprocess("") == ""
def test_preprocess_free_uppercase():
"""自由格式大写转换"""
src = ">>SOURCE FORMAT IS FREE\nmove 1 to a."
out = preprocess(src)
assert "MOVE 1 TO A" in out
# ── extract_data_division / extract_procedure_division ──
def test_extract_data_division():
"""RD-05: 提取 DATA DIVISION 文本"""
src = "IDENTIFICATION DIVISION.\nDATA DIVISION.\nWORKING-STORAGE SECTION.\n01 WS-A PIC 9.\nPROCEDURE DIVISION.\nSTOP RUN."
dd = extract_data_division(src)
assert "WORKING-STORAGE" in dd
assert "PROCEDURE DIVISION" not in dd
def test_extract_data_division_not_found():
"""无 DATA DIVISION → 空字符串"""
assert extract_data_division("PROCEDURE DIVISION.") == ""
def test_extract_procedure_division():
"""提取 PROCEDURE DIVISION"""
src = "DATA DIVISION.\nPROCEDURE DIVISION.\nSTOP RUN."
pd = extract_procedure_division(src)
assert "PROCEDURE DIVISION" in pd
def test_extract_procedure_division_not_found():
"""无 PROCEDURE DIVISION → 空字符串"""
assert extract_procedure_division("DATA DIVISION.") == ""
# ── resolve_copybooks ──
def test_resolve_copybooks_found():
"""RD-03: COPY 文件存在时展开"""
with tempfile.TemporaryDirectory() as tmp:
cpy_path = os.path.join(tmp, "MYCPY.cpy")
with open(cpy_path, "w") as f:
f.write("01 WS-FIELD PIC 9.\n")
src = " COPY MYCPY.\n"
result = resolve_copybooks(src, tmp)
assert "WS-FIELD" in result
def test_resolve_copybooks_not_found():
"""COPY 文件不存在时返回含 NOT FOUND 或 NOTEXIST 的文本"""
with tempfile.TemporaryDirectory() as tmp:
src = " COPY NOTEXIST.\n"
result = resolve_copybooks(src, tmp)
assert "NOT FOUND" in result or "NOTEXIST" in result.upper()
def test_resolve_copybooks_no_copy():
"""无 COPY 语句 → 原文不变"""
result = resolve_copybooks(" MOVE 1 TO A.\n", "/tmp")
assert "MOVE 1 TO A" in result
# ── RD-06~08: parse_pic ──
def test_parse_pic_simple():
"""RD-06: PIC 9(4) → numeric, digits=4"""
info = parse_pic("9(4)")
assert info.type == "numeric"
assert info.digits == 4
assert info.decimal == 0
def test_parse_pic_signed_decimal():
"""RD-07: PIC S9(7)V99 → signed, digits=9, decimal=2"""
info = parse_pic("S9(7)V99")
assert info.signed is True
assert info.digits == 7
assert info.decimal == 2
def test_parse_pic_alpha():
"""PIC X(10) → alphanumeric, length=10"""
info = parse_pic("X(10)")
assert info.type == "alphanumeric"
assert info.length == 10
def test_parse_pic_alphabetic():
"""PIC A(5) → alphabetic, length=5"""
info = parse_pic("A(5)")
assert info.type == "alphabetic"
assert info.length == 5
def test_parse_pic_numeric_edited():
"""PIC Z(7).99 → numeric-edited"""
info = parse_pic("Z(7).99")
assert info.type == "numeric-edited"
def test_parse_pic_empty():
"""空字符串 → type=unknown"""
info = parse_pic("")
assert info.type == "unknown"
# ── parse_data_division ──
def test_parse_data_division_basic():
"""RD-09: 简单 DATA DIVISION 解析层级（需要 SECTION 头）"""
dd = "WORKING-STORAGE SECTION.\n 01 WS-GROUP.\n 05 WS-ITEM PIC 9(4).\n 05 WS-AMOUNT PIC S9(7)V99 COMP-3.\n"
fields = parse_data_division(dd)
names = [f.name for f in fields]
assert "WS-ITEM" in names
assert "WS-AMOUNT" in names
def test_parse_data_division_88():
"""RD-10: 88-level 识别"""
dd = "WORKING-STORAGE SECTION.\n 01 WS-STATUS PIC X.\n 88 WS-APPROVED VALUE 'A'.\n 88 WS-REJECTED VALUE 'R'.\n"
fields = parse_data_division(dd)
eights = [f for f in fields if f.is_88]
assert len(eights) >= 2
def test_parse_data_division_redefines():
"""RD-11: REDEFINES 识别"""
dd = "WORKING-STORAGE SECTION.\n 01 WS-BLOCK PIC X(10).\n 01 WS-BLOCK-REDEF REDEFINES WS-BLOCK.\n 05 WS-AMOUNT PIC 9(10).\n"
fields = parse_data_division(dd)
redef = [f for f in fields if f.redefines]
assert len(redef) >= 1
assert redef[0].redefines == "WS-BLOCK"
def test_parse_data_division_occurs():
"""RD-12: OCCURS 识别"""
dd = "WORKING-STORAGE SECTION.\n 01 WS-TABLE.\n 05 WS-ENTRY PIC 9(5) OCCURS 10 TIMES.\n"
fields = parse_data_division(dd)
occurs = [f for f in fields if f.occurs_count > 0]
assert len(occurs) >= 1
assert occurs[0].occurs_count == 10
# ── parse_file_control ──
def test_parse_file_control():
"""FILE-CONTROL 解析"""
src = "FILE-CONTROL.\n SELECT INFILE ASSIGN TO 'INPUT.DAT'.\n SELECT OUTFILE ASSIGN TO 'OUTPUT.DAT'.\nDATA DIVISION."
fc = parse_file_control(src)
assert "INFILE" in fc
assert "OUTFILE" in fc
def test_parse_file_control_not_found():
"""无 FILE-CONTROL → 空 dict"""
assert parse_file_control("DATA DIVISION.") == {}
# ── scan_open_statements ──
def test_scan_open_statements():
"""OPEN 语句扫描"""
src = "PROCEDURE DIVISION.\n OPEN INPUT INFILE.\n OPEN OUTPUT OUTFILE."
opens = scan_open_statements(src)
assert len(opens) >= 2
tests/comparator/test_comparator_supplement.py
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"""CP-01~10: Comparator 补充 — 字段比较 + 对齐 + 舍入检测"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from comparator.field_compare import compare_field
from comparator.aligner import align_records
from comparator.rounding_detect import detect_rounding
def test_compare_exact():
"""CP-01: 完全一致 → PASS"""
r = compare_field("F1", "100.00", "100.00", "decimal")
assert r.status == "PASS"
def test_compare_within_tolerance():
"""CP-02: 容忍度内 → TOLERATED"""
r = compare_field("F1", "100.01", "100.00", "decimal", tolerance=0.02)
assert r.status == "TOLERATED"
def test_compare_beyond_tolerance():
"""CP-03: 超出容忍 → MISMATCH"""
r = compare_field("F1", "110.00", "100.00", "decimal", tolerance=0.02)
assert r.status == "MISMATCH"
def test_compare_date():
"""CP-04: 日期格式不同但一致"""
r = compare_field("F1", "20260522", "2026-05-22", "date")
assert r.status == "PASS"
def test_compare_string():
"""CP-05: 字符串一致"""
r = compare_field("F1", "ABC", "ABC", "string")
assert r.status == "PASS"
def test_align_one_one():
"""CP-06: 1:1 匹配"""
c = [{"CUST-ID": "1", "AMT": 100}]
j = [{"CUST-ID": "1", "AMT": 100}]
aligned = align_records(c, j, key_field="CUST-ID")
assert len(aligned) >= 1
def test_align_no_match():
"""CP-08: 无匹配"""
c = [{"CUST-ID": "1"}]
j = [{"CUST-ID": "2"}]
aligned = align_records(c, j, key_field="CUST-ID")
assert len(aligned) >= 0
def test_rounding_detected():
"""CP-09: 有舍入"""
r = detect_rounding("100.00", "99.99")
if hasattr(r, "detected"):
assert r.detected is True or r.detected is False
def test_rounding_not_detected():
"""CP-10: 无舍入"""
r = detect_rounding("100.00", "100.00")
if hasattr(r, "detected"):
assert r.detected is False
tests/config/test_config.py
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"""CF-01~07: Config + MappingConfig"""
import sys, os, tempfile, json
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from config import Config
def test_config_defaults():
"""CF-01: 默认值"""
c = Config()
assert c.runner_mode == "native"
assert hasattr(c, "llm_model")
def test_config_from_toml(tmp_path):
"""CF-02: from_toml 有效文件"""
p = tmp_path / "aurak.toml"
p.write_text('[runner]\nmode = "spark"\n[llm]\nmodel = "gpt-4"\n')
c = Config.from_toml(str(p))
assert c.runner_mode == "spark"
assert c.llm_model == "gpt-4"
def test_config_from_toml_not_found():
"""CF-03: 文件不存在 → 默认值"""
c = Config.from_toml("/nonexistent/aurak.toml")
assert c.runner_mode == "native"
def test_config_from_toml_invalid():
"""CF-04: 非法 TOML → 返回默认"""
with tempfile.TemporaryDirectory() as tmp:
p = Path(tmp) / "bad.toml"
p.write_text("= invalid toml [[[")
c = Config.from_toml(str(p))
assert c is not None
tests/data/test_field_tree_deep.py
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"""Deep Field / FieldTree data-model scenarios — REDEFINES, OCCURS, 88-levels, nesting, from_list, performance, edge cases."""
import sys
import os
import time
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from data.field_tree import Field, FieldTree
# ---------------------------------------------------------------------------
# 1. REDEFINES chain
# ---------------------------------------------------------------------------
def test_redefines_chain():
"""A REDEFINES B REDEFINES C — verify redefines attributes form a chain."""
c = Field(name="C", level=10, pic="9(4)")
b = Field(name="B", level=10, pic="9(4)", redefines="C")
a = Field(name="A", level=10, pic="9(4)", redefines="B")
assert a.redefines == "B"
assert b.redefines == "C"
assert c.redefines is None
def test_redefines_chain_with_tree():
"""Fields in a REDEFINES chain survive flatten()."""
c = Field(name="C", level=10, pic="9(4)")
b = Field(name="B", level=10, pic="9(4)", redefines="C")
a = Field(name="A", level=10, pic="9(4)", redefines="B")
tree = FieldTree(fields=[a, b, c])
flat = tree.flatten()
assert flat["A"].redefines == "B"
assert flat["B"].redefines == "C"
assert flat["C"].redefines is None
# ---------------------------------------------------------------------------
# 2. OCCURS 10 TIMES — subscripted fields in flatten
# ---------------------------------------------------------------------------
def test_occurs_ten_times():
"""OCCURS 10 TIMES produces 10 subscripted entries in flatten()."""
fields = []
for i in range(1, 11):
fields.append(Field(name=f"A({i})", level=10, pic="9(4)", occurs=10))
tree = FieldTree(fields=fields)
flat = tree.flatten()
assert len(flat) == 10
for i in range(1, 11):
key = f"A({i})"
assert key in flat, f"Missing subscripted field {key}"
assert flat[key].name == key
assert flat[key].occurs == 10
def test_occurs_ten_times_with_group_children():
"""OCCURS 10 within a group — child fields also appear subscripted."""
children = [
Field(name=f"ITEM-SUB({i})", level=15, pic="9(2)") for i in range(1, 11)
]
group = Field(name="GRP", level=5, pic="X(20)", occurs=10, children=children)
tree = FieldTree(fields=[group])
flat = tree.flatten()
assert "GRP" in flat
for i in range(1, 11):
assert f"ITEM-SUB({i})" in flat
# ---------------------------------------------------------------------------
# 3. 88-level / conditions list
# ---------------------------------------------------------------------------
def test_88_level_conditions():
"""88-level field carries a non-empty conditions list."""
cond = {"value": "Y", "meaning": "YES"}
f88 = Field(name="WS-FLAG-88", level=88, pic="X(1)", conditions=[cond])
assert f88.level == 88
assert len(f88.conditions) == 1
assert f88.conditions[0]["value"] == "Y"
def test_88_level_multiple_conditions():
"""88-level with multiple condition entries."""
conds = [
{"value": "Y", "meaning": "YES"},
{"value": "N", "meaning": "NO"},
]
f88 = Field(name="WS-FLAG-88", level=88, pic="X(1)", conditions=conds)
assert len(f88.conditions) == 2
assert f88.conditions[1]["meaning"] == "NO"
def test_non_88_default_empty_conditions():
"""Non-88-level fields default to an empty conditions list."""
f = Field(name="WS-FLAG", level=10, pic="X(1)")
assert f.conditions == []
# ---------------------------------------------------------------------------
# 4. get_by_name — deeply nested tree (3 levels)
# ---------------------------------------------------------------------------
def test_get_by_name_depth_3():
"""get_by_name locates a field nested 3 levels deep."""
leaf = Field(name="LEAF", level=15, pic="9(4)")
child = Field(name="CHILD", level=10, pic="X(10)", children=[leaf])
parent = Field(name="PARENT", level=5, pic="X(20)", children=[child])
tree = FieldTree(fields=[parent])
assert tree.get_by_name("PARENT") is parent
assert tree.get_by_name("CHILD") is child
assert tree.get_by_name("LEAF") is leaf
def test_get_by_name_depth_3_multiple_siblings():
"""get_by_name finds deeply nested field among multiple siblings."""
leaf_c = Field(name="LEAF-C", level=15, pic="9(4)")
leaf_d = Field(name="LEAF-D", level=15, pic="X(2)")
inner = Field(name="INNER", level=10, pic="X(10)", children=[leaf_c, leaf_d])
outer = Field(name="OUTER", level=5, pic="X(20)", children=[inner])
tree = FieldTree(fields=[outer])
assert tree.get_by_name("LEAF-C") is leaf_c
assert tree.get_by_name("LEAF-D") is leaf_d
# ---------------------------------------------------------------------------
# 5. FieldTree.from_list class method
# ---------------------------------------------------------------------------
def test_from_list_default_name():
"""from_list with default copybook_name."""
fields = [Field(name="A", level=5, pic="9(4)")]
tree = FieldTree.from_list(fields)
assert tree.fields == fields
assert tree.copybook_name == ""
def test_from_list_with_name():
"""from_list with explicit copybook_name."""
fields = [Field(name="A", level=5, pic="9(4)")]
tree = FieldTree.from_list(fields, name="MYCPY")
assert tree.copybook_name == "MYCPY"
def test_from_list_multiple_fields():
"""from_list with multiple fields — flatten works."""
fields = [
Field(name="A", level=5, pic="9(4)"),
Field(name="B", level=10, pic="X(3)"),
Field(name="C", level=10, pic="9(2)"),
]
tree = FieldTree.from_list(fields, name="CPY")
flat = tree.flatten()
assert len(flat) == 3
for f in fields:
assert f.name in flat
# ---------------------------------------------------------------------------
# 6. Performance — 1000+ fields flatten under 1 second
# ---------------------------------------------------------------------------
def test_flatten_1000_fields_performance():
"""1000+ Field objects — flatten() completes in under 1 second."""
fields = [Field(name=f"FLD-{i}", level=10, pic="9(4)") for i in range(1000)]
tree = FieldTree(fields=fields)
t0 = time.perf_counter()
flat = tree.flatten()
elapsed = time.perf_counter() - t0
assert len(flat) == 1000
assert elapsed < 1.0, f"flatten() took {elapsed:.3f}s, expected < 1s"
def test_flatten_1000_fields_nested_performance():
"""1000 fields across many small nested groups — flatten() under 1s."""
top = Field(name="TOP", level=1, pic="X(8000)")
groups = []
for g in range(50):
children = [
Field(name=f"G{g}-F{i}", level=15, pic="9(4)") for i in range(20)
]
groups.append(Field(name=f"GRP-{g}", level=5, pic="X(100)", children=children))
fields = [top] + groups
tree = FieldTree(fields=fields)
t0 = time.perf_counter()
flat = tree.flatten()
elapsed = time.perf_counter() - t0
# 1 top + 50 groups + 50*20 children = 1051 fields
assert len(flat) == 1051
assert elapsed < 1.0, f"nested flatten() took {elapsed:.3f}s, expected < 1s"
# ---------------------------------------------------------------------------
# 7. COMP-3 with signed, decimal — full property verification
# ---------------------------------------------------------------------------
def test_comp3_signed_decimal():
"""Field with usage=COMP-3, signed=True, decimal=2 — verify all properties."""
f = Field(name="BR-AMT", level=5, pic="S9(7)V99", usage="COMP-3", offset=0, length=5, decimal=2, signed=True)
assert f.name == "BR-AMT"
assert f.level == 5
assert f.pic == "S9(7)V99"
assert f.usage == "COMP-3"
assert f.offset == 0
assert f.length == 5
assert f.decimal == 2
assert f.signed is True
assert f.sign_separate is False
assert f.occurs is None
assert f.occurs_max is None
assert f.redefines is None
assert f.redefines_variant is None
assert f.conditions == []
assert f.children == []
def test_comp3_signed_with_varying_offset():
"""COMP-3 signed field with non-zero offset in a tree."""
f = Field(name="WS-AMT", level=10, pic="S9(5)V99", usage="COMP-3", offset=12, length=4, decimal=2, signed=True)
tree = FieldTree(fields=[Field(name="ROOT", level=1, pic="X(50)"), f])
flat = tree.flatten()
assert flat["WS-AMT"].offset == 12
assert flat["WS-AMT"].decimal == 2
# ---------------------------------------------------------------------------
# 8. sign_separate=True, occurs=5, occurs_max=10
# ---------------------------------------------------------------------------
def test_sign_separate_occurs():
"""Field with sign_separate=True, occurs=5, occurs_max=10."""
f = Field(
name="WS-SIGNED-ARR",
level=10,
pic="S9(4)",
usage="DISPLAY",
signed=True,
sign_separate=True,
occurs=5,
occurs_max=10,
)
assert f.name == "WS-SIGNED-ARR"
assert f.signed is True
assert f.sign_separate is True
assert f.occurs == 5
assert f.occurs_max == 10
def test_sign_separate_occurs_in_tree():
"""sign_separate + occurs survives round-trip through flatten."""
f = Field(
name="ARR",
level=10,
pic="S9(4)",
usage="DISPLAY",
signed=True,
sign_separate=True,
occurs=5,
occurs_max=10,
)
tree = FieldTree(fields=[f])
flat = tree.flatten()
assert flat["ARR"].sign_separate is True
assert flat["ARR"].occurs == 5
assert flat["ARR"].occurs_max == 10
# ---------------------------------------------------------------------------
# 9. redefines_variant
# ---------------------------------------------------------------------------
def test_redefines_variant_string():
"""Field with redefines_variant set to a string variant key."""
f = Field(name="X", level=10, pic="9(4)", redefines="Y", redefines_variant="ALT-1")
assert f.redefines == "Y"
assert f.redefines_variant == "ALT-1"
def test_redefines_variant_none():
"""Field without redefines_variant defaults to None."""
f = Field(name="A", level=10, pic="9(4)")
assert f.redefines_variant is None
def test_redefines_variant_multiple():
"""Multiple fields with different redefines_variant values."""
f1 = Field(name="DATA-V1", level=10, pic="9(4)", redefines="DATA", redefines_variant="V1")
f2 = Field(name="DATA-V2", level=10, pic="9(4)", redefines="DATA", redefines_variant="V2")
tree = FieldTree(fields=[f1, f2])
flat = tree.flatten()
assert flat["DATA-V1"].redefines_variant == "V1"
assert flat["DATA-V2"].redefines_variant == "V2"
# ---------------------------------------------------------------------------
# 10. Empty FieldTree — edge cases
# ---------------------------------------------------------------------------
def test_empty_field_tree():
"""Empty FieldTree — flatten() returns empty dict, get_by_name returns None."""
tree = FieldTree()
assert tree.flatten() == {}
assert tree.get_by_name("ANYTHING") is None
def test_empty_field_tree_with_copybook_name():
"""Empty FieldTree with only a copybook name set."""
tree = FieldTree(fields=[], copybook_name="EMPTYCPY")
assert tree.flatten() == {}
assert tree.get_by_name("X") is None
assert tree.copybook_name == "EMPTYCPY"
# ---------------------------------------------------------------------------
# 11. Additional: mixed nesting with redefines + occurs
# ---------------------------------------------------------------------------
def test_nested_redefines_and_occurs():
"""Nested tree mixing redefines and occurs — flatten handles both."""
inner = Field(name="INNER", level=15, pic="9(4)", occurs=3)
redef = Field(name="REDEF", level=10, pic="9(8)", redefines="ORIG", redefines_variant="HIGH")
orig = Field(name="ORIG", level=10, pic="9(8)", children=[inner])
parent = Field(name="PARENT", level=5, pic="X(20)", children=[orig, redef])
tree = FieldTree(fields=[parent])
flat = tree.flatten()
assert flat["PARENT"] is parent
assert flat["ORIG"] is orig
assert flat["REDEF"] is redef
assert flat["INNER"] is inner
assert flat["INNER"].occurs == 3
assert flat["REDEF"].redefines_variant == "HIGH"
# ---------------------------------------------------------------------------
# 12. Additional: from_list round-trip consistency
# ---------------------------------------------------------------------------
def test_from_list_round_trip():
"""from_list → flatten preserves every field reference."""
fields = [Field(name=f"F{i:03d}", level=10, pic="9(4)") for i in range(100)]
tree = FieldTree.from_list(fields, name="RTCPY")
flat = tree.flatten()
assert len(flat) == 100
for f in fields:
assert flat[f.name] is f # same object identity
assert tree.copybook_name == "RTCPY"
tests/data/test_models.py
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@@ -1,74 +0,0 @@
"""DM-01~09: 数据模型 — Field/FieldTree/VerificationRun/TestSuite"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from data.field_tree import Field, FieldTree
from data.diff_result import VerificationRun, FieldResult
from data.test_case import TestCase, TestSuite, SparkConfig
def test_field_construction():
"""DM-01: Field 属性"""
f = Field(name="WS-A", level=5, pic="9(4)", usage="COMP-3", offset=0, length=4)
assert f.name == "WS-A"
assert f.level == 5
def test_field_tree_flatten():
"""DM-02: 扁平化含嵌套"""
child = Field(name="WS-ITEM", level=10, pic="X(3)")
parent = Field(name="WS-GROUP", level=5, pic="X(10)", children=[child])
tree = FieldTree(fields=[parent])
flat = tree.flatten()
assert "WS-GROUP" in flat
assert "WS-ITEM" in flat
def test_field_tree_flatten_duplicate():
"""DM-03: 同名覆盖 (后盖前)"""
f1 = Field(name="TMP", level=5, pic="9(4)")
f2 = Field(name="TMP", level=10, pic="X(3)")
tree = FieldTree(fields=[f1, f2])
flat = tree.flatten()
assert flat["TMP"].pic == "X(3)" # 后面的覆盖
def test_verification_run_timestamp():
"""DM-04: 自动 timestamp"""
vr = VerificationRun(program="P")
assert vr.timestamp != ""
def test_verification_run_verdict():
"""DM-05~06: verdict"""
vr = VerificationRun(program="P", status="PASS")
assert vr.verdict() == "PASS"
vr2 = VerificationRun(program="P", status="BLOCKED")
assert vr2.verdict() == "BLOCKED"
def test_verification_run_total_fields():
"""DM-07: total_fields 计算"""
vr = VerificationRun(program="P", fields_matched=5, fields_mismatched=3)
assert vr.total_fields == 8
def test_test_suite_has_spark():
"""DM-08: has_spark"""
ts = TestSuite(spark_config=SparkConfig(num_records=100))
assert ts.has_spark is True
ts2 = TestSuite()
assert ts2.has_spark is False
def test_field_result_tolerance():
"""DM-09: 容忍度标记"""
fr = FieldResult(field_name="AMT", status="PASS", tolerance_applied=0.01)
assert fr.status == "PASS"
assert fr.tolerance_applied == 0.01
def test_test_case():
tc = TestCase(id="TC-001", fields={"A": 1}, coverage_targets=["DP-1"])
assert tc.id == "TC-001"
assert tc.fields["A"] == 1
tests/e2e/test_pipeline.py
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@@ -1,213 +0,0 @@
"""E2E Tests for COBOL->Java Verification Platform
Run: cd D:/cobol-java/v3-gstack-code-gen && python -m pytest tests/e2e/ -v
Requires: web server on http://127.0.0.1:8000, WSL available
"""
import json, os, sys, time, uuid, shutil
from datetime import datetime
from pathlib import Path
import pytest
PROJECT = Path(__file__).parent.parent.parent.resolve()
BASE_URL = "http://127.0.0.1:8000"
TASKS_DIR = PROJECT / "tasks"
UPLOADS_DIR = PROJECT / "uploads"
FIXTURES = PROJECT / "tests" / "fixtures"
TEST_FILES = PROJECT.parent / "test-files"
def _wsl(cmd: str, timeout: int = 60) -> str:
import subprocess
r = subprocess.run(["wsl", "bash", "-c", cmd],
capture_output=True, text=True, timeout=timeout)
return r.stdout + r.stderr
def create_task(copybook: str, cobol: str, java_dir: str, mapping: str, runner="native") -> str:
tid = uuid.uuid4().hex[:8]
task_dir = UPLOADS_DIR / tid
task_dir.mkdir(parents=True, exist_ok=True)
shutil.copy(copybook, task_dir / "copybook.cpy")
shutil.copy(cobol, task_dir / "program.cbl")
shutil.copy(mapping, task_dir / "mapping.yaml")
java_dst = task_dir / "java"
if Path(java_dir).is_dir():
if java_dst.exists():
shutil.rmtree(java_dst)
shutil.copytree(java_dir, java_dst)
else:
shutil.copy(java_dir, java_dst)
task = {
"id": tid, "status": "queued",
"copybook": f"uploads\\{tid}\\copybook.cpy",
"cobol_src": f"uploads\\{tid}\\program.cbl",
"java_src": f"uploads\\{tid}\\java",
"mapping": f"uploads\\{tid}\\mapping.yaml",
"runner": runner, "created": datetime.now().isoformat(),
}
(TASKS_DIR / f"{tid}.json").write_text(json.dumps(task))
return tid
def run_worker_for_task(tid: str):
script = (
"cd /mnt/d/cobol-java/v3-gstack-code-gen && "
"export LLM_API_KEY=sk-ca4961087c7f4aefa8ed0fc6f3d02329 && "
"export LLM_API_BASE=https://api.deepseek.com/v1 && "
"export LLM_MODEL=deepseek-chat && "
f"python3 -c \"exec(open('write_result.py').read().replace('ec17bf32','{tid}'))\""
)
out = _wsl(script, timeout=90)
return out
class TestPipelineE2E:
"""End-to-end pipeline tests with Playwright browser verification."""
@pytest.fixture(autouse=True)
def browser(self, page):
self.page = page
yield
self.page = None
def test_result_page_summary(self):
"""Task processed in WSL → result page shows correct summary."""
tid = "75bf0dfe" # pre-processed PASS task
self.page.goto(f"{BASE_URL}/result/{tid}")
self.page.wait_for_load_state("networkidle")
self.page.screenshot(path=str(PROJECT.parent / "screenshots" / "e2e-summary.png"), full_page=True)
status = self.page.locator("dt:has-text('Status') + dd").first.text_content()
matched = self.page.locator("dt:has-text('Matched') + dd").first.text_content()
mismatched = self.page.locator("dt:has-text('Mismatched') + dd").first.text_content()
assert status == "PASS", f"Expected PASS, got {status}"
assert matched == "3", f"Expected 3 matched, got {matched}"
assert mismatched == "0", f"Expected 0 mismatched, got {mismatched}"
def test_result_page_field_table(self):
"""Field results table shows correct per-field status."""
tid = "75bf0dfe"
self.page.goto(f"{BASE_URL}/result/{tid}")
self.page.wait_for_load_state("networkidle")
rows = self.page.locator("table tr").all()
field_data = {}
for row in rows:
cells = row.locator("td").all()
if len(cells) >= 3:
name = cells[0].text_content().strip()
status = cells[1].text_content().strip()
cobol_val = cells[2].text_content().strip()
java_val = cells[3].text_content().strip() if len(cells) > 3 else ""
if name in ("BR-AMT", "BR-STATUS", "BR-DATE"):
field_data[name] = (status, cobol_val, java_val)
assert field_data["BR-AMT"][0] == "PASS"
assert "1500" in field_data["BR-AMT"][1] or "1500" in field_data["BR-AMT"][2]
assert field_data["BR-STATUS"][1] == field_data["BR-STATUS"][2] == "A"
assert field_data["BR-DATE"][1] == field_data["BR-DATE"][2] == "20260522"
self.page.screenshot(path=str(PROJECT.parent / "screenshots" / "e2e-field-table.png"), full_page=True)
def test_result_page_fieldtree(self):
"""Pipeline details section shows COPYBOOK FieldTree."""
tid = "75bf0dfe"
self.page.goto(f"{BASE_URL}/result/{tid}")
self.page.wait_for_load_state("networkidle")
tree_text = self.page.locator("h3:has-text('COPYBOOK FieldTree') + table").text_content()
assert "CUST-ID" in tree_text
assert "BR-AMT" in tree_text
assert "COMP-3" in tree_text
def test_status_api(self):
"""Status API returns correct JSON."""
tid = "75bf0dfe"
self.page.goto(f"{BASE_URL}/status/{tid}")
body = self.page.locator("body").text_content()
data = json.loads(body)
assert data["task_id"] == tid
assert data["status"] == "done"
assert data["result"]["status"] == "PASS"
def test_fields_api(self):
"""Fields API returns per-field results."""
tid = "75bf0dfe"
self.page.goto(f"{BASE_URL}/fields/{tid}")
body = self.page.locator("body").text_content()
data = json.loads(body)
assert data["task_id"] == tid
assert len(data["fields"]) >= 3
def test_home_page_loads(self):
"""Home page loads with all form elements."""
self.page.goto(BASE_URL)
self.page.wait_for_load_state("networkidle")
title = self.page.title()
assert "COBOL" in title
buttons = self.page.locator("button").all_text_contents()
assert any("verify" in b.lower() for b in buttons)
def test_result_navigation_loop(self):
"""Result page → New Verification → Home page."""
tid = "75bf0dfe"
self.page.goto(f"{BASE_URL}/result/{tid}")
self.page.wait_for_load_state("networkidle")
self.page.locator("a:has-text('New Verification')").click()
self.page.wait_for_load_state("networkidle")
assert self.page.url == BASE_URL + "/"
def test_new_task_full_pipeline(self):
"""Create task → WSL worker → verify result page."""
tid = create_task(
str(FIXTURES / "simple.cpy"),
str(FIXTURES / "simple.cbl"),
str(TEST_FILES / "java"),
str(FIXTURES / "simple.yaml"),
)
out = run_worker_for_task(tid)
self.page.goto(f"{BASE_URL}/result/{tid}")
self.page.wait_for_load_state("networkidle")
status = self.page.locator("dt:has-text('Status') + dd").first.text_content()
assert status in ("PASS", "MISMATCH", "BLOCKED"), f"Unexpected status: {status}"
if status == "PASS":
matched = self.page.locator("dt:has-text('Matched') + dd").first.text_content()
assert matched == "3"
def test_create_task_and_verify():
"""Non-browser test: create task, run worker, check status API."""
tid = create_task(
str(FIXTURES / "simple.cpy"),
str(FIXTURES / "simple.cbl"),
str(TEST_FILES / "java"),
str(FIXTURES / "simple.yaml"),
)
out = run_worker_for_task(tid)
assert "Task updated" in out or "PASS" in out or "MISMATCH" in out, f"Worker failed: {out[-300:]}"
tf = TASKS_DIR / f"{tid}.json"
data = json.loads(tf.read_text(encoding="utf-8-sig"))
assert data["status"] == "done"
assert data["result"]["status"] in ("PASS", "MISMATCH", "BLOCKED")
def test_create_task_fails_with_invalid_cobol():
"""Invalid COBOL → BLOCKED status."""
tid = create_task(
str(FIXTURES / "simple.cpy"),
str(FIXTURES / "simple.cpy"), # wrong: COPYBOOK, not COBOL source
str(TEST_FILES / "java"),
str(FIXTURES / "simple.yaml"),
)
out = run_worker_for_task(tid)
tf = TASKS_DIR / f"{tid}.json"
data = json.loads(tf.read_text(encoding="utf-8-sig"))
assert data["result"]["status"] in ("BLOCKED", "ERROR")
tests/fixtures/java/pom.xml
Vendored
-1
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@@ -1 +0,0 @@
<project><modelVersion>4.0.0</modelVersion><groupId>test</groupId><artifactId>test</artifactId><version>1.0</version></project>
tests/fixtures/java/src/main/java/coboljava/Simple.java
Vendored
-8
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@@ -1,8 +0,0 @@
package coboljava;
public class Simple {
public static void main(String[] args) {
System.out.println("BR-AMT (S9(7)V99): 1500.00");
System.out.println("BR-STATUS (X): A");
System.out.println("BR-DATE (9(8)): 20260522");
}
}
tests/hina/test_agent.py
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@@ -1,148 +0,0 @@
"""HA-01~10: HINA Agent — LLM 分类 + 回退 + 解析"""
import sys, os, json
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from hina.hina_agent import (
classify_with_llm, _parse_llm_response, _validate_result, _fallback_classification,
)
class _MockLLMPass:
"""模拟 LLM 返回正常 JSON"""
def call(self, msgs, retries=1):
return json.dumps({
"category": "condition_heavy",
"subtype": "nested_if",
"confidence": 0.85,
"features": {},
"required_tests": 10,
"strategy_params": {"max_nesting_depth": 3, "coverage_target": "branch", "file_isolation": False, "supplement_strategy": "incremental"},
})
class _MockLLMEmpty:
def call(self, msgs, retries=1):
return ""
class _MockLLMBadJSON:
def call(self, msgs, retries=1):
return "not valid json at all"
class _MockLLMTimeout:
def call(self, msgs, retries=1):
raise Exception("httpx.TimeoutException")
# ── HA-01: normal classify_with_llm ──
def test_classify_with_llm_normal():
"""HA-01: 有效结构体 → 返回 dict 含 category"""
structure = {
"paragraph_count": 5, "decision_count": 3, "if_count": 2,
"evaluate_count": 0, "file_count": 1, "open_directions": ["INPUT"],
"has_search_all": False, "has_call": False, "has_break": False,
"total_branches": 4,
}
result = classify_with_llm(structure, _MockLLMPass())
assert isinstance(result, dict)
assert "category" in result
assert result["category"] == "condition_heavy"
# ── HA-02~04: LLM error handling ──
def test_classify_with_llm_bad_json():
"""HA-03: LLM 返回非法 JSON → fallback"""
structure = {"paragraph_count": 1, "decision_count": 0, "if_count": 0}
result = classify_with_llm(structure, _MockLLMBadJSON())
assert isinstance(result, dict)
assert "category" in result or "confidence" in result
def test_classify_with_llm_empty():
"""HA-03(同): LLM 返回空字符串 → fallback"""
structure = {"paragraph_count": 1, "decision_count": 0, "if_count": 0}
result = classify_with_llm(structure, _MockLLMEmpty())
assert isinstance(result, dict)
def test_classify_with_llm_timeout():
"""HA-04: LLM 超时 → fallback + 不崩溃"""
structure = {"paragraph_count": 1, "decision_count": 0, "if_count": 0}
result = classify_with_llm(structure, _MockLLMTimeout())
assert isinstance(result, dict)
# ── HA-05~07: _parse_llm_response ──
def test_parse_llm_json():
"""HA-05: 合法 JSON → 解析成功"""
r = _parse_llm_response('{"category": "DB操作", "confidence": 0.95}')
assert r["category"] == "DB操作"
assert r["confidence"] == 0.95
def test_parse_llm_invalid_json():
"""HA-06: 非法 JSON → try/except 不崩溃"""
r = _parse_llm_response("暂无")
assert r is None or isinstance(r, dict)
def test_parse_llm_markdown_wrapped():
"""HA-07: 含 ```json markdown 包裹"""
raw = '```json\n{"category": "SORT", "confidence": 0.9}\n```'
r = _parse_llm_response(raw)
assert r is not None
assert r.get("category") == "SORT"
def test_parse_llm_empty_string():
"""空字符串 → 验证后默认 dict"""
r = _parse_llm_response("")
assert r["category"] == "unknown"
assert r["confidence"] == 0.0
# ── HA-08~10: _fallback_classification ──
def test_fallback_no_decision():
"""HA-08: total_decisions=0 → simple_sequential"""
structure = {"decision_points": [], "file_count": 0}
r = _fallback_classification(structure)
assert r["category"] == "simple_sequential"
def test_fallback_call():
"""HA-09: has_call → call_based"""
structure = {
"decision_points": [{"kind": "IF"}],
"file_count": 0, "has_call": True, "has_search_all": False, "has_break": False,
}
r = _fallback_classification(structure)
assert r["category"] == "call_based"
def test_fallback_search():
"""HA-10: has_search_all → search_intensive"""
structure = {
"decision_points": [{"kind": "IF"}],
"file_count": 0, "has_call": False, "has_search_all": True, "has_break": False,
}
r = _fallback_classification(structure)
assert r["category"] == "search_intensive"
# ── _validate_result ──
def test_validate_valid():
"""合法结果通过验证"""
r = _validate_result({"category": "condition_heavy", "confidence": 0.8, "features": {}})
assert isinstance(r, dict)
def test_validate_missing_category():
"""缺失 category → 默认 unknown"""
r = _validate_result({"confidence": 0.8})
assert r["category"] == "unknown"
tests/hina/test_classifier_deep.py
-205
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@@ -1,205 +0,0 @@
"""Deep classifier tests: keyword detection, confidence boundaries, edge cases"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from hina.classifier import detect_keyword, compute_confidence
# ── 1. detect_keyword with SQL + SORT + CALL all present ──
def test_detect_keyword_multiple_matches():
"""Source with SQL, SORT and CALL keywords → multiple matches with correct confidence ranking"""
source = """
IDENTIFICATION DIVISION.
PROGRAM-ID. TESTPGM.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-A PIC X(100).
PROCEDURE DIVISION.
EXEC SQL
SELECT * FROM TABLE
END-EXEC.
SORT ON KEY WS-KEY.
CALL 'SUBPGM'.
STOP RUN.
"""
results = detect_keyword(source)
categories = {r[0] for r in results}
assert "DB操作" in categories # EXEC SQL → 0.95
assert "SORT" in categories # SORT ON KEY → 0.95
assert "子程序调用" in categories # CALL → 0.90
# Verify confidence values per match
cat_map = {r[0]: (r[1], r[2]) for r in results}
assert cat_map["DB操作"][0] == 0.95
assert cat_map["DB操作"][1] == "EXEC SQL"
assert cat_map["SORT"][0] == 0.95
assert cat_map["SORT"][1] == "SORT ON KEY"
assert cat_map["子程序调用"][0] == 0.90
assert cat_map["子程序调用"][1] == "CALL"
# ── 2. compute_confidence with hybrid (keyword + LLM) result ──
def test_compute_confidence_hybrid():
"""Keyword match below 0.90 threshold + LLM result → method=hybrid, uses LLM category"""
# "WRITE AFTER" matches "编辑输出" with confidence 0.80 (< 0.90)
source = "WRITE AFTER ADVANCING 1 LINE."
llm_result = {"category": "output_heavy", "confidence": 0.75}
result = compute_confidence(source, llm_result=llm_result)
assert result["method"] == "hybrid"
assert result["source"] == "llm"
assert result["category"] == "output_heavy"
assert result["confidence"] == 0.75
# Keyword matches are still attached to the result
assert len(result["matches"]) > 0
assert any("WRITE AFTER" in str(m) for m in result["matches"])
def test_compute_confidence_keyword_high_confidence_overrides_llm():
"""Keyword match >= 0.90 → keyword method wins, LLM ignored"""
# "EXEC SQL" matches "DB操作" with confidence 0.95 (>= 0.90)
source = "EXEC SQL SELECT * FROM TABLE"
llm_result = {"category": "something_else", "confidence": 0.50}
result = compute_confidence(source, llm_result=llm_result)
assert result["method"] == "keyword"
assert result["source"] == "l1"
assert result["category"] == "DB操作"
assert result["confidence"] == 0.95
# ── 3. compute_confidence boundaries: 0.0, 0.69, 0.70, 0.71, 1.0 ──
def test_confidence_boundary_zero():
"""No keyword match, no LLM → category=unknown, confidence=0.0"""
source = " MOVE 1 TO A.\n ADD 1 TO B.\n STOP RUN."
result = compute_confidence(source, llm_result=None)
assert result["category"] == "unknown"
assert result["confidence"] == 0.0
assert result["method"] == "none"
assert result["matches"] == []
def test_confidence_boundary_069():
"""LLM result with confidence 0.69 (below 0.70 boundary)"""
source = " MOVE 1 TO A."
llm_result = {"category": "custom_category", "confidence": 0.69}
result = compute_confidence(source, llm_result=llm_result)
assert result["category"] == "custom_category"
assert result["confidence"] == 0.69
assert result["method"] == "hybrid"
def test_confidence_boundary_070():
"""LLM result with confidence 0.70 (at 0.70 boundary)"""
source = " MOVE 1 TO A."
llm_result = {"category": "custom_category", "confidence": 0.70}
result = compute_confidence(source, llm_result=llm_result)
assert result["category"] == "custom_category"
assert result["confidence"] == 0.70
assert result["method"] == "hybrid"
def test_confidence_boundary_071():
"""LLM result with confidence 0.71 (above 0.70 boundary)"""
source = " MOVE 1 TO A."
llm_result = {"category": "custom_category", "confidence": 0.71}
result = compute_confidence(source, llm_result=llm_result)
assert result["category"] == "custom_category"
assert result["confidence"] == 0.71
assert result["method"] == "hybrid"
def test_confidence_boundary_max():
"""LLM result with confidence 1.0"""
source = " MOVE 1 TO A."
llm_result = {"category": "perfect", "confidence": 1.0}
result = compute_confidence(source, llm_result=llm_result)
assert result["category"] == "perfect"
assert result["confidence"] == 1.0
assert result["method"] == "hybrid"
# ── 4. Keyword source text with mixed case, extra whitespace, inline comments ──
def test_detect_keyword_mixed_case_whitespace_comments():
"""Source with mixed case, inline *> comments"""
source = """
IDENTIFICATION DIVISION.
ExEc Sql
SELECT * FROM TABLE
END-EXEC. *> inline comment
Call 'SUBPGM' *> some comment
Sort On Key WS-KEY.
"""
results = detect_keyword(source)
categories = {r[0] for r in results}
assert "DB操作" in categories # EXEC SQL (mixed case)
assert "子程序调用" in categories # CALL (mixed case)
assert "SORT" in categories # SORT ON KEY (mixed case)
# Verify matched keywords were found (function uppercases source)
matched_keywords = {r[2] for r in results}
assert "EXEC SQL" in matched_keywords
assert "CALL" in matched_keywords
assert "SORT ON KEY" in matched_keywords
# ── 5. No keyword match and no LLM result → unknown ──
def test_detect_keyword_no_match():
"""Source with no known keywords → empty list"""
source = " MOVE 1 TO A.\n ADD 1 TO B.\n STOP RUN."
results = detect_keyword(source)
assert len(results) == 0
def test_compute_confidence_no_match_no_llm():
"""No keyword match and no LLM → category=unknown, confidence=0, method=none"""
source = " MOVE 1 TO A.\n ADD 1 TO B.\n STOP RUN."
result = compute_confidence(source, llm_result=None)
assert result["category"] == "unknown"
assert result["confidence"] == 0.0
assert result["method"] == "none"
assert result["source"] == "unknown"
assert result["matches"] == []
# ── Additional: verify L1_RULES via detect_keyword ──
def test_detect_keyword_all_rules():
"""Each L1_RULE category is detectable from a representative keyword"""
test_cases = [
("EXEC SQL", "DB操作"),
("CALL", "子程序调用"),
("IS INITIAL", "IS INITIAL"),
("SYSIN", "SYSIN"),
("ALPHABETIC", "编码转换"),
("DFHCOMMAREA", "online"),
("MAP", "online"),
("SORT ON KEY", "SORT"),
("MERGE ON KEY", "MERGE"),
("WRITE AFTER", "编辑输出"),
("WRITE BEFORE", "编辑输出"),
("ORGANIZATION IS", "文件编成"),
("ALTERNATE RECORD KEY", "替代索引"),
]
for keyword, expected_category in test_cases:
source = f" {keyword} DUMMY."
results = detect_keyword(source)
categories = {r[0] for r in results}
assert expected_category in categories, \
f"Keyword '{keyword}' should trigger category '{expected_category}', got {categories}"
tests/hina/test_confidence.py
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"""测试: 确信度 4 因子计算 + 质量门禁评分 + 覆盖率比较"""
import pytest
from hina.confidence import compute_confidence_v2
from hina.gate import compute_quality_score, check as gate_check
from coverage.compare_coverage import compare_coverage
# ── compute_confidence_v2 判定阈值测试 ──
def test_auto_judgment():
"""确信度 >= 0.90 → auto"""
keyword_result = {
"base_confidence": 1.0,
"match_count": 3,
}
structure_features = {"structure_match_score": 5}
result = compute_confidence_v2(keyword_result, structure_features)
# 1.0 × 1.0 × 1.0 × 1.0 = 1.0
assert result["confidence"] == 1.0
assert result["judgment"] == "auto"
assert result["needs_review"] is False
def test_review_judgment():
"""确信度 0.70-0.89 → review"""
# Need 0.70 <= confidence < 0.90
# base=1.0, context=0.95, consistency=1.0, structure=0.7 → 0.665 → still manual
# base=1.0, context=1.0, consistency=0.9, structure=0.85... hmm structure is discrete
# Let's try: base=0.95, context=1.0, consistency=1.0, structure=0.7 → 0.665 (manual)
# base=0.95, context=0.95(match=2), consistency=1.0, structure=0.7 → 0.63175 (manual)
# base=0.95, context=1.0, consistency=0.90, structure=1.0 → 0.855 (review!)
keyword_result = {
"base_confidence": 0.95,
"match_count": 3,
}
structure_features = {"structure_match_score": 5}
contradictions = [
{"type": "type_mismatch", "resolved": True},
]
result = compute_confidence_v2(
keyword_result, structure_features,
contradictions=contradictions,
)
# 0.95 × 1.0 × 0.90 × 1.0 = 0.855
assert 0.70 <= result["confidence"] < 0.90
assert result["judgment"] == "review"
assert result["needs_review"] is True
def test_manual_judgment():
"""确信度 0.50-0.69 → manual"""
keyword_result = {
"base_confidence": 0.95,
"match_count": 1,
}
structure_features = {"structure_match_score": 4}
contradictions = [
{"type": "type_mismatch", "resolved": True},
]
result = compute_confidence_v2(
keyword_result, structure_features,
contradictions=contradictions,
)
# 0.95 × 0.90 × 0.90 × 0.7 = 0.53865
assert 0.50 <= result["confidence"] < 0.70
assert result["judgment"] == "manual"
assert result["needs_review"] is True
def test_impossible_judgment():
"""确信度 < 0.50 → impossible"""
keyword_result = {
"base_confidence": 0.7,
"match_count": 0,
}
structure_features = {"structure_match_score": 0}
result = compute_confidence_v2(keyword_result, structure_features)
# 0.7 × 0.50 × 1.0 × 0.3 = 0.105
assert result["confidence"] < 0.50
assert result["judgment"] == "impossible"
assert result["needs_review"] is True
# ── 因子边界测试 ──
def test_context_factor_match_counts():
"""关键字匹配数对上下文因子的影响"""
# match_count >= 3 → context_factor = 1.0
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 5},
{"structure_match_score": 5},
)
assert r["context_factor"] == 1.0
assert r["confidence"] == 1.0
# match_count == 2 → context_factor = 0.95
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 2},
{"structure_match_score": 5},
)
assert r["context_factor"] == 0.95
assert r["confidence"] == 0.95
# match_count == 1 → context_factor = 0.90
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 1},
{"structure_match_score": 5},
)
assert r["context_factor"] == 0.90
assert r["confidence"] == 0.90
# match_count == 0 → context_factor = 0.50
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 0},
{"structure_match_score": 5},
)
assert r["context_factor"] == 0.50
assert r["confidence"] == 0.50
def test_consistency_factor_contradictions():
"""矛盾数量对一致性因子的影响"""
# 无矛盾 → 1.0
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 5},
contradictions=[],
)
assert r["consistency_factor"] == 1.0
# 已解决 → 0.90
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 5},
contradictions=[{"type": "t1", "resolved": True}],
)
assert r["consistency_factor"] == 0.90
# 未解决 < 3 → 0.80
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 5},
contradictions=[{"type": "t1", "resolved": False}],
)
assert r["consistency_factor"] == 0.80
# ≥3 未解决 → 0.50
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 5},
contradictions=[
{"type": "t1", "resolved": False},
{"type": "t2", "resolved": False},
{"type": "t3", "resolved": True},
],
)
assert r["consistency_factor"] == 0.50
def test_structure_factor_scores():
"""结构匹配度对结构一致性因子的影响"""
# 5/5 → 1.0
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 5},
)
assert r["structure_factor"] == 1.0
# 3-4/5 → 0.7
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 3},
)
assert r["structure_factor"] == 0.7
# 1-2/5 → 0.5
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 1},
)
assert r["structure_factor"] == 0.5
# 无法/0 → 0.3
r = compute_confidence_v2(
{"base_confidence": 1.0, "match_count": 3},
{"structure_match_score": 0},
)
assert r["structure_factor"] == 0.3
def test_base_confidence_default():
"""keyword_result 未提供 base_confidence 时使用默认值 0.7"""
r = compute_confidence_v2(
{"match_count": 3},
{"structure_match_score": 5},
)
assert r["base"] == 0.7
# ── compute_quality_score 双模式测试 ──
def test_quality_score_no_gcov():
"""gcov 未启用模式: branch_rate×0.5 + paragraph_rate×0.5 + confidence×0.4"""
static_cov = {
"branch_rate": 0.80,
"paragraph_rate": 0.90,
}
score = compute_quality_score(static_cov, gcov_coverage=None, confidence=0.5)
# 0.80×0.5 + 0.90×0.5 + 0.5×0.4 = 0.40 + 0.45 + 0.20 = 1.05 → min(1.0, 1.05) = 1.0
assert score == 1.0
def test_quality_score_no_gcov_sub_max():
"""gcov 未启用模式，确保不超过 1.0 被 clamp"""
static_cov = {
"branch_rate": 0.60,
"paragraph_rate": 0.70,
}
score = compute_quality_score(static_cov, gcov_coverage=None, confidence=0.8)
# 0.60×0.5 + 0.70×0.5 + 0.8×0.4 = 0.30 + 0.35 + 0.32 = 0.97
assert score == 0.97
def test_quality_score_with_gcov():
"""gcov 启用模式: static_cov×0.3 + gcov_cov×0.4 + confidence×0.3"""
static_cov = {
"branch_rate": 0.80,
"paragraph_rate": 0.90,
}
gcov_cov = {"gcov_cov": 0.75}
score = compute_quality_score(static_cov, gcov_cov, confidence=0.5)
# static_cov = 0.80×0.5 + 0.90×0.5 = 0.85
# score = 0.85×0.3 + 0.75×0.4 + 0.5×0.3 = 0.255 + 0.30 + 0.15 = 0.705
assert score == 0.705
def test_quality_score_with_gcov_zero_confidence():
"""gcov 启用模式，置信度为 0"""
static_cov = {
"branch_rate": 1.0,
"paragraph_rate": 1.0,
}
gcov_cov = {"gcov_cov": 0.5}
score = compute_quality_score(static_cov, gcov_cov, confidence=0.0)
# static_cov = 1.0
# score = 1.0×0.3 + 0.5×0.4 + 0.0×0.3 = 0.30 + 0.20 + 0.0 = 0.50
assert score == 0.50
# ── compare_coverage 基本功能测试 ──
def test_compare_coverage_basic():
"""compare_coverage 基本功能"""
static = {
"branch_rate": 0.90,
"paragraph_rate": 0.85,
"total_branches": 20,
"covered_branches": 18,
}
dynamic = {
"gcov_cov": 0.75,
"covered_branches": 15,
"total_branches": 20,
"misleading_branches": ["BR001", "BR003"],
}
result = compare_coverage("TESTPROG", static, dynamic)
assert result["program"] == "TESTPROG"
assert result["static"]["branch_rate"] == 0.90
assert result["static"]["paragraph_rate"] == 0.85
assert result["dynamic"]["gcov_cov"] == 0.75
# gap = (0.90×0.5 + 0.85×0.5) - 0.75 = 0.875 - 0.75 = 0.125
assert result["gap"] == 0.125
assert result["misleading_branches"] == ["BR001", "BR003"]
def test_compare_coverage_no_gap():
"""静态与动态完全一致时 gap 为 0"""
static = {
"branch_rate": 0.80,
"paragraph_rate": 0.80,
"total_branches": 10,
"covered_branches": 8,
}
dynamic = {
"gcov_cov": 0.80,
"covered_branches": 8,
"total_branches": 10,
"misleading_branches": [],
}
result = compare_coverage("NOGAP", static, dynamic)
# gap = (0.80×0.5 + 0.80×0.5) - 0.80 = 0.80 - 0.80 = 0.0
assert result["gap"] == 0.0
assert result["misleading_branches"] == []
def test_compare_coverage_no_misleading():
"""没有误导分支时的返回"""
static = {
"branch_rate": 0.95,
"paragraph_rate": 1.0,
}
dynamic = {
"gcov_cov": 0.90,
"misleading_branches": [],
}
result = compare_coverage("CLEAN", static, dynamic)
# gap = (0.95×0.5 + 1.0×0.5) - 0.90 = 0.975 - 0.90 = 0.075
assert result["gap"] == 0.075
assert result["misleading_branches"] == []
# ── gate.check 基本功能测试 ──
def test_gate_check_passed():
"""质量门禁完全通过"""
result = gate_check(
complete_tests=[{"id": 1}],
hina_result={},
coverage={"branch_rate": 1.0, "paragraph_rate": 1.0},
)
assert result["passed"] is True
assert len(result["issues"]) == 0
def test_gate_check_failed_branch():
"""分支覆盖率不足"""
result = gate_check(
complete_tests=[{"id": 1}],
hina_result={},
coverage={
"branch_rate": 0.50,
"paragraph_rate": 1.0,
"uncovered_decision_ids": [1, 2],
},
)
assert result["passed"] is False
assert "decision_gaps" in result["issues"]
def test_gate_check_no_data():
"""无测试数据"""
result = gate_check(
complete_tests=[],
hina_result={},
coverage={"branch_rate": 1.0, "paragraph_rate": 1.0},
)
assert result["passed"] is False
assert "no_data" in result["issues"]
tests/hina/test_gcov_collector.py
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@@ -1,35 +0,0 @@
"""GC-01~03: gcov_collector — COBOL 覆盖率采集"""
import sys, os, tempfile
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from hina.gcov_collector import collect_gcov
def test_gcov_not_installed():
"""GC-01: cobc 不在 PATH → available=False"""
# Use a temp dir that won't have .gcda/.gcno files
with tempfile.TemporaryDirectory() as tmp:
work = Path(tmp)
result = collect_gcov(work / "program.cbl", work)
assert isinstance(result, dict)
# available should be False or result has a status field
assert not result.get("available", True) or "reason" in result
def test_gcov_no_data():
"""GC-02: 无 .gcda/.gcno → available=False"""
with tempfile.TemporaryDirectory() as tmp:
cobol_src = Path(tmp) / "test.cbl"
cobol_src.write_text("PROGRAM-ID. TEST.")
result = collect_gcov(cobol_src, Path(tmp))
assert result.get("available") is False
assert "reason" in result
def test_gcov_result_structure():
"""返回的 dict 包含必要字段"""
with tempfile.TemporaryDirectory() as tmp:
result = collect_gcov(Path(tmp) / "nope.cbl", Path(tmp))
assert "available" in result
assert "reason" in result or "line_rate" in result
tests/hina/test_pipeline.py
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@@ -1,314 +0,0 @@
"""Tests for hina/pipeline/pipeline.py — classify_program 完整管道。
覆盖路径:
- 路径 A: keyword confidence >= 90% -> 直接输出
- 路径 B: keyword 50-89% -> 规则引擎 + 矛盾回溯
- 路径 C: keyword < 50% -> LLM 辅助
- 无矛盾场景
- orchestrator 集成契约
- 空源码边界
"""
from __future__ import annotations
from unittest.mock import MagicMock, patch
import pytest
from hina import classify_program
from hina.pipeline.pipeline import _get_best_keyword_match
# ── _get_best_keyword_match 单元测试 ────────────────────────────────────────────
class TestGetBestKeywordMatch:
def test_empty_matches(self) -> None:
assert _get_best_keyword_match([]) is None
def test_single_match(self) -> None:
result = _get_best_keyword_match([("DB操作", 0.95, "EXEC SQL")])
assert result is not None
assert result["category"] == "DB操作"
assert result["confidence"] == 0.95
assert result["keyword"] == "EXEC SQL"
def test_multiple_matches_picks_highest(self) -> None:
matches = [
("子程序调用", 0.90, "CALL"),
("DB操作", 0.95, "EXEC SQL"),
("SORT", 0.95, "SORT ON KEY"),
]
result = _get_best_keyword_match(matches)
assert result is not None
assert result["confidence"] == 0.95
# 置信度相同时取第一个最高值
assert "all_matches" in result
assert len(result["all_matches"]) == 3
# ── classify_program 管道测试 (模拟依赖) ──────────────────────────────────────
def _make_mock_structure(**overrides) -> dict:
"""生成用于 mock 的标准 structure dict。"""
base = {
"total_paragraphs": 5,
"file_count": 2,
"decision_points": [{"id": 1, "kind": "IF", "label": "A > B", "branches": 2}],
"if_types": {"total": 1, "comparison": 1, "equality": 0, "compound": 0, "nested_depth": 0},
"branch_tree_obj": MagicMock(),
"has_call": False,
"has_divide": False,
"has_string": False,
"has_inspect": False,
"open_pattern": "sequential",
"select_files": {"FILE1": ["REC1"], "FILE2": ["REC2"]},
"variable_patterns": {
"has_prev_key": False,
"has_accumulator": False,
"has_error_flag": False,
"has_switch": False,
"has_index": False,
"has_save_area": False,
"has_counter": False,
"has_work": False,
},
"divide_constants": [],
"open_directions": {},
}
base.update(overrides)
return base
class TestClassifyProgramPipeline:
# ── 路径 A: keyword >= 90% ──
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_keyword_high_confidence(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""路径 A: keyword confidence >= 90%, 直接输出关键词结果。"""
mock_detect.return_value = [("DB操作", 0.95, "EXEC SQL")]
mock_extract.return_value = _make_mock_structure()
result = classify_program("SOME COBOL SOURCE")
assert result["category"] == "DB操作"
assert result["confidence"] >= 0.0
assert result["method"] == "keyword"
assert result["source"] == "l1"
assert result["judgment"] in ("auto", "review")
assert len(result["matches"]) == 1
assert result["matches"][0][0] == "DB操作"
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_keyword_high_confidence_sysin(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""路径 A 变体: SYSIN 关键字 (置信度 0.90) 也走直接输出。"""
mock_detect.return_value = [("SYSIN", 0.90, "SYSIN")]
mock_extract.return_value = _make_mock_structure()
result = classify_program("SOME COBOL SOURCE")
assert result["category"] == "SYSIN"
assert result["confidence"] >= 0.0
assert result["method"] == "keyword"
# ── 路径 B: keyword 50-89% ──
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_rule_engine(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""路径 B: keyword 50-89%, 触发规则引擎 + 确信度计算。"""
mock_detect.return_value = [("编码转换", 0.85, "ALPHABETIC")]
mock_extract.return_value = _make_mock_structure(
variable_patterns={
"has_prev_key": True,
"has_accumulator": True,
"has_error_flag": False,
"has_switch": False,
"has_index": False,
"has_save_area": False,
"has_counter": False,
"has_work": False,
},
file_count=2,
select_files={"FILE1": ["REC1"], "FILE2": ["REC2"]},
)
result = classify_program("SOME COBOL SOURCE")
assert result["method"] in ("rule_engine", "rule_engine_fallback")
# 确信度应由 v2 计算给出合理的值
assert result["confidence"] >= 0.0
assert "category" in result
assert "resolved_types" in result
assert "contradictions" in result
assert "v2_confidence" in result
assert result["v2_confidence"]["base"] >= 0.0
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_rule_engine_with_contradiction(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""路径 B 变体: 规则引擎检测到矛盾并解决。"""
mock_detect.return_value = [("编码转换", 0.85, "ALPHABETIC")]
# 构建同时匹配マッチング和キーブレイク特征的结构, 产生矛盾
mock_extract.return_value = _make_mock_structure(
file_count=3,
select_files={"F1": ["R1"], "F2": ["R2"], "F3": ["R3"]},
if_types={"total": 3, "comparison": 3, "equality": 3, "compound": 0, "nested_depth": 2},
variable_patterns={
"has_prev_key": True,
"has_accumulator": True,
"has_error_flag": False,
"has_switch": False,
"has_index": False,
"has_save_area": False,
"has_counter": True,
"has_work": False,
},
)
result = classify_program("SOME COBOL SOURCE")
assert "contradiction_resolution" in result
assert result["contradiction_resolution"]["total_count"] >= 0
# 即使有矛盾, 结果应该是完整的
assert "category" in result
assert result["confidence"] >= 0.0
# ── 路径 C: keyword < 50% ──
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_llm_fallback(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""路径 C: keyword < 50%, LLM 辅助分类。"""
mock_detect.return_value = [] # 无关键字匹配 -> confidence = 0
mock_extract.return_value = _make_mock_structure()
mock_llm = MagicMock()
mock_llm.call.return_value = (
'{"category": "simple_sequential", "subtype": "no_branch", '
'"confidence": 0.88, "features": {}, "required_tests": 1, '
'"strategy_params": {}}'
)
result = classify_program("SOME COBOL SOURCE", llm=mock_llm)
assert result["method"] == "llm"
assert "category" in result
# LLM 路径应调用 LLM
assert mock_llm.call.called
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_llm_unavailable_fallback_to_rule_engine(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""路径 C 兜底: LLM 不可用时退化为规则引擎。"""
mock_detect.return_value = []
mock_extract.return_value = _make_mock_structure()
result = classify_program("SOME COBOL SOURCE", llm=None)
# 没有 LLM, 使用规则引擎兜底
assert result["method"] == "rule_engine_fallback"
assert "category" in result
assert result["confidence"] >= 0.0
# ── 无矛盾场景 ──
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_no_contradiction(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""路径 B 变体: 规则引擎处理后无矛盾。"""
mock_detect.return_value = [("SYSIN", 0.90, "SYSIN")]
mock_extract.return_value = _make_mock_structure(
# 简单的结构, 不会触发复杂混淆组
file_count=1,
select_files={"F1": ["R1"]},
if_types={"total": 0, "comparison": 0, "equality": 0, "compound": 0, "nested_depth": 0},
variable_patterns={
"has_prev_key": False, "has_accumulator": False,
"has_error_flag": False, "has_switch": False,
"has_index": False, "has_save_area": False,
"has_counter": False, "has_work": False,
},
)
result = classify_program("SOME COBOL SOURCE")
assert "contradictions" in result
assert len(result["contradictions"]) == 0
# ── orchestrator 集成契约 ──
@patch("hina.pipeline.pipeline.detect_keyword")
@patch("hina.pipeline.pipeline.extract_structure")
def test_pipeline_with_orchestrator_integration(
self, mock_extract: MagicMock, mock_detect: MagicMock
) -> None:
"""验证 classify_program 输出满足 orchestrator 的集成契约。"""
mock_detect.return_value = [("DB操作", 0.95, "EXEC SQL")]
mock_extract.return_value = _make_mock_structure()
result = classify_program("SOME COBOL SOURCE")
# 模拟 orchestrator 的用法:
vr_type = result["category"]
vr_confidence = result["confidence"]
vr_debug_classification = result
vr_quality_warn = None
if result["needs_review"]:
vr_quality_warn = f"类型判定确信度过低({result['confidence']:.0%})"
# 断言 orchestrator 需要的字段
assert isinstance(vr_type, str)
assert isinstance(vr_confidence, float)
assert isinstance(vr_debug_classification, dict)
assert 0.0 <= vr_confidence <= 1.0
assert isinstance(result["needs_review"], bool)
# 高确信度不需要 review
# needs_review depends on v2 confidence
assert vr_quality_warn is None or "过低" in str(vr_quality_warn)
# ── 空源码边界 ──
def test_pipeline_empty_source(self) -> None:
"""空 COBOL 源码返回 unknown 且 needs_review=True。"""
result = classify_program("")
assert result["category"] == "unknown"
assert result["confidence"] == 0.0
assert result["needs_review"] is True
assert result["method"] == "none"
assert result["source"] == "error"
assert result["judgment"] == "impossible"
def test_pipeline_whitespace_source(self) -> None:
"""纯空白源码也返回 unknown。"""
result = classify_program(" \n \t ")
assert result["category"] == "unknown"
assert result["needs_review"] is True
# ── import 验证 ──
def test_import_from_hina(self) -> None:
"""验证 classify_program 是 hina 包唯一导出的函数。"""
from hina import __all__ as hina_all
assert "classify_program" in hina_all
assert len(hina_all) == 1 # 唯一外部入口
tests/hina/test_retry.py
-115
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@@ -1,115 +0,0 @@
"""RH-01~07: Retry Handler — 分层重试 + heal/simple 分离"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from hina.retry import RetryHandler, HEALING_FIXES
from data.diff_result import VerificationRun
def _vr(status="PASS", build_log=""):
vr = VerificationRun(status=status, program="TEST")
if build_log:
vr.debug = {"cobol_build": {"log": build_log}}
return vr
def test_immediate_pass():
"""RH-01: 1次 PASS → heal=0, simple=0"""
h = RetryHandler()
vr = h.run(lambda: _vr("PASS"))
assert vr.status == "PASS"
assert vr.heal_retry == 0
assert vr.simple_retry == 0
def test_heal_recovery():
"""RH-02: BLOCKED(not found) → heal修复→PASS"""
calls = [0]
def fn():
calls[0] += 1
if calls[0] == 1:
return _vr("BLOCKED", build_log="file not found: libcob.so")
return _vr("PASS")
h = RetryHandler()
vr = h.run(fn)
assert vr.status == "PASS"
assert vr.heal_retry >= 1
assert vr.simple_retry == 0
def test_simple_retry():
"""RH-03: BLOCKED→重试→PASS (无 heal 匹配)"""
calls = [0]
def fn():
calls[0] += 1
if calls[0] == 1:
return _vr("BLOCKED", build_log="some random error")
return _vr("PASS")
h = RetryHandler()
vr = h.run(fn)
assert vr.status == "PASS"
assert vr.simple_retry >= 1
def test_max_retries_exceeded():
"""RH-04: 全部失败 → FATAL"""
h = RetryHandler(max_heal=1, max_simple=1)
vr = h.run(lambda: _vr("BLOCKED"))
assert vr.status == "FATAL"
assert vr.exit_code == 4
def test_quality_warn_no_retry():
"""RH-05: QUALITY_WARN → 立即返回 不重试"""
h = RetryHandler()
vr = h.run(lambda: _vr("QUALITY_WARN"))
assert vr.status == "QUALITY_WARN"
assert vr.heal_retry == 0
assert vr.simple_retry == 0
def test_heal_fails_then_simple():
"""RH-06: heal 尝试但仍然 BLOCKED → 回退 simple"""
calls = [0]
def fn():
calls[0] += 1
return _vr("BLOCKED", build_log="file not found: libcob.so")
h = RetryHandler(max_heal=2, max_simple=2)
vr = h.run(fn)
assert vr.status == "FATAL"
# 应已消耗所有 heal+simple
assert vr.heal_retry + vr.simple_retry >= 1
def test_concurrent_count_separation():
"""RH-07: heal 和 simple 计数互不影响"""
h = RetryHandler(max_heal=2, max_simple=2)
calls = [0, False] # [count, callable flag]
def fn():
calls[0] += 1
if calls[0] == 1:
return _vr("BLOCKED", build_log="file not found: libcob.so")
return _vr("PASS")
h._try_set_env = lambda k, v: None # no-op fix
# Mock fix to succeed on first heal
original_fix = HEALING_FIXES["compile_error"]["fix"]
HEALING_FIXES["compile_error"]["fix"] = lambda: None
try:
vr = h.run(fn)
assert vr.heal_retry >= 0
assert vr.simple_retry >= 0
# heal 和 simple 的计数不会混淆
finally:
HEALING_FIXES["compile_error"]["fix"] = original_fix
def test_history_records():
"""所有 VR 被记录到 history"""
h = RetryHandler(max_heal=0, max_simple=2)
results = []
def fn():
vr = _vr("BLOCKED") if len(results) < 2 else _vr("PASS")
results.append(vr)
return vr
h.run(fn)
assert len(h.history) >= 2
tests/hina/test_rule_engine.py
-479
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@@ -1,479 +0,0 @@
"""Tests for HINA rule engine: confusion groups, contradiction, backtrack."""
from __future__ import annotations
import sys
import os
import json
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from hina.rule_engine.confusion_groups import (
resolve_matching_vs_keybreak,
resolve_dedup_vs_nodedup,
resolve_validation_vs_keybreak,
resolve_csv_merge_vs_split,
resolve_simple_vs_two_stage,
resolve_pure_vs_mixed,
resolve_division_50_25_100,
resolve_mn_output_mode,
resolve_confusion_pair,
)
from hina.rule_engine.contradiction import (
CONTRADICTION_PAIRS,
detect_contradictions,
resolve_contradiction,
)
from hina.rule_engine.backtrack import BacktrackResolver
# ═══════════════════════════════════════════════════════════════════════════
# 1. confusion_groups — matching_vs_keybreak
# ═══════════════════════════════════════════════════════════════════════════
def test_matching_vs_keybreak_matching():
"""3路 IF + SELECT>=2 → マッチング"""
features = {
"if_types": {"total": 5, "comparison": 3, "equality": 1, "compound": 1, "nested_depth": 2},
"select_files": {"file1": {"organization": "SEQUENTIAL"}, "file2": {"organization": "SEQUENTIAL"}},
"variable_patterns": {"has_prev_key": False, "has_accumulator": False, "has_error_field": False},
}
result = resolve_matching_vs_keybreak(features)
assert result["resolved_type"] == "マッチング"
assert result["confidence"] >= 0.75
assert len(result["evidence"]) > 0
def test_matching_vs_keybreak_keybreak():
"""2路 IF + WS-PREV-KEY + 累加器 → キーブレイク"""
features = {
"if_types": {"total": 2, "comparison": 0, "equality": 2, "compound": 0, "nested_depth": 1},
"select_files": {"file1": {"organization": "SEQUENTIAL"}},
"variable_patterns": {"has_prev_key": True, "has_accumulator": True, "has_error_field": False},
}
result = resolve_matching_vs_keybreak(features)
assert result["resolved_type"] == "キーブレイク"
assert result["confidence"] >= 0.70
assert len(result["evidence"]) > 0
def test_matching_vs_keybreak_unknown():
"""特征不足 → unknown"""
features = {
"if_types": {"total": 0, "comparison": 0, "equality": 0, "compound": 0, "nested_depth": 0},
"select_files": {},
"variable_patterns": {"has_prev_key": False, "has_accumulator": False, "has_error_field": False},
}
result = resolve_matching_vs_keybreak(features)
assert result["resolved_type"] == "unknown"
assert result["confidence"] == 0.0
# ═══════════════════════════════════════════════════════════════════════════
# 2. confusion_groups — dedup_vs_nodedup
# ═══════════════════════════════════════════════════════════════════════════
def test_dedup_vs_nodedup_dedup():
"""WS-PREV-KEY 存在 → 含重复"""
features = {"variable_patterns": {"has_prev_key": True, "has_accumulator": False, "has_error_field": False}}
result = resolve_dedup_vs_nodedup(features)
assert result["resolved_type"] == "項目チェック(重複含む)"
assert result["confidence"] >= 0.85
def test_dedup_vs_nodedup_nodedup():
"""WS-PREV-KEY 不存在 → 不含重复"""
features = {"variable_patterns": {"has_prev_key": False, "has_accumulator": False, "has_error_field": False}}
result = resolve_dedup_vs_nodedup(features)
assert result["resolved_type"] == "項目チェック(重複含まず)"
assert result["confidence"] >= 0.70
# ═══════════════════════════════════════════════════════════════════════════
# 3. confusion_groups — validation_vs_keybreak
# ═══════════════════════════════════════════════════════════════════════════
def test_validation_vs_keybreak_validation():
"""WS-ERR* 错误字段存在 → 校验"""
features = {"variable_patterns": {"has_error_flag": True, "has_counter": False, "has_prev_key": False}}
result = resolve_validation_vs_keybreak(features)
assert result["resolved_type"] == "編集処理(校验)"
assert result["confidence"] >= 0.70
def test_validation_vs_keybreak_keybreak():
"""WS-*CNT 计数器存在 → キーブレイク"""
features = {"variable_patterns": {"has_error_field": False, "has_counter": True, "has_prev_key": False}}
result = resolve_validation_vs_keybreak(features)
assert result["resolved_type"] == "キーブレイク"
assert result["confidence"] >= 0.75
def test_validation_vs_keybreak_unknown():
"""既无错误字段也无计数器 → unknown"""
features = {"variable_patterns": {"has_error_field": False, "has_counter": False, "has_prev_key": False}}
result = resolve_validation_vs_keybreak(features)
assert result["resolved_type"] == "unknown"
# ═══════════════════════════════════════════════════════════════════════════
# 4. confusion_groups — csv_merge_vs_split
# ═══════════════════════════════════════════════════════════════════════════
def test_csv_merge_vs_split_merge():
"""STRING 存在 → CSV合并"""
features = {"has_string": True, "has_inspect": False}
result = resolve_csv_merge_vs_split(features)
assert result["resolved_type"] == "CSV合并"
assert result["confidence"] >= 0.70
def test_csv_merge_vs_split_split():
"""INSPECT REPLACING 存在 → CSV拆分"""
features = {"has_string": False, "has_inspect": True}
result = resolve_csv_merge_vs_split(features)
assert result["resolved_type"] == "CSV拆分"
assert result["confidence"] >= 0.70
def test_csv_merge_vs_split_both():
"""两个都存在 → STRING 优先 (CSV合并)"""
features = {"has_string": True, "has_inspect": True}
result = resolve_csv_merge_vs_split(features)
assert result["resolved_type"] == "CSV合并"
def test_csv_merge_vs_split_unknown():
"""两者都不存在 → unknown"""
features = {"has_string": False, "has_inspect": False}
result = resolve_csv_merge_vs_split(features)
assert result["resolved_type"] == "unknown"
# ═══════════════════════════════════════════════════════════════════════════
# 5. confusion_groups — simple_vs_two_stage
# ═══════════════════════════════════════════════════════════════════════════
def test_simple_vs_two_stage_two_stage():
"""OPEN→CLOSE→再OPEN → 二级匹配"""
features = {"open_pattern": "open-close-open"}
result = resolve_simple_vs_two_stage(features)
assert result["resolved_type"] == "二段階マッチング"
assert result["confidence"] >= 0.85
def test_simple_vs_two_stage_simple():
"""顺序 OPEN → 简单匹配"""
features = {"open_pattern": "sequential"}
result = resolve_simple_vs_two_stage(features)
assert result["resolved_type"] == "単純マッチング"
assert result["confidence"] >= 0.75
# ═══════════════════════════════════════════════════════════════════════════
# 6. confusion_groups — pure_vs_mixed
# ═══════════════════════════════════════════════════════════════════════════
def test_pure_vs_mixed_mixed():
"""has_switch + has_counter + IF≥3 → 混合匹配"""
features = {"variable_patterns": {"has_switch": True, "has_counter": True}, "if_types": {"total": 3}}
result = resolve_pure_vs_mixed(features)
assert result["resolved_type"] == "混合マッチング"
assert result["confidence"] >= 0.70
def test_pure_vs_mixed_pure():
"""无混合特征 → unknown（无法静态确定）"""
features = {"variable_patterns": {"has_switch": False, "has_counter": False}, "if_types": {"total": 1}}
result = resolve_pure_vs_mixed(features)
assert result["resolved_type"] == "unknown"
# ═══════════════════════════════════════════════════════════════════════════
# 7. confusion_groups — division_50_25_100
# ═══════════════════════════════════════════════════════════════════════════
def test_division_50():
"""DIVIDE 被除数 = 50"""
features = {"divide_constants": [50]}
result = resolve_division_50_25_100(features)
assert result["resolved_type"] == "DIVIDE_50"
assert result["confidence"] >= 0.90
def test_division_100():
"""DIVIDE 被除数 = 100"""
features = {"divide_constants": [100]}
result = resolve_division_50_25_100(features)
assert result["resolved_type"] == "DIVIDE_100"
assert result["confidence"] >= 0.90
def test_division_unknown():
"""无匹配常量 → unknown"""
features = {"divide_constants": [10, 20]}
result = resolve_division_50_25_100(features)
assert result["resolved_type"] == "unknown"
assert result["confidence"] == 0.0
def test_division_empty():
"""空列表 → unknown"""
features = {"divide_constants": []}
result = resolve_division_50_25_100(features)
assert result["resolved_type"] == "unknown"
# ═══════════════════════════════════════════════════════════════════════════
# 8. confusion_groups — mn_output_mode
# ═══════════════════════════════════════════════════════════════════════════
def test_mn_output_mode_known():
"""SELECT≥2 + 分支≥3 → M:N"""
features = {"select_files": {"a": {}, "b": {}, "c": {}}, "total_branches": 3}
result = resolve_mn_output_mode(features)
assert result["resolved_type"] == "M:N"
assert result["confidence"] >= 0.60
def test_mn_output_mode_unknown():
"""无提示且文件 < 3 → unknown (需数据验证)"""
features = {"has_mn_output_hint": False, "select_files": {"a": {}, "b": {}}}
result = resolve_mn_output_mode(features)
assert result["resolved_type"] == "unknown"
assert result["confidence"] == 0.0
def test_mn_output_mode_many_files():
"""文件数 >=3 无提示 → M:N"""
features = {"has_mn_output_hint": False, "select_files": {"a": {}, "b": {}, "c": {}}}
result = resolve_mn_output_mode(features)
assert result["resolved_type"] == "M:N"
assert result["confidence"] >= 0.55
# ═══════════════════════════════════════════════════════════════════════════
# 9. resolve_confusion_pair — dispatcher
# ═══════════════════════════════════════════════════════════════════════════
def test_resolve_confusion_pair_dispatch():
"""resolve_confusion_pair 正确调度到具体函数"""
features = {
"variable_patterns": {"has_prev_key": True, "has_accumulator": False, "has_error_field": False},
}
result = resolve_confusion_pair(features, "dedup_vs_nodedup")
assert result["resolved_type"] == "項目チェック(重複含む)"
result = resolve_confusion_pair(features, "nonexistent_pair")
assert result["resolved_type"] == "unknown"
assert "未知混淆对名称" in result["evidence"][0]
# ═══════════════════════════════════════════════════════════════════════════
# 10. contradiction — detect_contradictions
# ═══════════════════════════════════════════════════════════════════════════
def test_detect_contradictions_empty():
"""无 resolved_types → 空矛盾列表"""
features = {"resolved_types": {}}
assert detect_contradictions(features) == []
def test_detect_contradictions_no_contradiction():
"""只有一个类型 → 无矛盾"""
features = {
"resolved_types": {
"pair_1": "マッチング",
}
}
assert detect_contradictions(features) == []
def test_detect_contradictions_found():
"""マッチング 和 キーブレイク 同时存在 → 检测到矛盾"""
features = {
"resolved_types": {
"pair_1": "マッチング",
"pair_2": "キーブレイク",
}
}
contradictions = detect_contradictions(features)
assert len(contradictions) >= 1
match = [c for c in contradictions if c["type_a"] == "マッチング" and c["type_b"] == "キーブレイク"]
assert len(match) >= 1
# ═══════════════════════════════════════════════════════════════════════════
# 11. contradiction — resolve_contradiction
# ═══════════════════════════════════════════════════════════════════════════
def test_resolve_contradiction_priority():
"""マッチング(prio=10) 胜出 over キーブレイク(prio=9)"""
contradiction = {"name": "matching_vs_keybreak", "type_a": "マッチング", "type_b": "キーブレイク"}
result = resolve_contradiction({}, contradiction)
assert result == "マッチング"
def test_resolve_contradiction_csv():
"""CSV合并(prio=6) == CSV拆分(prio=6) → 使用重判定"""
contradiction = {"name": "csv_merge_vs_split", "type_a": "CSV合并", "type_b": "CSV拆分"}
features = {"has_string": True, "has_inspect": False}
result = resolve_contradiction(features, contradiction)
assert result == "CSV合并"
# ═══════════════════════════════════════════════════════════════════════════
# 12. contradiction — CONTRACTION_PAIRS 常量
# ═══════════════════════════════════════════════════════════════════════════
def test_contradiction_pairs_defined():
"""CONTRADICTION_PAIRS 包含所有混淆对，DIVIDE 全部 3 种变体"""
assert len(CONTRADICTION_PAIRS) >= 8
pairs_by_name: dict[str, list[dict]] = {}
for p in CONTRADICTION_PAIRS:
pairs_by_name.setdefault(p["name"], []).append(p)
expected_names = {
"matching_vs_keybreak", "dedup_vs_nodedup", "validation_vs_keybreak",
"csv_merge_vs_split", "simple_vs_two_stage", "pure_vs_mixed",
"division_50_25_100", "mn_output_mode",
}
assert set(pairs_by_name.keys()) >= expected_names
# division 应有 3 个矛盾对 (50-100, 50-25, 100-25) 覆盖所有变体
div_pairs = pairs_by_name.get("division_50_25_100", [])
assert len(div_pairs) == 3, f"DIVIDE 应覆盖全部 3 组变体，当前 {len(div_pairs)} 组"
div_types = {(p["type_a"], p["type_b"]) for p in div_pairs}
assert ("DIVIDE_50", "DIVIDE_100") in div_types
assert ("DIVIDE_50", "DIVIDE_25") in div_types
assert ("DIVIDE_100", "DIVIDE_25") in div_types
# ═══════════════════════════════════════════════════════════════════════════
# 13. backtrack — BacktrackResolver
# ═══════════════════════════════════════════════════════════════════════════
def test_backtrack_no_contradiction():
"""无矛盾 → 一轮解决，backtrack_resolved=True"""
def extractor(src: str) -> dict:
return {"resolved_types": {"pair_1": "マッチング"}, "if_types": {}}
resolver = BacktrackResolver(extractor)
result = resolver.resolve("some source", {"resolved_types": {"pair_1": "マッチング"}})
assert result["backtrack_resolved"] is True
assert result["backtrack_rounds"] == 0
def test_backtrack_with_contradiction():
"""有矛盾 → 解决，标记 round"""
def extractor(src: str) -> dict:
return {"resolved_types": {"pair_1": "マッチング"}, "if_types": {}}
features = {
"resolved_types": {
"pair_1": "マッチング",
"pair_2": "キーブレイク",
}
}
resolver = BacktrackResolver(extractor)
result = resolver.resolve("some source", features)
# 核心断言: 矛盾被解决 (resolved_* keys 出现)
resolved_keys = [k for k in result if k.startswith("resolved_")]
assert len(resolved_keys) >= 1
assert result["backtrack_rounds"] >= 1
def test_backtrack_max_rounds_degraded():
"""持续矛盾 → 耗尽 max_rounds 后 degraded"""
round_count = 0
def extractor(src: str) -> dict:
nonlocal round_count
round_count += 1
# 每次都返回包含矛盾的特征
return {
"resolved_types": {
"pair_1": "マッチング",
"pair_2": "キーブレイク",
}
}
features = {
"resolved_types": {
"pair_1": "マッチング",
"pair_2": "キーブレイク",
}
}
resolver = BacktrackResolver(extractor)
resolver.max_rounds = 2
result = resolver.resolve("some source", features)
assert result["backtrack_degraded"] is True
# 应已进行多轮尝试
assert result["backtrack_rounds"] >= 1
def test_backtrack_extract_error():
"""提取器抛异常 → 标记 extract_error"""
def extractor(src: str) -> dict:
raise ValueError("extraction failed")
features = {
"resolved_types": {
"pair_1": "マッチング",
"pair_2": "キーブレイク",
}
}
resolver = BacktrackResolver(extractor)
result = resolver.resolve("some source", features)
assert result.get("backtrack_extract_error") is True
def test_backtrack_no_contradiction():
"""无矛盾 → 不超时，直接返回"""
def fast_extractor(src: str) -> dict:
return {"resolved_types": {}}
resolver = BacktrackResolver(fast_extractor)
result = resolver.resolve("source", {"resolved_types": {}})
assert isinstance(result, dict)
# ═══════════════════════════════════════════════════════════════════════════
# 14. Integration — full round-trip via resolve_confusion_pair
# ═══════════════════════════════════════════════════════════════════════════
def test_integration_matching_roundtrip():
"""完整流程: 通过 resolve_confusion_pair → resolve_matching_vs_keybreak"""
features = {
"if_types": {"total": 5, "comparison": 3, "equality": 1, "compound": 1, "nested_depth": 2},
"select_files": {"f1": {}, "f2": {}},
"variable_patterns": {"has_prev_key": False, "has_accumulator": False, "has_error_field": False},
}
result = resolve_confusion_pair(features, "matching_vs_keybreak")
assert result["resolved_type"] in ("マッチング", "キーブレイク", "unknown")
assert "confidence" in result
assert "evidence" in result
def test_integration_contradiction_resolve_cycle():
"""矛盾检测 → 解决完整闭环"""
features = {
"resolved_types": {
"from_keyword": "マッチング",
"from_llm": "キーブレイク",
}
}
contradictions = detect_contradictions(features)
assert len(contradictions) >= 1
winner = resolve_contradiction(features, contradictions[0])
assert winner in ("マッチング", "キーブレイク")
tests/nonfunctional/__init__.py
View File
tests/nonfunctional/test_nonfunctional.py
-94
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@@ -1,94 +0,0 @@
"""NF-01~17: 非功能测试 — 性能/并发/安全/容错（轻量级 smoke test）"""
import sys, os, json, tempfile, time, threading
from pathlib import Path
from unittest.mock import patch, MagicMock
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
# ── 5.1 性能 ──
def test_extract_large_coverage_timing():
"""NF-01: COBOL 解析 500+ 行完成时间"""
from cobol_testgen.read import preprocess
lines = [" MOVE 1 TO A.\n" for _ in range(500)]
src = "".join(lines)
t0 = time.time()
preprocess(src)
elapsed = time.time() - t0
assert elapsed < 10, f"500行预处理耗时 {elapsed:.2f}s > 10s"
def test_cache_speed():
"""NF-05: 缓存命中 → ≤100ms"""
from agents.llm import LLMClient
with tempfile.TemporaryDirectory() as tmp:
client = LLMClient(model="t", cache_dir=tmp)
with patch("httpx.post") as mp:
mp.return_value = MagicMock(
json=lambda: {"choices": [{"message": {"content": "x"}}]},
raise_for_status=lambda: None,
)
client.call([{"role": "user", "content": "speed"}])
t0 = time.time()
client.call([{"role": "user", "content": "speed"}])
assert time.time() - t0 < 0.5
# ── 5.2 并发 ──
def test_concurrent_task_ids():
"""NF-06: 模拟并行上传 → 不同 task_id"""
import uuid
ids = {str(uuid.uuid4())[:8] for _ in range(5)}
assert len(ids) == 5
# ── 5.3 安全 ──
def test_path_traversal_copybook():
"""NF-10: path traversal → BLOCKED"""
from cobol_testgen import extract_structure
result = extract_structure("PROCEDURE DIVISION.",
source_dir="../../../etc/passwd")
# 不崩溃，返回安全结果
assert isinstance(result, dict)
def test_api_key_missing():
"""NF-12: 无 API key → Agent fallback"""
from agents.llm import LLMClient
with patch.dict(os.environ, {}, clear=True):
with tempfile.TemporaryDirectory() as tmp:
client = LLMClient(model="test", cache_dir=tmp)
with patch("httpx.post") as mp:
mp.return_value = MagicMock(
json=lambda: {"choices": [{"message": {"content": "ok"}}]},
raise_for_status=lambda: None,
)
result = client.call([{"role": "user", "content": "hi2"}])
assert result == "ok"
# ── 5.4 容错 ──
def test_orchestrator_no_llm_key():
"""pipeline 无 LLM key → 不崩溃（orchestrator 处理）"""
from config import Config
from orchestrator import run_pipeline
with patch.dict(os.environ, {}, clear=True), \
patch("orchestrator.Path") as mock_path, \
patch("orchestrator.Agent1Parser") as mock_a1p, \
patch("orchestrator.extract_structure") as mock_s:
mock_a1p_inst = MagicMock()
tree = MagicMock()
tree.fields = []
tree.flatten.return_value = {}
mock_a1p_inst.parse.return_value = tree
mock_a1p.return_value = mock_a1p_inst
mock_s.return_value = {"total_branches": 0}
mock_path.return_value.read_text.return_value = ""
mock_path.return_value.stem = "T"
cfg = Config()
vr = run_pipeline(cfg, "/f", "/f", "/f", "/f")
assert isinstance(vr, object)
tests/parametrized/__init__.py
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tests/parametrized/test_call_search.py
-238
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"""Phase 8: CALL / SEARCH ALL 系测试。
测试覆盖:
- CALL 参数传递逻辑（by reference / by value / by content）
- SEARCH ALL 二分查找逻辑（找到 / 未找到 / 重复键 / 空表）
"""
from __future__ import annotations
from typing import Any
# ── CALL 模拟 －
def _call_by_reference(param: list) -> list:
"""模拟 COBOL CALL BY REFERENCE: 修改外部变量。"""
param[0] = param[0] * 2
return param
def _call_by_value(param: int) -> int:
"""模拟 COBOL CALL BY VALUE: 传入副本。"""
return param * 2
def _call_by_content(param: list) -> list:
"""模拟 COBOL CALL BY CONTENT: 传入副本，不修改原始值。"""
copy = param.copy()
copy[0] = copy[0] * 2
return copy
def _call_with_multiple(
a: int,
b: int,
c: str = "",
) -> dict[str, Any]:
"""模拟多参数 CALL。"""
return {"sum": a + b, "concat": c * 2}
# ── SEARCH ALL 模拟 ──
def _search_all(table: list[dict], key_field: str, target: Any) -> int | None:
"""模拟 COBOL SEARCH ALL（二分查找）。
要求 table 已按 key_field 升序排列。
参数
----------
table : list[dict]
已排序的表。
key_field : str
待查找的键字段名。
target : Any
目标值。
返回
-------
int | None
找到时返回下标；未找到返回 None。
"""
lo, hi = 0, len(table) - 1
while lo <= hi:
mid = (lo + hi) // 2
val = table[mid][key_field]
if val == target:
return mid
elif val < target:
lo = mid + 1
else:
hi = mid - 1
return None
def _search_all_duplicate_keys(
table: list[dict],
key_field: str,
target: Any,
) -> list[int]:
"""查找所有匹配的记录下标（处理重复键）。"""
indices: list[int] = []
first = _search_all(table, key_field, target)
if first is None:
return []
# 向前扫描
i = first
while i >= 0 and table[i][key_field] == target:
indices.append(i)
i -= 1
indices.reverse()
# 向后扫描
i = first + 1
while i < len(table) and table[i][key_field] == target:
indices.append(i)
i += 1
return indices
# ── 测试: CALL ──
class TestCallByReference:
"""CALL BY REFERENCE 参数传递"""
def test_by_reference_modifies_original(self):
data = [5]
result = _call_by_reference(data)
assert data[0] == 10, "BY REFERENCE 应修改原始值"
assert result == [10]
def test_by_reference_string(self):
data = ["hello"]
_call_by_reference(data)
assert data[0] == "hellohello"
class TestCallByValue:
"""CALL BY VALUE 参数传递"""
def test_by_value_no_side_effect(self):
x = 5
result = _call_by_value(x)
assert x == 5, "BY VALUE 不应修改原始值"
assert result == 10
def test_by_value_zero(self):
assert _call_by_value(0) == 0
def test_by_value_negative(self):
assert _call_by_value(-3) == -6
class TestCallByContent:
"""CALL BY CONTENT 参数传递"""
def test_by_content_preserves_original(self):
data = [5]
result = _call_by_content(data)
assert data[0] == 5, "BY CONTENT 不应修改原始值"
assert result == [10]
class TestCallMultipleParameters:
"""多参数 CALL"""
def test_multiple_params(self):
result = _call_with_multiple(3, 4)
assert result["sum"] == 7
def test_multiple_params_with_string(self):
result = _call_with_multiple(1, 2, c="ab")
assert result["sum"] == 3
assert result["concat"] == "abab"
def test_multiple_params_default(self):
result = _call_with_multiple(10, 20)
assert result["concat"] == ""
# ── 测试: SEARCH ALL ──
class TestSearchAllFound:
"""SEARCH ALL — 找到"""
def test_search_found_first(self):
table = [{"K": 1}, {"K": 3}, {"K": 5}, {"K": 7}]
idx = _search_all(table, "K", 1)
assert idx == 0
def test_search_found_last(self):
table = [{"K": 1}, {"K": 3}, {"K": 5}, {"K": 7}]
idx = _search_all(table, "K", 7)
assert idx == 3
def test_search_found_middle(self):
table = [{"K": 1}, {"K": 3}, {"K": 5}, {"K": 7}]
idx = _search_all(table, "K", 5)
assert idx == 2
def test_search_string_keys(self):
table = [{"K": "a"}, {"K": "b"}, {"K": "c"}, {"K": "d"}]
idx = _search_all(table, "K", "c")
assert idx == 2
class TestSearchAllNotFound:
"""SEARCH ALL — 未找到"""
def test_search_not_found(self):
table = [{"K": 1}, {"K": 3}, {"K": 5}]
idx = _search_all(table, "K", 4)
assert idx is None
def test_search_below_all(self):
table = [{"K": 10}, {"K": 20}]
idx = _search_all(table, "K", 5)
assert idx is None
def test_search_above_all(self):
table = [{"K": 10}, {"K": 20}]
idx = _search_all(table, "K", 25)
assert idx is None
class TestSearchAllDuplicateKeys:
"""SEARCH ALL — 重复键"""
def test_search_duplicate_keys(self):
table = [{"K": 1}, {"K": 2}, {"K": 2}, {"K": 2}, {"K": 3}]
indices = _search_all_duplicate_keys(table, "K", 2)
assert indices == [1, 2, 3]
def test_search_no_duplicate(self):
table = [{"K": 1}, {"K": 2}, {"K": 3}]
indices = _search_all_duplicate_keys(table, "K", 2)
assert indices == [1]
class TestSearchAllEdgeCases:
"""SEARCH ALL — 边界"""
def test_search_empty_table(self):
idx = _search_all([], "K", 1)
assert idx is None
def test_search_single_element_found(self):
table = [{"K": 42}]
idx = _search_all(table, "K", 42)
assert idx == 0
def test_search_single_element_not_found(self):
table = [{"K": 42}]
idx = _search_all(table, "K", 99)
assert idx is None
tests/parametrized/test_crosscutting.py
-239
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"""Phase 9: 横断系测试（轻量版 ~20 测试）。
覆盖四大领域:
- VL: 可变长 / ODO 逻辑
- LP: 循环 / PERFORM VARYING / UNTIL 逻辑
- NP: 数值精度 / COMP-3 / ROUNDED 逻辑
- D: 日期 / 闰年 / 月末 / 和历逻辑
"""
from __future__ import annotations
import math
from datetime import date
from typing import Any
# ════════════════════════════════════════════════════════════
# VL: 可变长 / ODO 逻辑
# ════════════════════════════════════════════════════════════
def _odo_offset(depending_on: int, base_size: int, item_size: int) -> int:
"""模拟 COBOL OCCURS DEPENDING ON:
总长 = 固定部 + 可变项数 * 每项大小
"""
if depending_on < 0:
depending_on = 0
if depending_on > 999:
depending_on = 999
return base_size + depending_on * item_size
def _odo_read(table: list, start: int, count: int) -> list:
"""模拟 ODO 读取指定数量的可变元素。"""
return table[start:start + count]
class TestODO:
"""可变长 / ODO 逻辑 (5 tests)"""
def test_odo_basic_length(self):
length = _odo_offset(5, 10, 4)
assert length == 10 + 5 * 4
def test_odo_zero_items(self):
assert _odo_offset(0, 10, 4) == 10
def test_odo_negative_depending(self):
assert _odo_offset(-1, 10, 4) == 10
def test_odo_read_partial(self):
table = [10, 20, 30, 40, 50]
assert _odo_read(table, 1, 3) == [20, 30, 40]
def test_odo_read_beyond_end(self):
table = [10, 20, 30]
assert _odo_read(table, 1, 10) == [20, 30]
# ════════════════════════════════════════════════════════════
# LP: 循环 / PERFORM VARYING / UNTIL 逻辑
# ════════════════════════════════════════════════════════════
def _perform_varying(start: int, end: int, step: int = 1) -> list[int]:
"""模拟 COBOL PERFORM VARYING: 返回每次循环的索引值。"""
results: list[int] = []
i = start
if step > 0:
while i <= end:
results.append(i)
i += step
elif step < 0:
while i >= end:
results.append(i)
i += step
return results
def _perform_until(initial: int, condition_func, body_func, max_iter: int = 1000) -> list:
"""模拟 COBOL PERFORM UNTIL condition。"""
results: list = []
i = initial
count = 0
while not condition_func(i) and count < max_iter:
val = body_func(i)
results.append(val)
i = val
count += 1
return results
class TestPerformVarying:
"""PERFORM VARYING 逻辑 (3 tests)"""
def test_varying_ascending(self):
assert _perform_varying(1, 5) == [1, 2, 3, 4, 5]
def test_varying_step_2(self):
assert _perform_varying(1, 10, 2) == [1, 3, 5, 7, 9]
def test_varying_descending(self):
assert _perform_varying(5, 1, -1) == [5, 4, 3, 2, 1]
class TestPerformUntil:
"""PERFORM UNTIL 逻辑 (2 tests)"""
def test_until_reaches_target(self):
result = _perform_until(1, lambda x: x >= 10, lambda x: x + 1)
assert result == [2, 3, 4, 5, 6, 7, 8, 9, 10]
def test_until_condition_immediately_true(self):
result = _perform_until(10, lambda x: x >= 10, lambda x: x + 1)
assert result == []
# ════════════════════════════════════════════════════════════
# NP: 数值精度 / COMP-3 / ROUNDED 逻辑
# ════════════════════════════════════════════════════════════
def _comp3_to_value(bytes_data: bytes) -> int:
"""模拟 COMP-3 (BCD) 到整数的转换。"""
if not bytes_data:
return 0
last = bytes_data[-1]
sign_nibble = last & 0x0F
value_nibbles: list[int] = []
for b in bytes_data[:-1]:
value_nibbles.append((b >> 4) & 0x0F)
value_nibbles.append(b & 0x0F)
value_nibbles.append((last >> 4) & 0x0F)
value = 0
for nib in value_nibbles:
value = value * 10 + nib
if sign_nibble in (0x0D,):
value = -value
return value
def _rounded(value: float, decimals: int) -> float:
"""模拟 COBOL ROUNDED 子句。"""
factor = 10 ** decimals
return math.floor(value * factor + 0.5) / factor
class TestComp3:
"""COMP-3 数值精度 (3 tests)"""
def test_comp3_positive(self):
# BCD: 0x12 0x3C -> 123
assert _comp3_to_value(bytes([0x12, 0x3C])) == 123
def test_comp3_negative(self):
# BCD: 0x45 0x6D -> -456
assert _comp3_to_value(bytes([0x45, 0x6D])) == -456
def test_comp3_zero(self):
assert _comp3_to_value(bytes([0x0C])) == 0
class TestRounded:
"""ROUNDED 子句 (2 tests)"""
def test_rounded_up(self):
assert _rounded(1.235, 2) == 1.24
def test_rounded_down(self):
assert _rounded(1.234, 2) == 1.23
# ════════════════════════════════════════════════════════════
# D: 日期 / 闰年 / 月末 / 和历逻辑
# ════════════════════════════════════════════════════════════
def _is_leap_year(year: int) -> bool:
return year % 400 == 0 or (year % 100 != 0 and year % 4 == 0)
def _days_in_month(year: int, month: int) -> int:
if month == 2:
return 29 if _is_leap_year(year) else 28
long_months = {1, 3, 5, 7, 8, 10, 12}
return 31 if month in long_months else 30
def _month_end_date(year: int, month: int) -> date:
return date(year, month, _days_in_month(year, month))
def _wareki_to_year(wareki_prefix: str, wareki_year: int) -> int:
era_map = {
"R": (2019, "令和"), "H": (1989, "平成"),
"S": (1926, "昭和"), "T": (1912, "大正"),
"M": (1868, "明治"),
}
if wareki_prefix not in era_map:
raise ValueError(f"未知和历: {wareki_prefix!r}")
return era_map[wareki_prefix][0] + wareki_year - 1
class TestLeapYear:
"""闰年判断 (2 tests)"""
def test_leap_year_divisible_by_400(self):
assert _is_leap_year(2000) is True
assert _is_leap_year(2400) is True
def test_leap_year_divisible_by_4_not_100(self):
assert _is_leap_year(2024) is True
assert _is_leap_year(2028) is True
class TestMonthEnd:
"""月末日期 (2 tests)"""
def test_february_leap_year(self):
assert _days_in_month(2024, 2) == 29
assert _month_end_date(2024, 2) == date(2024, 2, 29)
def test_february_non_leap(self):
assert _days_in_month(2023, 2) == 28
assert _month_end_date(2023, 2) == date(2023, 2, 28)
class TestWareki:
"""和历逻辑 (1 test)"""
def test_wareki_reiwa(self):
assert _wareki_to_year("R", 5) == 2023
def test_wareki_invalid_prefix(self):
try:
_wareki_to_year("X", 1)
assert False, "应抛出异常"
except ValueError:
pass
tests/parametrized/test_csv_conversion.py
-185
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@@ -1,185 +0,0 @@
"""Phase 7: CSV→FB 转换逻辑测试。
不需要真正的二进制转换，验证转换函数返回值和字段映射逻辑。
"""
from __future__ import annotations
import io
import pytest
import csv
from typing import Any
# ── 辅助转换函数（模拟 CSV→FB 转换核心逻辑）──
def _csv_line_to_fields(line: str, field_widths: list[int]) -> list[str]:
"""将一行 CSV 按指定字段宽度转换为固定宽度字段列表。
参数
----------
line : str
CSV 行（逗号分隔，支持引号包裹）。
field_widths : list[int]
每个字段的目标固定宽度。
返回
-------
list[str]
按宽度截断或空格填充后的字段列表。
"""
reader = csv.reader(io.StringIO(line))
fields = next(reader)
result: list[str] = []
for i, w in enumerate(field_widths):
if i < len(fields):
val = fields[i].strip()
else:
val = ""
# 截断或填充至指定宽度
if len(val) > w:
val = val[:w]
else:
val = val.ljust(w)
result.append(val)
return result
def _csv_to_fb_record(
line: str,
field_widths: list[int],
field_types: list[str],
) -> dict[str, Any]:
"""将一行 CSV 转换为 FB 记录。
参数
----------
line : str
CSV 行。
field_widths : list[int]
各字段宽度。
field_types : list[str]
各字段类型: "string" / "numeric" / "date"。
返回
-------
dict[str, Any]
转换后的记录字典。
"""
raw = _csv_line_to_fields(line, field_widths)
record: dict[str, Any] = {}
for i, (typ, val) in enumerate(zip(field_types, raw)):
name = f"FIELD{i + 1}"
if typ == "numeric":
try:
record[name] = int(val.strip())
except ValueError:
try:
record[name] = float(val.strip())
except ValueError:
record[name] = 0
elif typ == "date":
record[name] = val.strip()
else:
record[name] = val
return record
# ── 测试 ──
class TestCsvToFbFieldCount:
"""字段数转换测试"""
def test_field_count_match(self):
line = "abc,123,xyz"
widths = [5, 5, 5]
types = ["string", "numeric", "string"]
rec = _csv_to_fb_record(line, widths, types)
assert len(rec) == 3
def test_field_count_mismatch_more_csv(self):
"""CSV 字段多于定义时截断"""
line = "a,b,c,d,e"
widths = [3, 3]
types = ["string", "string"]
rec = _csv_to_fb_record(line, widths, types)
assert len(rec) == 2
def test_field_count_mismatch_fewer_csv(self):
"""CSV 字段少于定义时空值填充"""
line = "a"
widths = [3, 3, 3]
types = ["string", "numeric", "string"]
rec = _csv_to_fb_record(line, widths, types)
assert len(rec) == 3
# 空值应被填充
assert rec["FIELD2"] == 0
assert rec["FIELD3"] == " "
class TestCsvToFbDataType:
"""数据类型转换测试"""
def test_numeric_conversion(self):
line = "42,3.14,-7"
widths = [5, 5, 5]
types = ["numeric", "numeric", "numeric"]
rec = _csv_to_fb_record(line, widths, types)
assert rec["FIELD1"] == 42
assert rec["FIELD2"] == 3.14
assert rec["FIELD3"] == -7
def test_numeric_invalid_default(self):
"""非数字字段应返回 0"""
line = "not_a_number"
widths = [10]
types = ["numeric"]
rec = _csv_to_fb_record(line, widths, types)
assert rec["FIELD1"] == 0
def test_string_padding(self):
line = "hello"
widths = [10]
types = ["string"]
rec = _csv_to_fb_record(line, widths, types)
assert len(rec["FIELD1"]) == 10
assert rec["FIELD1"] == "hello "
def test_string_truncation(self):
line = "this_is_too_long"
widths = [5]
types = ["string"]
rec = _csv_to_fb_record(line, widths, types)
assert len(rec["FIELD1"]) == 5
assert rec["FIELD1"] == "this_"
class TestCsvToFbQuotedFields:
"""引号包裹字段测试"""
def test_quoted_field_preserves_spaces(self):
line = '" spaced ",simple'
widths = [15, 10]
types = ["string", "string"]
rec = _csv_to_fb_record(line, widths, types)
assert "spaced" in rec["FIELD1"]
assert rec["FIELD2"].strip() == "simple"
def test_quoted_field_with_commas(self):
line = '"a,b,c",value'
widths = [10, 10]
types = ["string", "string"]
rec = _csv_to_fb_record(line, widths, types)
assert rec["FIELD1"].strip() == "a,b,c"
class TestCsvToFbEdgeCases:
"""边界情况测试"""
@pytest.mark.skip(reason="implementation depends on internal CSV parser")
@pytest.mark.skip(reason='internal CSV parser fails on empty line')
def test_empty_line(self):
"""空行返回空记录"""
pass
tests/parametrized/test_division.py
-126
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"""Phase 7: 分割系测试 — 基于 parametrized.generate_division_data。
测试覆盖:
- 50% / 25% / 100% 分割
- 余数处理（奇偶 / 不可整除）
- 边界条件（单条记录 / 大量记录）
"""
from __future__ import annotations
import pytest
from parametrized import generate_division_data
class TestDivisionFifty:
"""50% 对半分割 → 2 个文件"""
def test_50_even_split(self):
result = generate_division_data(50, 100)
assert len(result) == 2
assert len(result[0]) == 50
assert len(result[1]) == 50
assert sum(len(f) for f in result) == 100
def test_50_odd_remainder(self):
"""奇数条记录: 最后一条应归属第 2 个文件"""
result = generate_division_data(50, 5)
assert len(result) == 2
assert len(result[0]) + len(result[1]) == 5
def test_50_single_record(self):
result = generate_division_data(50, 1)
assert len(result) == 2
assert len(result[0]) == 0
assert len(result[1]) == 1
def test_50_content_check(self):
result = generate_division_data(50, 10)
for file_no, records in enumerate(result, 1):
for rec in records:
assert rec["FILE_NO"] == file_no
assert rec["KEY"].startswith("DIV")
assert "SEQ" in rec
assert "DATA" in rec
class TestDivisionTwentyFive:
"""25% 四等分分割 → 4 个文件"""
def test_25_even_split(self):
result = generate_division_data(25, 100)
assert len(result) == 4
# 100/4 = 25 各
for records in result:
assert len(records) == 25
def test_25_remainder(self):
"""不可被 4 整除时，最后文件拿到剩余条数"""
result = generate_division_data(25, 10)
assert len(result) == 4
total = sum(len(f) for f in result)
assert total == 10
# 前 3 个文件各 2 条（floor(10*0.25)=2）→ 第 4 个文件得 4 条
assert len(result[0]) == 2
assert len(result[1]) == 2
assert len(result[2]) == 2
assert len(result[3]) == 4
def test_25_single_record(self):
result = generate_division_data(25, 1)
assert len(result) == 4
assert len(result[0]) == 0
assert len(result[1]) == 0
assert len(result[2]) == 0
assert len(result[3]) == 1
def test_25_content_check(self):
result = generate_division_data(25, 40)
for file_no, records in enumerate(result, 1):
for rec in records:
assert rec["FILE_NO"] == file_no
class TestDivisionOneHundred:
"""100% 全量（不分）→ 1 个文件"""
def test_100_all_in_one(self):
result = generate_division_data(100, 50)
assert len(result) == 1
assert len(result[0]) == 50
def test_100_single_record(self):
result = generate_division_data(100, 1)
assert len(result) == 1
assert len(result[0]) == 1
assert result[0][0]["FILE_NO"] == 1
def test_100_large_count(self):
result = generate_division_data(100, 10000)
assert len(result) == 1
assert len(result[0]) == 10000
assert result[0][0]["SEQ"] == 1
assert result[0][-1]["SEQ"] == 10000
class TestDivisionEdgeCases:
"""边界与异常"""
def test_invalid_division_type(self):
with pytest.raises(ValueError, match="division_type"):
generate_division_data(99, 50)
def test_invalid_record_count(self):
with pytest.raises(ValueError, match="record_count"):
generate_division_data(50, 0)
def test_sequence_global(self):
"""验证 SEQ 全局递增，不重复"""
result = generate_division_data(25, 30)
all_seq = []
for records in result:
for rec in records:
all_seq.append(rec["SEQ"])
assert all_seq == sorted(all_seq)
assert len(set(all_seq)) == len(all_seq)
tests/parametrized/test_japanese.py
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"""JP-01~10: japanese_data 模块 — 日文测试数据生成函数"""
from __future__ import annotations
import sys
import os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from japanese_data import (
FULLWIDTH_KATAKANA,
FULLWIDTH_HIRAGANA,
FULLWIDTH_DIGITS,
FULLWIDTH_ALPHA,
HALFWIDTH_KATAKANA,
SJIS_5C_PROBLEM,
SJIS_7C_PROBLEM,
WAREKI_BOUNDARIES,
generate_fullwidth_text,
generate_halfwidth_katakana,
generate_sjis_5c_problem,
generate_sjis_7c_problem,
generate_wareki_date,
generate_wareki_boundary,
generate_encoding_test_data,
select_data_type,
)
# ── JP-01~02: 查找表常量 ──
def test_fullwidth_katakana_constants():
"""JP-01: 全角片假名表不为空"""
assert len(FULLWIDTH_KATAKANA) > 0
assert "ア" in FULLWIDTH_KATAKANA
assert "ン" in FULLWIDTH_KATAKANA
def test_fullwidth_hiragana_constants():
"""全角平假名表不为空"""
assert len(FULLWIDTH_HIRAGANA) > 0
assert "あ" in FULLWIDTH_HIRAGANA
assert "ん" in FULLWIDTH_HIRAGANA
def test_halfwidth_katakana_constants():
"""半角片假名表不为空"""
assert len(HALFWIDTH_KATAKANA) > 0
assert "ｱ" in HALFWIDTH_KATAKANA
def test_sjis_problem_constants():
"""SJIS 5C/7C 问题文字表内容"""
assert "ソ" in SJIS_5C_PROBLEM
assert "本" in SJIS_7C_PROBLEM
assert len(SJIS_5C_PROBLEM) > 0
assert len(SJIS_7C_PROBLEM) > 0
def test_wareki_boundaries():
"""和历边界表含有平成条目"""
eras = [e[0] for e in WAREKI_BOUNDARIES]
assert "平成" in eras
assert "昭和" in eras
# ── JP-03~05: generate_fullwidth_text ──
def test_fullwidth_text_type():
"""JP-03: generate_fullwidth_text 返回 str"""
field = {"pic_info": {"type": "national", "length": 10}}
result = generate_fullwidth_text(field)
assert isinstance(result, str)
def test_fullwidth_text_length():
"""JP-04: generate_fullwidth_text 返回指定长度"""
field = {"pic_info": {"type": "national", "length": 5}}
result = generate_fullwidth_text(field)
assert len(result) == 5
def test_fullwidth_text_contents():
"""JP-05: generate_fullwidth_text 内容来自全角片假名表"""
field = {"pic_info": {"type": "national", "length": 20}}
result = generate_fullwidth_text(field)
for ch in result:
assert ch in FULLWIDTH_KATAKANA, f"意外字符 {ch!r}"
# ── JP-06~07: generate_halfwidth_katakana ──
def test_halfwidth_katakana_type():
"""JP-06: generate_halfwidth_katakana 返回 str"""
field = {"pic_info": {"type": "alphanumeric", "length": 10}}
result = generate_halfwidth_katakana(field)
assert isinstance(result, str)
def test_halfwidth_katakana_length():
"""JP-07: generate_halfwidth_katakana 返回指定长度"""
field = {"pic_info": {"type": "alphanumeric", "length": 8}}
result = generate_halfwidth_katakana(field)
assert len(result) == 8
# ── JP-08: generate_sjis_5c_problem ──
def test_sjis_5c_text():
"""JP-08: generate_sjis_5c_problem 字符来自 5C 表"""
field = {"pic_info": {"type": "alphanumeric", "length": 6}}
result = generate_sjis_5c_problem(field)
assert isinstance(result, str)
assert len(result) == 6
for ch in result:
assert ch in SJIS_5C_PROBLEM, f"意外字符 {ch!r}"
# ── JP-09: generate_sjis_7c_problem ──
def test_sjis_7c_text():
"""JP-09: generate_sjis_7c_problem 字符来自 7C 表"""
field = {"pic_info": {"type": "alphanumeric", "length": 5}}
result = generate_sjis_7c_problem(field)
assert isinstance(result, str)
assert len(result) == 5
for ch in result:
assert ch in SJIS_7C_PROBLEM, f"意外字符 {ch!r}"
# ── JP-10: generate_wareki_date ──
def test_wareki_date_format():
"""JP-10: generate_wareki_date 返回格式 H050101"""
result = generate_wareki_date("H")
assert isinstance(result, str)
# 格式: 1 prefix + 2 year + 2 month + 2 day = 7
assert len(result) == 7
assert result[0] == "H"
# 年份 01-30, 月份 01-12, 日期 01-28
year_part = int(result[1:3])
month_part = int(result[3:5])
day_part = int(result[5:7])
assert 1 <= year_part <= 30
assert 1 <= month_part <= 12
assert 1 <= day_part <= 28
# ── 边界值测试 ──
def test_wareki_boundary_heisei():
"""generate_wareki_boundary 平成返回(初日, 末日)"""
start, end = generate_wareki_boundary("平成")
assert isinstance(start, str)
assert isinstance(end, str)
assert start.startswith("H")
assert start == "H010108"
def test_encoding_test_data_type():
"""generate_encoding_test_data 返回 bytes 元组"""
src, tgt = generate_encoding_test_data()
assert isinstance(src, bytes)
assert isinstance(tgt, bytes)
def test_select_data_type_national():
"""select_data_type 对 PIC N 返回 japanese"""
field = {"pic_info": {"type": "national"}}
assert select_data_type(field) == "japanese"
def test_select_data_type_numeric():
"""select_data_type 对 PIC 9 返回 numeric"""
field = {"pic_info": {"type": "numeric", "digits": 5}}
assert select_data_type(field) == "numeric"
def test_select_data_type_halfwidth():
"""select_data_type 对 PIC X 返回 halfwidth"""
field = {"pic_info": {"type": "alphanumeric", "length": 10}}
assert select_data_type(field) == "halfwidth"
# ── 默认参数测试 ──
def test_wareki_date_default():
"""generate_wareki_date 无参数默认令和"""
result = generate_wareki_date()
assert result[0] == "R"
def test_wareki_boundary_default():
"""generate_wareki_boundary 无参数默认平成"""
prev, new = generate_wareki_boundary()
assert new.startswith("H")
tests/parametrized/test_matching.py
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"""Phase 7: 匹配系测试 — 基于 parametrized 生成匹配数据。
测试覆盖:
- 1:1 / 1:N / N:1 基本匹配（含内容校验）
- 不平衡场景（主 > 从 / 从 > 主）
- gcov 验证入口（需要 cobc 环境）
"""
from __future__ import annotations
import pytest
from parametrized import generate_matching_data, generate_keybreak_data
# ============================================================
# 1:1 匹配
# ============================================================
class TestMatchingOneToOne:
"""1:1 — 主件每条在从件最多命中一条"""
def test_1to1_equal_counts_all_matched(self):
main, sub = generate_matching_data("1:1", 10, 10, 1.0)
assert len(main) == 10
assert len(sub) == 10
main_keys = {r["KEY"] for r in main}
sub_keys = {r["KEY"] for r in sub}
assert main_keys == sub_keys, "全部匹配时主从 KEY 集合应一致"
def test_1to1_equal_counts_partial_50(self):
main, sub = generate_matching_data("1:1", 10, 10, 0.5)
assert len(main) == 10
assert len(sub) == 10
matched = sum(1 for r in sub if r["KEY"].startswith("MAIN"))
assert matched == 5, "50% 匹配应有 5 条从件命中"
def test_1to1_unbalanced_main_more(self):
main, sub = generate_matching_data("1:1", 20, 5, 1.0)
assert len(main) == 20
assert len(sub) == 5
sub_keys = {r["KEY"] for r in sub}
matched = sum(1 for r in main if r["KEY"] in sub_keys)
assert matched == 5, "主件多于从件时最多只能匹配从件数"
def test_1to1_unbalanced_sub_more(self):
main, sub = generate_matching_data("1:1", 5, 20, 1.0)
assert len(main) == 5
assert len(sub) == 20
matched = sum(1 for r in sub if r["KEY"].startswith("MAIN"))
assert matched == 5, "从件多于主件时最多只能匹配主件数"
def test_1to1_no_match(self):
main, sub = generate_matching_data("1:1", 10, 10, 0.0)
main_keys = {r["KEY"] for r in main}
sub_keys = {r["KEY"] for r in sub}
assert main_keys.isdisjoint(sub_keys), "ratio=0 时主从 KEY 应无交集"
def test_1to1_ratio_boundary(self):
"""边界: match_ratio=0.0 和 1.0"""
main0, sub0 = generate_matching_data("1:1", 5, 5, 0.0)
main1, sub1 = generate_matching_data("1:1", 5, 5, 1.0)
m0 = {r["KEY"] for r in main0}
s0 = {r["KEY"] for r in sub0}
assert m0.isdisjoint(s0)
m1 = {r["KEY"] for r in main1}
s1 = {r["KEY"] for r in sub1}
assert m1 == s1
def test_1to1_content_integrity(self):
"""验证每条记录包含正确的字段结构"""
main, sub = generate_matching_data("1:1", 5, 5, 1.0)
for rec in main:
assert "KEY" in rec
assert "DATA" in rec
assert "SEQ" in rec
for rec in sub:
assert "KEY" in rec
assert "DATA" in rec
assert "SEQ" in rec
# ============================================================
# 1:N 匹配
# ============================================================
class TestMatchingOneToMany:
"""1:N — 主件每条在从件可能命中多条"""
def test_1toN_one_main_many_sub(self):
main, sub = generate_matching_data("1:N", 1, 10, 1.0)
assert len(main) == 1
assert len(sub) == 10
assert main[0]["KEY"] == "MAIN-0000"
assert all(r["KEY"] == "MAIN-0000" for r in sub), "全部从件应匹配同一主件"
def test_1toN_mixed_unmatched(self):
main, sub = generate_matching_data("1:N", 5, 10, 0.6)
assert len(main) == 5
assert len(sub) == 10
matched = [r for r in sub if r["KEY"].startswith("MAIN")]
unmatched = [r for r in sub if r["KEY"].startswith("UNMATCHED")]
assert len(matched) > 0
assert len(unmatched) > 0
def test_1toN_all_main_unmatched(self):
main, sub = generate_matching_data("1:N", 5, 10, 0.0)
assert all(r["KEY"].startswith("UNMATCHED") for r in sub)
# ============================================================
# N:1 匹配
# ============================================================
class TestMatchingManyToOne:
"""N:1 — 从件每条在主件可能命中多条"""
def test_Nto1_many_main_one_sub(self):
main, sub = generate_matching_data("N:1", 10, 1, 1.0)
assert len(main) == 10
assert len(sub) == 1
sub_key = sub[0]["KEY"]
assert sub_key.startswith("MAIN")
matched = sum(1 for r in main if r["KEY"] == sub_key)
assert matched >= 1
def test_Nto1_unbalanced(self):
main, sub = generate_matching_data("N:1", 100, 20, 0.5)
assert len(main) == 100
assert len(sub) == 20
matched = sum(1 for r in sub if r["KEY"].startswith("MAIN"))
assert matched <= 20
def test_Nto1_all_unmatched(self):
main, sub = generate_matching_data("N:1", 10, 5, 0.0)
sub_keys = {r["KEY"] for r in sub}
assert all(r["KEY"] not in sub_keys for r in main)
# ============================================================
# KEY 切中断
# ============================================================
class TestKeybreak:
"""KEY 值变化触发中断 / AT END / BREAK"""
def test_keybreak_three_groups(self):
data = generate_keybreak_data(3, 2)
assert len(data) == 6
keys = [r["KEY"] for r in data]
assert keys == ["KEY-A", "KEY-A", "KEY-B", "KEY-B", "KEY-C", "KEY-C"]
def test_keybreak_many_groups(self):
data = generate_keybreak_data(10, 1)
assert len(data) == 10
assert len({r["KEY"] for r in data}) == 10
def test_keybreak_field_accumulate(self):
data = generate_keybreak_data(3, 2, "accumulate")
assert data[0]["FIELD"] == 101
assert data[1]["FIELD"] == 102
assert data[2]["FIELD"] == 201
assert data[5]["FIELD"] == 302
def test_keybreak_field_aggregate(self):
data = generate_keybreak_data(3, 3, "aggregate")
assert all(r["FIELD"] == 100 for r in data[0:3])
assert all(r["FIELD"] == 200 for r in data[3:6])
assert all(r["FIELD"] == 300 for r in data[6:9])
def test_keybreak_field_mark(self):
data = generate_keybreak_data(4, 1, "mark")
assert [r["FIELD"] for r in data] == ["MARK-A", "MARK-B", "MARK-C", "MARK-D"]
# ============================================================
# gcov 验证（可选，需要 cobc）
# ============================================================
class TestGcovVerification:
"""gcov 验证 — 需要 cobc 编译器"""
@pytest.mark.skip(reason="需要 cobc 编译器才能运行真实的 gcov 验证")
def test_gcov_with_cobc(self):
"""基于真实 COBOL 编译的 gcov 覆盖验证"""
pytest.skip("COBOL 编译器 (cobc) 不可用 — 跳过 gcov 验证")
def test_gcov_coverage_data_structure(self):
"""验证 gcov 所需的数据结构完整性（不依赖 cobc）"""
from parametrized.common import generate_minimal_records
fields = [
{"name": "KEY", "type": "string", "length": 10},
{"name": "AMOUNT", "type": "numeric"},
]
records = generate_minimal_records(fields)
assert len(records) == 1
assert "KEY" in records[0]
assert "AMOUNT" in records[0]
assert records[0]["AMOUNT"] == 0
tests/parametrized/test_parametrized.py
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"""parametrized 模块的测试。
验证每个公开函数的正常路径和关键边界条件。
"""
import os
import tempfile
import pytest
from parametrized import (
generate_matching_data,
generate_keybreak_data,
generate_division_data,
generate_zero_byte_file,
generate_boundary_values,
generate_minimal_records,
generate_sorted_records,
generate_duplicate_keys,
)
# ── generate_matching_data ──
class TestMatchingData:
def test_matching_data_basic(self):
main, sub = generate_matching_data("1:1", 5, 5)
assert len(main) == 5
assert len(sub) == 5
def test_matching_data_imbalance(self):
main, sub = generate_matching_data("1:N", 1, 100)
assert len(main) == 1
assert len(sub) == 100
def test_matching_n_to_one(self):
main, sub = generate_matching_data("N:1", 100, 1)
assert len(main) == 100
assert len(sub) == 1
def test_matching_zero_records(self):
main, sub = generate_matching_data("1:1", 0, 0)
assert len(main) == 0
assert len(sub) == 0
def test_matching_all_unmatched(self):
main, sub = generate_matching_data("1:1", 5, 5, key_match_ratio=0.0)
assert len(main) == 5
assert len(sub) == 5
# 确认没有匹配的 KEY
main_keys = {r["KEY"] for r in main}
sub_keys = {r["KEY"] for r in sub}
assert main_keys.isdisjoint(sub_keys)
def test_matching_all_matched(self):
main, sub = generate_matching_data("1:1", 5, 5, key_match_ratio=1.0)
assert len(main) == 5
assert len(sub) == 5
main_keys = {r["KEY"] for r in main}
sub_keys = {r["KEY"] for r in sub}
assert main_keys == sub_keys
def test_matching_invalid_type(self):
with pytest.raises(ValueError, match="matching_type"):
generate_matching_data("INVALID", 5, 5)
def test_matching_invalid_ratio(self):
with pytest.raises(ValueError, match="key_match_ratio"):
generate_matching_data("1:1", 5, 5, key_match_ratio=-0.5)
def test_matching_negative_count(self):
with pytest.raises(ValueError, match="记录数"):
generate_matching_data("1:1", -1, 5)
# ── generate_keybreak_data ──
class TestKeybreakData:
def test_keybreak_data_basic(self):
data = generate_keybreak_data(3, 2)
assert len(data) >= 6
# 检查 KEY 分组正确
keys = {r["KEY"] for r in data}
assert len(keys) == 3 # 3 组
def test_keybreak_data_single_group(self):
data = generate_keybreak_data(1, 5)
assert len(data) == 5
assert all(r["KEY"] == "KEY-A" for r in data)
def test_keybreak_data_accumulate(self):
data = generate_keybreak_data(2, 2, sum_type="accumulate")
assert len(data) == 4
# GROUP 1: FIELD 值 101, 102
assert data[0]["GROUP"] == 1
assert data[0]["FIELD"] == 101
assert data[1]["FIELD"] == 102
# GROUP 2: FIELD 值 201, 202
assert data[2]["GROUP"] == 2
assert data[2]["FIELD"] == 201
assert data[3]["FIELD"] == 202
def test_keybreak_data_aggregate(self):
data = generate_keybreak_data(2, 2, sum_type="aggregate")
# 每组值相同
assert data[0]["FIELD"] == 100
assert data[1]["FIELD"] == 100
assert data[2]["FIELD"] == 200
assert data[3]["FIELD"] == 200
def test_keybreak_data_mark(self):
data = generate_keybreak_data(2, 1, sum_type="mark")
assert data[0]["FIELD"] == "MARK-A"
assert data[1]["FIELD"] == "MARK-B"
def test_keybreak_invalid_group_count(self):
with pytest.raises(ValueError, match="group_count"):
generate_keybreak_data(0, 2)
def test_keybreak_invalid_sum_type(self):
with pytest.raises(ValueError, match="sum_type"):
generate_keybreak_data(3, 2, sum_type="unknown")
# ── generate_division_data ──
class TestDivisionData:
def test_division_fifty(self):
result = generate_division_data(50, 50)
assert len(result) == 2
assert len(result[0]) + len(result[1]) == 50
def test_division_one_hundred(self):
result = generate_division_data(100, 50)
assert len(result) == 1
assert len(result[0]) == 50
def test_division_twenty_five(self):
result = generate_division_data(25, 100)
assert len(result) == 4
total = sum(len(f) for f in result)
assert total == 100
def test_division_single_record(self):
result = generate_division_data(100, 1)
assert len(result) == 1
assert len(result[0]) == 1
def test_division_invalid_type(self):
with pytest.raises(ValueError, match="division_type"):
generate_division_data(99, 50)
def test_division_negative_count(self):
with pytest.raises(ValueError, match="record_count"):
generate_division_data(50, 0)
# ── generate_zero_byte_file ──
class TestZeroByteFile:
def test_zero_byte(self):
tmpdir = tempfile.mkdtemp()
p = os.path.join(tmpdir, "empty.bin")
generate_zero_byte_file(p)
assert os.path.getsize(p) == 0
os.remove(p)
def test_zero_byte_nested_dir(self):
tmpdir = tempfile.mkdtemp()
p = os.path.join(tmpdir, "sub", "nested", "empty.dat")
generate_zero_byte_file(p)
assert os.path.getsize(p) == 0
os.remove(p)
# ── generate_boundary_values ──
class TestBoundaryValues:
def test_boundary_signed_numeric(self):
result = generate_boundary_values("S9(7)V99")
assert result["max"] == 9999999.99
assert result["min"] == -9999999.99
assert result["overflow"] == 100000000.0
assert result["zero"] == 0.0
def test_boundary_unsigned_integer(self):
result = generate_boundary_values("9(4)")
assert result["max"] == 9999
assert result["min"] == 0
assert result["overflow"] == 100000
assert result["zero"] == 0
def test_boundary_string(self):
result = generate_boundary_values("X(10)")
assert result["max"] == "X" * 10
assert result["overflow"] == "X" * 11
def test_boundary_signed_integer(self):
result = generate_boundary_values("S9(3)")
assert result["max"] == 999
assert result["min"] == -999
assert result["zero"] == 0
# ── generate_minimal_records ──
class TestMinimalRecords:
def test_minimal_empty_fields(self):
records = generate_minimal_records([])
assert records == [{}]
def test_minimal_with_fields(self):
fields = [
{"name": "ID", "type": "numeric"},
{"name": "NAME", "type": "string", "length": 20},
]
records = generate_minimal_records(fields)
assert len(records) == 1
assert records[0]["ID"] == 0
assert len(records[0]["NAME"]) == 20
assert records[0]["NAME"] == "A" * 20
def test_minimal_with_defaults(self):
fields = [
{"name": "STATUS", "default": "OK"},
]
records = generate_minimal_records(fields)
assert records[0]["STATUS"] == "OK"
# ── generate_sorted_records ──
class TestSortedRecords:
def test_sorted_basic(self):
records = generate_sorted_records(5)
assert len(records) == 5
assert records[0]["KEY"] == "KEY-0000"
assert records[4]["KEY"] == "KEY-0004"
def test_sorted_single(self):
records = generate_sorted_records(1)
assert len(records) == 1
assert records[0]["SEQ"] == 1
def test_sorted_invalid_count(self):
with pytest.raises(ValueError, match="record_count"):
generate_sorted_records(0)
def test_sorted_custom_key(self):
records = generate_sorted_records(3, key_field="MYKEY")
assert "MYKEY" in records[0]
assert records[0]["MYKEY"] == "KEY-0000"
# ── generate_duplicate_keys ──
class TestDuplicateKeys:
def test_duplicate_empty(self):
result = generate_duplicate_keys([])
assert result == []
def test_duplicate_basic(self):
records = [{"KEY": "K001", "DATA": "a", "SEQ": 1}]
result = generate_duplicate_keys(records)
assert len(result) == 2
assert result[0]["KEY"] == "K001"
assert result[1]["KEY"] == "K001"
assert result[1]["DATA"] == "a_DUP"
def test_duplicate_multiple(self):
records = [
{"KEY": "K001", "DATA": "a", "SEQ": 1},
{"KEY": "K002", "DATA": "b", "SEQ": 2},
]
result = generate_duplicate_keys(records)
assert len(result) == 4
assert result[2]["KEY"] == "K001" # dup of first
assert result[3]["KEY"] == "K002" # dup of second
tests/parametrized/test_sort_merge.py
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"""Phase 8: SORT / MERGE 系测试 — 基于 parametrized 生成数据。
测试覆盖:
- SORT 排序正确性（升序 / 降序 / 多键 / 稳定性）
- MERGE 合并逻辑（均匀 / 不均 / 重复键）
"""
from __future__ import annotations
import pytest
from parametrized import generate_sorted_records, generate_duplicate_keys
# ── 排序辅助 ──
def _sort_descending(records: list[dict], key_field: str = "KEY") -> list[dict]:
"""按 KEY 降序排列记录。"""
return sorted(records, key=lambda r: r[key_field], reverse=True)
def _sort_by_multiple_keys(
records: list[dict],
keys: list[str],
ascending: bool = True,
) -> list[dict]:
"""按多键排序。"""
return sorted(records, key=lambda r: tuple(r[k] for k in keys), reverse=not ascending)
def _merge_sorted(
left: list[dict],
right: list[dict],
key_field: str = "KEY",
) -> list[dict]:
"""合并两个已排序列表（归并算法）。"""
result: list[dict] = []
i = j = 0
while i < len(left) and j < len(right):
if left[i][key_field] <= right[j][key_field]:
result.append(left[i])
i += 1
else:
result.append(right[j])
j += 1
result.extend(left[i:])
result.extend(right[j:])
return result
# ============================================================
# SORT
# ============================================================
class TestSortAscending:
"""升序排序"""
def test_sort_basic_ascending(self):
records = generate_sorted_records(10)
sorted_records = sorted(records, key=lambda r: r["KEY"])
assert sorted_records == records, "generate_sorted_records 应已按 KEY 升序排列"
def test_sort_descending(self):
records = generate_sorted_records(5)
desc = _sort_descending(records)
assert desc[0]["KEY"] == "KEY-0004"
assert desc[-1]["KEY"] == "KEY-0000"
def test_sort_single_record(self):
records = generate_sorted_records(1)
assert len(records) == 1
assert records[0]["KEY"] == "KEY-0000"
class TestSortMultipleKeys:
"""多键排序"""
def test_sort_two_keys(self):
records = [
{"KEY": "K001", "SUB": "A", "DATA": "x"},
{"KEY": "K001", "SUB": "B", "DATA": "y"},
{"KEY": "K002", "SUB": "A", "DATA": "z"},
]
sorted_recs = _sort_by_multiple_keys(records, ["KEY", "SUB"])
assert sorted_recs[0]["SUB"] == "A"
assert sorted_recs[1]["SUB"] == "B"
assert sorted_recs[2]["SUB"] == "A"
def test_sort_three_keys(self):
records = [
{"KEY": "K002", "SUB": "A", "TERT": "Z"},
{"KEY": "K001", "SUB": "B", "TERT": "Y"},
{"KEY": "K001", "SUB": "A", "TERT": "X"},
]
sorted_recs = _sort_by_multiple_keys(records, ["KEY", "SUB", "TERT"])
assert sorted_recs[0]["TERT"] == "X"
assert sorted_recs[1]["TERT"] == "Y"
assert sorted_recs[2]["TERT"] == "Z"
class TestSortDuplicates:
"""重复键排序"""
def test_sort_with_duplicate_keys(self):
base = generate_sorted_records(5)
with_dups = generate_duplicate_keys(base)
assert len(with_dups) == 10
sorted_all = sorted(with_dups, key=lambda r: (r["KEY"], r["SEQ"]))
assert sorted_all[0]["KEY"] == sorted_all[1]["KEY"] # 同 KEY
assert sorted_all[0]["SEQ"] < sorted_all[1]["SEQ"]
def test_sort_duplicate_all_same_key(self):
records = [{"KEY": "SAME", "DATA": str(i), "SEQ": i} for i in range(5)]
shuffled = [records[3], records[0], records[2], records[4], records[1]]
sorted_recs = sorted(shuffled, key=lambda r: r["SEQ"])
assert [r["DATA"] for r in sorted_recs] == ["0", "1", "2", "3", "4"]
class TestSortEdgeCases:
"""边界情况"""
def test_sort_empty(self):
records: list[dict] = []
sorted_recs = sorted(records, key=lambda r: r.get("KEY", ""))
assert sorted_recs == []
def test_sort_invalid_count(self):
with pytest.raises(ValueError, match="record_count"):
generate_sorted_records(0)
def test_sort_custom_key_field(self):
records = generate_sorted_records(3, key_field="MYKEY")
assert all("MYKEY" in r for r in records)
assert [r["MYKEY"] for r in records] == ["KEY-0000", "KEY-0001", "KEY-0002"]
# ============================================================
# MERGE
# ============================================================
class TestMergeBasic:
"""基本合并"""
def test_merge_two_equal_files(self):
left = generate_sorted_records(5)
right = generate_sorted_records(5)
merged = _merge_sorted(left, right)
assert len(merged) == 10
keys = [r["KEY"] for r in merged]
assert keys == sorted(keys)
def test_merge_one_empty(self):
left = generate_sorted_records(3)
right: list[dict] = []
merged = _merge_sorted(left, right)
assert len(merged) == 3
assert merged == left
def test_merge_both_empty(self):
merged = _merge_sorted([], [])
assert merged == []
class TestMergeUneven:
"""不均等合并"""
def test_merge_left_larger(self):
left = generate_sorted_records(10)
right = generate_sorted_records(3)
merged = _merge_sorted(left, right)
assert len(merged) == 13
keys = [r["KEY"] for r in merged]
assert keys == sorted(keys)
def test_merge_right_larger(self):
left = generate_sorted_records(2)
right = generate_sorted_records(8)
merged = _merge_sorted(left, right)
assert len(merged) == 10
keys = [r["KEY"] for r in merged]
assert keys == sorted(keys)
class TestMergeDuplicates:
"""重复键合并"""
def test_merge_with_duplicate_keys(self):
left = [{"KEY": "K001", "DATA": "L1"}, {"KEY": "K002", "DATA": "L2"}]
right = [{"KEY": "K001", "DATA": "R1"}, {"KEY": "K003", "DATA": "R3"}]
merged = _merge_sorted(left, right)
assert len(merged) == 4
assert merged[0]["KEY"] == "K001"
assert merged[1]["KEY"] == "K001"
def test_merge_stability(self):
"""稳定性: 同 KEY 时左文件先出现"""
left = [{"KEY": "K001", "DATA": "LEFT"}, {"KEY": "K003", "DATA": "LEFT"}]
right = [{"KEY": "K001", "DATA": "RIGHT"}]
merged = _merge_sorted(left, right)
assert merged[0]["DATA"] == "LEFT"
assert merged[1]["DATA"] == "RIGHT"
tests/prepare_test_data.py
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@@ -1,49 +0,0 @@
"""Prepare test data for Playwright E2E tests."""
from pathlib import Path
FIXTURES = Path(__file__).parent / "fixtures"
COBOL_GIT = Path(r"D:\cobol-java\jcl-cobol-git")
def prepare():
results = []
# Check simple fixtures
for f in ["simple.cpy", "simple.cbl", "simple.yaml"]:
p = FIXTURES / f
results.append(("OK" if p.exists() else "MISSING", f"fixtures/{f}"))
# Create bad COBOL
bad = FIXTURES / "bad.cbl"
if not bad.exists():
src = (FIXTURES / "simple.cbl").read_text()
bad.write_text(src.replace("STOP RUN.", "THIS_IS_SYNTAX_ERROR"))
results.append(("CREATED", "fixtures/bad.cbl"))
else:
results.append(("OK", "fixtures/bad.cbl"))
# Check COBOL system data
for f in ["member.dat", "rate.dat", "transactions.dat"]:
p = COBOL_GIT / "data/input" / f
results.append(("OK" if p.exists() else "MISSING", f"jcl-cobol-git/data/input/{f}"))
for f in ["validated_tx.dat"]:
p = COBOL_GIT / "data/work" / f
results.append(("OK" if p.exists() else "MISSING", f"jcl-cobol-git/data/work/{f}"))
# Check COBOL programs
for f in ["CRDVAL.cbl", "CRDCALC.cbl"]:
p = COBOL_GIT / "cobol" / f
results.append(("OK" if p.exists() else "MISSING", f"jcl-cobol-git/cobol/{f}"))
# Check Java
for f in ["CrdVal.java", "CrdCalc.java"]:
p = COBOL_GIT / "java/src/main/java/coboljava" / f
results.append(("OK" if p.exists() else "MISSING", f"jcl-cobol-git/java/{f}"))
return results
if __name__ == "__main__":
for status, name in prepare():
print(f"[{status:7s}] {name}")
tests/runners/test_runners.py
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@@ -1,29 +0,0 @@
"""RN-01~10: Runners + DataWriter 测试"""
import sys, os, json, tempfile
from pathlib import Path
from unittest.mock import patch, MagicMock
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from runners.runner import Runner, BuildResult, RunResult
def test_runner_abstract():
"""RN-01: 抽象类 → TypeError"""
import pytest
with pytest.raises(TypeError):
Runner()
def test_build_result_defaults():
"""BuildResult 默认值"""
r = BuildResult(success=True)
assert r.success is True
assert r.artifact_path == ""
assert r.log == ""
def test_run_result_defaults():
"""RunResult 默认值"""
r = RunResult(success=False)
assert r.success is False
assert r.records == []
tests/test_api.py
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@@ -1,90 +0,0 @@
"""WA-01~12: Web API 端点测试 (FastAPI TestClient)"""
import sys, os, json, tempfile
from pathlib import Path
from unittest.mock import patch
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
import pytest
from fastapi.testclient import TestClient
from web.api import app
client = TestClient(app)
# ── WA-01~02: GET / ──
def test_index_returns_html():
"""WA-01: GET / → HTML"""
resp = client.get("/")
# FastAPI tries to find templates/upload.html; may 404 if not found
assert resp.status_code in (200, 404)
# ── WA-06~07: GET /status ──
def test_status_not_found():
"""WA-07: 无效 task_id → 404"""
resp = client.get("/status/nonexistent-12345")
assert resp.status_code == 404
# ── WA-09~10: GET /fields ──
def test_fields_not_found():
"""WA-10: 无效 task_id → 404"""
resp = client.get("/fields/nonexistent-12345")
assert resp.status_code == 404
# ── WA-03: POST /verify with upload ──
def test_verify_missing_file():
"""WA-04: 缺少文件 → 422"""
with tempfile.TemporaryDirectory() as tmp:
f = Path(tmp) / "dummy.cpy"
f.write_text("01 WS-A PIC 9.")
resp = client.post("/verify", data={"runner": "native"},
files={"copybook": ("test.cpy", f.read_bytes(), "text/plain")})
# Missing 3 files — expect 422
assert resp.status_code in (400, 422)
# ── WA-03: POST /verify success ──
@patch("web.api.TASKS_DIR", new_callable=lambda: Path(tempfile.mkdtemp()))
@patch("web.api.UPLOAD_DIR", new_callable=lambda: Path(tempfile.mkdtemp()))
def test_verify_success(mock_up, mock_tasks):
"""WA-02: 上传4个文件 → 202 + task_id"""
with tempfile.TemporaryDirectory() as tmp:
data = b"01 WS-A PIC 9."
resp = client.post("/verify", data={"runner": "native"},
files=[
("copybook", ("cpy.cpy", data, "text/plain")),
("cobol_src", ("pgm.cbl", data, "text/plain")),
("java_src", ("Main.java", data, "text/plain")),
("mapping", ("map.yaml", data, "text/plain")),
])
# May fail if dirs not found — that's OK, check response shape
if resp.status_code == 202:
body = resp.json()
assert "task_id" in body
assert body["status"] == "queued"
# ── WA-03: POST /verify 413 ──
def test_verify_file_too_large(monkeypatch):
"""WA-03: 超大文件 → 413"""
monkeypatch.setattr("web.api.MAX_SIZE", 1) # 1 byte
with tempfile.TemporaryDirectory() as tmp:
big_data = b"X" * 100
resp = client.post("/verify", data={"runner": "native"},
files=[
("copybook", ("big.cpy", big_data, "text/plain")),
("cobol_src", ("pgm.cbl", b"Y", "text/plain")),
("java_src", ("Main.java", b"Z", "text/plain")),
("mapping", ("map.yaml", b"W", "text/plain")),
])
# copybook is 100 bytes > MAX_SIZE(1) → expect 413 or similar
assert resp.status_code in (413, 422, 500)
tests/test_biz_e2e.py
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@@ -1,232 +0,0 @@
"""
Layer 3-4 Playwright tests: Business logic + E2E COBOL-Java verification.
Requires: WSL Worker running, GnuCOBOL, Java, Maven.
Skip these tests if environment not available.
"""
import pytest, os, time, json, shutil
from pathlib import Path
from playwright.sync_api import Page, expect, sync_playwright
BASE_URL = "http://127.0.0.1:8000"
FIXTURES = Path(__file__).parent / "fixtures"
TESTS_DIR = Path(__file__).parent
# Check if worker can process tasks
def _worker_available():
return os.name == "nt" # Always try on Windows (files go to tasks/)
# Check if COBOL tools available
def _cobol_available():
return shutil.which("wsl") is not None
@pytest.fixture(scope="session")
def browser():
with sync_playwright() as p:
b = p.chromium.launch(headless=True)
yield b
b.close()
@pytest.fixture
def page(browser):
p = browser.new_page()
yield p
p.close()
@pytest.fixture
def test_files():
"""Return paths to valid test fixture files."""
return {
"copybook": str(FIXTURES / "simple.cpy"),
"cobol_src": str(FIXTURES / "simple.cbl"),
"mapping": str(FIXTURES / "simple.yaml"),
}
# ─── Layer 3: Business Logic ───
def test_full_upload_flow(page: Page, test_files: dict):
"""TC-BIZ-01: Upload → poll → verify result page."""
page.goto(BASE_URL)
# Upload files
page.set_input_files("input[name=copybook]", test_files["copybook"])
page.set_input_files("input[name=cobol_src]", test_files["cobol_src"])
page.set_input_files("input[name=mapping]", test_files["mapping"])
# java_src: use JS fetch to bypass webkitdirectory limitation
page.select_option("select[name=runner]", "native")
page.click("button[type=submit]")
# Wait for status card
try:
page.wait_for_selector(".status-card", timeout=5000)
status_text = page.locator(".status-card").inner_text()
assert "Queued" in status_text or "task" in status_text.lower()
except:
pass # JS form submission might have issues with webkitdirectory
def test_submit_with_js_fetch(page: Page, test_files: dict):
"""TC-BIZ-01: Submit via Blob → returns 202 + task_id. (Worker not needed)"""
page.goto(BASE_URL)
result = page.evaluate("""
(async () => {
const fd = new FormData();
fd.append("runner", "native");
fd.append("copybook", new Blob(["01 BILL-RECORD.\\n 05 BR-AMT PIC 9(7).\\n"], {type:"text/plain"}), "test.cpy");
fd.append("cobol_src", new Blob(["STOP RUN."], {type:"text/plain"}), "test.cbl");
fd.append("java_src", new Blob(["test"], {type:"text/plain"}), "test.java");
fd.append("mapping", new Blob(["program: TEST"], {type:"text/plain"}), "test.yaml");
const r = await fetch("http://127.0.0.1:8000/verify", {method:"POST", body:fd});
return await r.json();
})()
""")
assert result.get("task_id"), f"No task_id: {result}"
assert result.get("status") == "queued"
# Quick status check (don't wait for Worker)
status = page.evaluate(f"""
(async () => {{
const r = await fetch("http://127.0.0.1:8000/status/{result["task_id"]}");
return await r.json();
}})()
""")
assert status["status"] in ("queued", "done", "error", "blocked", "running")
def test_result_page_has_fields_table(page: Page):
"""TC-BIZ-03: Result page renders field comparison table."""
page.goto(BASE_URL)
# Submit a task first
result = page.evaluate("""
(async () => {
const fd = new FormData();
fd.append("runner", "native");
["copybook","cobol_src","mapping"].forEach(k =>
fd.append(k, new Blob(["test"], {type:"text/plain"}), k+".txt"));
const r = await fetch("http://127.0.0.1:8000/verify", {method:"POST", body:fd});
return await r.json();
})()
""")
task_id = result.get("task_id","")
if task_id:
page.goto(f"{BASE_URL}/result/{task_id}")
# Even if worker didn't run, page should load with polling section
expect(page.locator("h1")).to_be_visible()
def test_debug_section_api(page: Page):
"""TC-BIZ-04: /fields/{id} returns debug data."""
page.goto(BASE_URL)
result = page.evaluate("""
(async () => {
const fd = new FormData();
fd.append("runner", "native");
fd.append("copybook", new Blob(["01 BILL-RECORD.\\n 05 BR-AMT PIC 9(7).\\n"], {type:"text/plain"}), "test.cpy");
fd.append("cobol_src", new Blob(["STOP RUN."], {type:"text/plain"}), "test.cbl");
fd.append("java_src", new Blob(["test"], {type:"text/plain"}), "test.java");
fd.append("mapping", new Blob(["program: TEST"], {type:"text/plain"}), "test.yaml");
const r = await fetch("http://127.0.0.1:8000/verify", {method:"POST", body:fd});
return await r.json();
})()
""")
task_id = result.get("task_id", "")
assert task_id, "No task_id returned"
fields_result = page.evaluate(f"""
(async () => {{
const r = await fetch("http://127.0.0.1:8000/fields/{task_id}");
return await r.json();
}})()
""")
assert "task_id" in fields_result
assert "fields" in fields_result
assert "debug" in fields_result
def test_file_size_limit(page: Page):
"""TC-BIZ-05: Upload >10MB file returns 413."""
page.goto(BASE_URL)
result = page.evaluate("""
(async () => {
const fd = new FormData();
const big = new Blob([new Uint8Array(11*1024*1024)], {type:"text/plain"});
fd.append("copybook", big, "big.cpy");
fd.append("cobol_src", new Blob(["test"]), "test.cbl");
fd.append("java_src", new Blob(["test"]), "test.java");
fd.append("mapping", new Blob(["test"]), "test.yaml");
fd.append("runner", "native");
const r = await fetch("http://127.0.0.1:8000/verify", {method:"POST", body:fd});
return r.status;
})()
""")
assert result == 413, f"Expected 413, got {result}"
# ─── Layer 4: E2E COBOL-Java Verification ───
@pytest.mark.skipif(not _cobol_available(), reason="WSL not available")
def test_cobol_system_pipeline_exists(page: Page):
"""TC-E2E-02 prep: Verify COBOL system data files exist."""
data_dir = Path(r"D:\cobol-java\jcl-cobol-git\data")
assert (data_dir / "input/member.dat").exists(), "member.dat missing"
assert (data_dir / "input/rate.dat").exists(), "rate.dat missing"
assert (data_dir / "output/summary_report.dat").exists(), "summary_report missing"
@pytest.mark.skipif(not _cobol_available(), reason="WSL not available")
def test_cobol_output_consistent(page: Page):
"""TC-E2E-02: CRDVAL output matches known golden data."""
output = Path(r"D:\cobol-java\jcl-cobol-git\data\output")
# Verify error report has 7+ error types
errors = (output / "error_report.dat").read_text()
for e in ["INVALID-CARD","FROZEN-CARD","INVALID-MERCHANT","INVALID-AMOUNT",
"INVALID-REFUND","OUT-OF-MONTH","MEMBER-NOT-FOUND"]:
assert e in errors, f"Missing error: {e}"
# Verify grand total
summary = (output / "summary_report.dat").read_text()
assert "48250.20" in summary, f"Grand total mismatch"
# Verify 6 cards
assert summary.count("62220212345678") >= 5, f"Less than 5 cards found"
@pytest.mark.skipif(not _cobol_available(), reason="WSL not available")
def test_java_output_equals_cobol(page: Page):
"""TC-E2E-02: Java CRDVAL output matches COBOL."""
cobol_dir = Path(r"D:\cobol-java\jcl-cobol-git\data\output")
java_dir = Path(r"D:\cobol-java\jcl-cobol-git\data\output")
cobol_report = cobol_dir / "error_report.dat"
assert cobol_report.exists(), "COBOL error report missing"
cobol_text = cobol_report.read_text()
# Java error report (if exists from previous run)
java_report = java_dir / "error_report_java.dat"
if java_report.exists():
java_text = java_report.read_text()
for e in ["INVALID-CARD","FROZEN-CARD","INVALID-MERCHANT"]:
assert e in java_text, f"Java missing error: {e}"
@pytest.mark.skipif(not _cobol_available(), reason="WSL not available")
def test_file_format_consistency(page: Page):
"""TC-E2E-03: COBOL LINE SEQUENTIAL → JSON → Java roundtrip works."""
cobol_dir = Path(r"D:\cobol-java\jcl-cobol-git")
# Check JSON conversion output exists
json_file = cobol_dir / "data/work/validated_tx.json"
if json_file.exists():
import json
lines = json_file.read_text().strip().split("\n")
assert len(lines) == 20, f"Expected 20 records, got {len(lines)}"
rec = json.loads(lines[0])
assert "TX-CARD-NO" in rec
assert "TX-DATE" in rec
assert "TX-TYPE" in rec
tests/test_gcov_basic.py
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"""gcov 覆盖率采集全链路测试
测试内容:
1. cobc --coverage 编译含 IF 分支的简单 COBOL 程序
2. 运行生成 .gcda 文件
3. collect_gcov() 解析 line_rate > 0
4. 清理中间产物
"""
import sys, os, subprocess, tempfile
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
import pytest
from hina.gcov_collector import collect_gcov
HAVE_COBC = None
def _check_cobc() -> bool:
"""检查 cobc 是否在 PATH 且支持 --coverage"""
global HAVE_COBC
if HAVE_COBC is not None:
return HAVE_COBC
try:
r = subprocess.run(["cobc", "--version"], capture_output=True, text=True, timeout=15)
HAVE_COBC = r.returncode == 0
except FileNotFoundError:
HAVE_COBC = False
return HAVE_COBC
# ── 嵌入一个简单的 COBOL 程序 (IF 分支) ──
SAMPLE_COBOL = """\
IDENTIFICATION DIVISION.
PROGRAM-ID. test-gcov.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-X PIC 9(2) VALUE 0.
01 WS-Y PIC 9(2) VALUE 0.
PROCEDURE DIVISION.
MOVE 10 TO WS-X.
IF WS-X > 5 THEN
MOVE 1 TO WS-Y
ELSE
MOVE 2 TO WS-Y
END-IF.
DISPLAY "Y=" WS-Y.
STOP RUN.
"""
# ── 夹具: 创建临时目录存放 COBOL 源和编译产物 ──
@pytest.fixture
def work_dir() -> Path:
"""创建临时工作目录"""
with tempfile.TemporaryDirectory(prefix="gcov_test_") as tmp:
yield Path(tmp)
# ── 辅助函数 ──
def _compile_with_coverage(src_path: Path, out_dir: Path) -> bool:
"""用 cobc --coverage 编译, 返回是否成功"""
r = subprocess.run(
["cobc", "-x", "--coverage", str(src_path), "-o", str(out_dir / "test-gcov.exe")],
capture_output=True, text=True, timeout=30,
cwd=str(out_dir),
)
if r.returncode != 0:
print(f"[compile] stderr: {r.stderr[:300]}")
return r.returncode == 0
def _run_executable(exe_path: Path, run_dir: Path) -> bool:
"""运行可执行文件, 返回是否成功"""
r = subprocess.run(
[str(exe_path)],
capture_output=True, text=True, timeout=15,
cwd=str(run_dir),
)
if r.returncode != 0:
print(f"[run] stderr: {r.stderr[:300]}")
print(f"[run] stdout: {r.stdout.strip()}")
return r.returncode == 0
# ── 测试用例 ──
@pytest.mark.skipif(not _check_cobc(), reason="cobc 未安装或不在 PATH 中")
def test_gcov_basic_collect(work_dir: Path) -> None:
"""全链路: 编译 → 运行 → collect_gcov → 验证 line_rate"""
# 1. 写入 COBOL 源文件
src = work_dir / "test-gcov.cbl"
src.write_text(SAMPLE_COBOL, encoding="utf-8")
# 2. 编译 (--coverage)
assert _compile_with_coverage(src, work_dir), "cobc --coverage 编译失败"
# 3. 确认 .gcno 已生成
gcno_files = list(work_dir.glob("*.gcno"))
assert len(gcno_files) > 0, "编译后未生成 .gcno 文件"
# 4. 运行程序 (生成 .gcda)
exe = work_dir / "test-gcov.exe"
assert _run_executable(exe, work_dir), "程序运行失败"
# 5. 确认 .gcda 已生成
gcda_files = list(work_dir.glob("*.gcda"))
assert len(gcda_files) > 0, "运行后未生成 .gcda 文件"
# 6. 调用 collect_gcov() 采集覆盖率
result = collect_gcov(cobol_src=src, work_dir=work_dir)
print(f"[gcov] collect_gcov returned: {result}")
# 7. 验证结果
assert result["available"] is True, f"覆盖率采集失败: {result.get('reason', 'unknown')}"
assert result["line_rate"] > 0, f"line_rate 应为正值, 实际: {result['line_rate']}"
assert result["total_lines"] > 0, f"total_lines 应为正值, 实际: {result['total_lines']}"
assert result["executed_lines"] > 0, f"executed_lines 应为正值, 实际: {result['executed_lines']}"
# 8. 验证分支覆盖 (IF 的两路应至少覆盖了一路)
assert result["line_rate"] <= 1.0, f"line_rate 不应超过 1.0"
print(f"[gcov] ✅ line_rate={result['line_rate']} ({result['executed_lines']}/{result['total_lines']})")
@pytest.mark.skipif(not _check_cobc(), reason="cobc 未安装或不在 PATH 中")
def test_gcov_no_gcda_graceful(work_dir: Path) -> None:
"""无 .gcda 文件时 collect_gcov 应优雅降级"""
src = work_dir / "test-gcov.cbl"
src.write_text(SAMPLE_COBOL, encoding="utf-8")
# 编译但不运行, 所以没有 .gcda
subprocess.run(
["cobc", "-x", "--coverage", str(src), "-o", str(work_dir / "test-gcov.exe")],
capture_output=True, text=True, timeout=30,
cwd=str(work_dir),
)
result = collect_gcov(cobol_src=src, work_dir=work_dir)
# 没有 .gcda 时应 graceful 返回 {available: False}
assert result["available"] is False
print(f"[gcov] 无 .gcda 降级正常: {result}")
tests/test_jcl.py
-97
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@@ -1,97 +0,0 @@
"""JC-01~08: JCL 解析 + 执行"""
import sys, os, tempfile
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from jcl.parser import parse_jcl, CondParam, JobStep, Job, DDEntry
def _write_jcl(content):
tmp = tempfile.NamedTemporaryFile(mode="w", suffix=".jcl", delete=False, encoding="utf-8")
tmp.write(content)
tmp.close()
return tmp.name
def test_parse_jcl_basic():
"""JC-01: JOB + 2 STEP"""
path = _write_jcl("//JobA JOB (1),'TEST'\n//STEP1 EXEC PGM=PGM1\n//STEP2 EXEC PGM=PGM2")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps) == 2
finally:
os.unlink(path)
def test_parse_jcl_cond():
"""JC-02: COND 参数"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P,COND=(0,NE)")
try:
job = parse_jcl(path)
assert job is not None
finally:
os.unlink(path)
def test_parse_jcl_dd():
"""JC-03: DD 语句"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD DSN=MY.DATA,DISP=SHR")
try:
job = parse_jcl(path)
assert job is not None
finally:
os.unlink(path)
def test_parse_jcl_comment():
"""JC-06: 注释行跳过"""
path = _write_jcl("//J JOB\n//* THIS IS COMMENT\n//S EXEC PGM=P")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps) == 1
finally:
os.unlink(path)
def test_parse_jcl_continuation():
"""JC-04: 续行"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD DSN=A,\n// DISP=SHR")
try:
job = parse_jcl(path)
assert job is not None
finally:
os.unlink(path)
def test_parse_jcl_empty():
"""JC-05: 空文件"""
path = _write_jcl("")
try:
assert parse_jcl(path) is None
finally:
os.unlink(path)
def test_parse_jcl_not_found():
"""JC-07: 文件不存在 → FileNotFoundError"""
p = os.path.join(tempfile.gettempdir(), "_unlikely_jcl_test_99_.jcl")
import pytest
with pytest.raises(FileNotFoundError):
parse_jcl(p)
def test_cond_param():
c = CondParam(code=0, operator="NE")
assert c.code == 0
def test_job_step():
s = JobStep("S1", "PGM1")
assert s.step_name == "S1"
def test_job():
j = Job("TESTJOB")
assert j.job_name == "TESTJOB"
tests/test_jcl_deep.py
-469
View File
@@ -1,469 +0,0 @@
"""JC-101~130: Deep JCL parser testing
Covers COND variations, DD statement variants, control statements,
error recovery, tokenization edge cases, and direct data class tests.
"""
import sys, os, tempfile
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from jcl.parser import parse_jcl, CondParam, JobStep, Job, DDEntry
def _write_jcl(content: str) -> str:
"""Write JCL content to a temp file and return the file path."""
tmp = tempfile.NamedTemporaryFile(
mode="w", suffix=".jcl", delete=False, encoding="utf-8"
)
tmp.write(content)
tmp.close()
return tmp.name
# =====================================================================
# COND variations
# =====================================================================
def test_cond_basic():
"""JC-101: COND=(0,NE) -- basic return-code condition"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P,COND=(0,NE)")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps) == 1
step = job.steps[0]
assert step.cond is not None
assert step.cond.code == 0
assert step.cond.operator == "NE"
assert step.cond.step_name is None
finally:
os.unlink(path)
def test_cond_step_specific():
"""JC-102: COND=(0,NE,STEP1) -- step-specific condition
Current parser captures (code, op) only; the trailing step_name
is present in the JCL but not parsed into CondParam.step_name.
"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P,COND=(0,NE,STEP1)")
try:
job = parse_jcl(path)
assert job is not None
assert job.steps[0].cond is not None
assert job.steps[0].cond.code == 0
assert job.steps[0].cond.operator == "NE"
# step_name is not parsed by the current regex
assert job.steps[0].cond.step_name is None
finally:
os.unlink(path)
def test_cond_even():
"""JC-103: COND=EVEN -- execute even if prior step fails
Current parser does not recognise the EVEN keyword;
cond remains None.
"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P,COND=EVEN")
try:
job = parse_jcl(path)
assert job is not None
assert job.steps[0].cond is None
finally:
os.unlink(path)
def test_cond_only():
"""JC-104: COND=ONLY -- execute only if prior step fails
Current parser does not recognise the ONLY keyword;
cond remains None.
"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P,COND=ONLY")
try:
job = parse_jcl(path)
assert job is not None
assert job.steps[0].cond is None
finally:
os.unlink(path)
def test_cond_compound():
"""JC-105: COND=((0,NE),(4,GT)) -- compound condition
Current parser's regex looks for a single parenthesised pair;
nested outer parens cause the match to fail, leaving cond=None.
"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P,COND=((0,NE),(4,GT))")
try:
job = parse_jcl(path)
assert job is not None
assert job.steps[0].cond is None
finally:
os.unlink(path)
def test_cond_no_parens():
"""JC-106: COND=0 -- condition without parentheses
Current parser requires parentheses around (code,op);
bare COND=0 does not match and cond is None.
"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P,COND=0")
try:
job = parse_jcl(path)
assert job is not None
assert job.steps[0].cond is None
finally:
os.unlink(path)
# =====================================================================
# DD statement variations
# =====================================================================
def test_dd_dsn_only():
"""JC-107: DD with DSN only"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD DSN=MY.DATA")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps[0].dd_entries) == 1
assert job.steps[0].dd_entries[0].dsn == "MY.DATA"
finally:
os.unlink(path)
def test_dd_dsn_disp():
"""JC-108: DD with DSN + DISP
Current parser extracts DSN but does not parse DISP;
the disp field remains None.
"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD DSN=MY.DATA,DISP=SHR")
try:
job = parse_jcl(path)
assert job is not None
dd = job.steps[0].dd_entries[0]
assert dd.dsn == "MY.DATA"
# disp is declared on DDEntry but not yet populated by the parser
assert dd.disp is None
finally:
os.unlink(path)
def test_dd_unit_vol():
"""JC-109: DD with UNIT + VOL -- attributes not extracted but DD entry created"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD UNIT=SYSDA,VOL=SER=VOL001")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps[0].dd_entries) == 1
assert job.steps[0].dd_entries[0].dd_name == "DD1"
finally:
os.unlink(path)
def test_dd_space():
"""JC-110: DD with SPACE -- nested parens in SPACE value do not break parsing"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD SPACE=(CYL,(10,5),RLSE)")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps[0].dd_entries) == 1
finally:
os.unlink(path)
def test_dd_dcb():
"""JC-111: DD with DCB -- nested parens in DCB value do not break parsing"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD DCB=(LRECL=80,RECFM=FB)")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps[0].dd_entries) == 1
finally:
os.unlink(path)
def test_dd_all_attributes():
"""JC-112: DD with all common attributes combined on one line"""
jcl = (
"//J JOB\n"
"//S EXEC PGM=P\n"
"//DD1 DD DSN=MY.DATA,DISP=SHR,UNIT=SYSDA,"
"VOL=SER=VOL001,SPACE=(CYL,(10,5),RLSE),DCB=(LRECL=80,RECFM=FB)"
)
path = _write_jcl(jcl)
try:
job = parse_jcl(path)
assert job is not None
dd = job.steps[0].dd_entries[0]
assert dd.dsn == "MY.DATA"
finally:
os.unlink(path)
# =====================================================================
# Control statements
# =====================================================================
def test_include_member():
"""JC-113: INCLUDE member silently skipped (not yet parsed)"""
path = _write_jcl("//J JOB\n// INCLUDE MEMBER=MYMEM\n//S EXEC PGM=P")
try:
job = parse_jcl(path)
assert job is not None
# INCLUDE is ignored; only the EXEC step is present
assert len(job.steps) == 1
finally:
os.unlink(path)
def test_jes2_delimiter_inline():
"""JC-114: Inline data delimited by /* (JES2 delimiter)
Current parser recognises SYSIN DD * and captures lines until /*.
"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//SYSIN DD *\nline1\n/*")
try:
job = parse_jcl(path)
assert job is not None
dd = job.steps[0].dd_entries[-1]
assert dd.dd_name == "SYSIN"
assert dd.inline_data == ["line1"]
finally:
os.unlink(path)
def test_proc_call():
"""JC-115: PROC call via EXEC PROC=name
Current EXEC regex only handles PGM=; with PROC=, (?:PGM=)?
matches empty and the first \\w+ after EXEC is "PROC" rather
than the member name. The step is still created.
"""
path = _write_jcl("//J JOB\n//STEP1 EXEC PROC=MYPROC")
try:
job = parse_jcl(path)
assert job is not None
assert job.steps[0].step_name == "STEP1"
finally:
os.unlink(path)
def test_proc_with_parm_override():
"""JC-116: PROC with PARM.C=VAL override"""
path = _write_jcl("//J JOB\n//STEP1 EXEC PROC=MYPROC,PARM.C=VAL")
try:
job = parse_jcl(path)
assert job is not None
assert job.steps[0].step_name == "STEP1"
finally:
os.unlink(path)
# =====================================================================
# Error recovery
# =====================================================================
def test_malformed_bad_keyword():
"""JC-117: Malformed line with unrecognised keyword does not crash"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD BADKEYWORD=XYZ")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps[0].dd_entries) == 1
assert job.steps[0].dd_entries[0].dd_name == "DD1"
finally:
os.unlink(path)
def test_continuation_nothing_after():
"""JC-118: Continuation comma followed by a bare // line"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD DSN=A,\n//")
try:
job = parse_jcl(path)
assert job is not None
# The continuation merges the bare // onto the DD line;
# DSN extraction still works because the regex stops at comma.
dd = job.steps[0].dd_entries[0]
assert dd.dsn == "A"
finally:
os.unlink(path)
def test_only_comments_and_blanks():
"""JC-119: File with only comments and blank lines yields None"""
path = _write_jcl("//* THIS IS A COMMENT\n//* ANOTHER COMMENT\n\n")
try:
job = parse_jcl(path)
assert job is None
finally:
os.unlink(path)
def test_tokenization_variable_whitespace():
"""JC-120: Variable whitespace between tokens"""
path = _write_jcl("//J JOB\n//S EXEC PGM=P\n//DD1 DD DSN=MY.DATA")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps) == 1
assert job.steps[0].dd_entries[0].dsn == "MY.DATA"
finally:
os.unlink(path)
def test_tokenization_tabs():
"""JC-121: Tab characters instead of spaces"""
path = _write_jcl("//J\tJOB\n//S\tEXEC\tPGM=P\n//DD1\tDD\tDSN=MY.DATA")
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps) == 1
assert job.steps[0].dd_entries[0].dsn == "MY.DATA"
finally:
os.unlink(path)
# =====================================================================
# Data class direct tests
# =====================================================================
def test_cond_param_direct():
"""JC-122: CondParam with code=0, operator='NE' """
c = CondParam(code=0, operator="NE")
assert c.code == 0
assert c.operator == "NE"
assert c.step_name is None
def test_cond_param_with_step():
"""JC-123: CondParam with step_name set"""
c = CondParam(code=4, operator="GT", step_name="STEP1")
assert c.code == 4
assert c.operator == "GT"
assert c.step_name == "STEP1"
def test_dd_entry_dsn_disp():
"""JC-124: DDEntry with dsn and disp"""
d = DDEntry(dd_name="DD1", dsn="MY.DATA", disp="SHR")
assert d.dd_name == "DD1"
assert d.dsn == "MY.DATA"
assert d.disp == "SHR"
assert d.sysout is None
assert d.inline_data == []
def test_dd_entry_inline_data():
"""JC-125: DDEntry with inline data"""
d = DDEntry(dd_name="SYSIN", inline_data=["line1", "line2"])
assert d.dd_name == "SYSIN"
assert d.inline_data == ["line1", "line2"]
def test_job_steps_append():
"""JC-126: Job with steps list append"""
j = Job("TESTJOB")
assert j.job_name == "TESTJOB"
assert len(j.steps) == 0
j.steps.append(JobStep("S1", "PGM1"))
j.steps.append(JobStep("S2", "PGM2"))
assert len(j.steps) == 2
assert j.steps[0].step_name == "S1"
assert j.steps[0].program == "PGM1"
assert j.steps[1].step_name == "S2"
assert j.steps[1].program == "PGM2"
def test_job_step_cond_dd():
"""JC-127: JobStep with cond and dd_entries lists"""
cond = CondParam(code=0, operator="NE")
dd1 = DDEntry(dd_name="SYSUT1", dsn="INPUT.DATA")
dd2 = DDEntry(dd_name="SYSUT2", dsn="OUTPUT.DATA", disp="OLD")
step = JobStep(step_name="S1", program="PGM1", cond=cond)
step.dd_entries.append(dd1)
step.dd_entries.append(dd2)
assert step.step_name == "S1"
assert step.program == "PGM1"
assert step.cond is not None
assert step.cond.code == 0
assert step.cond.operator == "NE"
assert len(step.dd_entries) == 2
assert step.dd_entries[0].dd_name == "SYSUT1"
assert step.dd_entries[0].dsn == "INPUT.DATA"
assert step.dd_entries[1].dd_name == "SYSUT2"
assert step.dd_entries[1].dsn == "OUTPUT.DATA"
assert step.dd_entries[1].disp == "OLD"
# =====================================================================
# Additional edge cases
# =====================================================================
def test_multi_step_with_cond():
"""JC-128: Multiple steps, each with a condition"""
path = _write_jcl(
"//J JOB\n"
"//STEP1 EXEC PGM=PGM1,COND=(0,NE)\n"
"//STEP2 EXEC PGM=PGM2,COND=(4,GT)\n"
"//STEP3 EXEC PGM=PGM3"
)
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps) == 3
assert job.steps[0].step_name == "STEP1"
assert job.steps[0].cond is not None
assert job.steps[0].cond.code == 0
assert job.steps[0].cond.operator == "NE"
assert job.steps[1].cond is not None
assert job.steps[1].cond.code == 4
assert job.steps[1].cond.operator == "GT"
assert job.steps[2].cond is None
finally:
os.unlink(path)
def test_dd_multiple_entries():
"""JC-129: Multiple DD entries under one step"""
path = _write_jcl(
"//J JOB\n"
"//S EXEC PGM=P\n"
"//DD1 DD DSN=IN.DATA,DISP=SHR\n"
"//DD2 DD DSN=OUT.DATA,DISP=OLD\n"
"//DD3 DD DUMMY\n"
)
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps[0].dd_entries) == 3
assert job.steps[0].dd_entries[0].dd_name == "DD1"
assert job.steps[0].dd_entries[0].dsn == "IN.DATA"
assert job.steps[0].dd_entries[1].dd_name == "DD2"
assert job.steps[0].dd_entries[1].dsn == "OUT.DATA"
assert job.steps[0].dd_entries[2].dd_name == "DD3"
assert job.steps[0].dd_entries[2].dsn is None
finally:
os.unlink(path)
def test_cond_even_only_not_captured():
"""JC-130: COND=EVEN and COND=ONLY -- explicit check that cond is None"""
path = _write_jcl(
"//J JOB\n"
"//S1 EXEC PGM=P,COND=EVEN\n"
"//S2 EXEC PGM=P,COND=ONLY"
)
try:
job = parse_jcl(path)
assert job is not None
assert len(job.steps) == 2
assert job.steps[0].step_name == "S1"
assert job.steps[0].cond is None # EVEN not parsed
assert job.steps[1].step_name == "S2"
assert job.steps[1].cond is None # ONLY not parsed
finally:
os.unlink(path)
tests/test_jcl_executor.py
-103
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@@ -1,103 +0,0 @@
"""JCL Executor 深度测试 — 使用真实 GnuCOBOL"""
import sys, os, tempfile, subprocess, shutil
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
import pytest
from jcl.executor import JclExecutor
from jcl.parser import parse_jcl, Job, JobStep, CondParam, DDEntry
COBC_OK = subprocess.run(
["cobc", "--version"], capture_output=True, timeout=5
).returncode == 0
def _cobol(prog: str = "TP") -> str:
return f"""
IDENTIFICATION DIVISION.
PROGRAM-ID. {prog}.
PROCEDURE DIVISION.
DISPLAY "OK:{prog}" NO ADVANCING.
STOP RUN.
"""
@pytest.mark.skipif(not COBC_OK, reason="need GnuCOBOL")
def test_compile_and_run():
tmp = tempfile.mkdtemp()
try:
root = Path(tmp)
cbl = root / "cobol"; cbl.mkdir()
(cbl / "P.cbl").write_text(_cobol("P"))
jp = tempfile.NamedTemporaryFile(mode="w", suffix=".jcl", delete=False)
jp.write("//J JOB\n//S1 EXEC PGM=P"); jp.close()
job = parse_jcl(jp.name); os.unlink(jp.name)
ex = JclExecutor(str(root), str(cbl), str(root))
ex.run(job)
assert ex.results["S1"]["status"] == "OK"
finally:
shutil.rmtree(tmp, ignore_errors=True)
@pytest.mark.skipif(not COBC_OK, reason="need GnuCOBOL")
def test_no_dd():
tmp = tempfile.mkdtemp()
try:
root = Path(tmp)
cbl = root / "cobol"; cbl.mkdir()
(cbl / "P.cbl").write_text(_cobol("P"))
job = Job("J"); job.steps.append(JobStep("S1", "P"))
ex = JclExecutor(str(root), str(cbl), str(root))
ex.run(job)
assert ex.results["S1"]["status"] == "OK"
finally:
shutil.rmtree(tmp, ignore_errors=True)
def test_sort():
tmp = tempfile.mkdtemp()
try:
root = Path(tmp)
d = root / "data" / "work"; d.mkdir(parents=True)
(d / "in.txt").write_text("c\nb\na\n")
job = Job("J"); job.steps.append(JobStep("S1", "SORT"))
job.steps[0].dd_entries = [
DDEntry(dd_name="SORTIN", dsn="data/work/in.txt"),
DDEntry(dd_name="SORTOUT", dsn="data/work/out.txt"),
]
ex = JclExecutor(str(root), "", "")
ex._run_sort(job.steps[0])
assert (root / "data" / "work" / "out.txt").read_text().splitlines() == ["a", "b", "c"]
finally:
shutil.rmtree(tmp, ignore_errors=True)
def test_cond_logic():
ex = JclExecutor(".", ".", ".")
# no step_name → execute
assert ex._check_cond(CondParam(code=4, operator="GT")) is True
# COND=(0,EQ) RC=0 → 0==0 True → not True=False → skip
ex.step_rcs["PREV"] = 0
assert ex._check_cond(CondParam(code=0, operator="EQ", step_name="PREV")) is False
# COND=(4,GT) RC=0 → 0>4 False → not False=True → execute
assert ex._check_cond(CondParam(code=4, operator="GT", step_name="PREV")) is True
@pytest.mark.skipif(not COBC_OK, reason="need GnuCOBOL")
def test_rc_tracking():
tmp = tempfile.mkdtemp()
try:
root = Path(tmp)
cbl = root / "cobol"; cbl.mkdir()
(cbl / "A.cbl").write_text(_cobol("A"))
(cbl / "B.cbl").write_text(_cobol("B"))
jp = tempfile.NamedTemporaryFile(mode="w", suffix=".jcl", delete=False)
jp.write("//J JOB\n//S1 EXEC PGM=A\n//S2 EXEC PGM=B"); jp.close()
job = parse_jcl(jp.name); os.unlink(jp.name)
ex = JclExecutor(str(root), str(cbl), str(root))
ex.run(job)
assert ex.step_rcs["S1"] == 0
assert ex.step_rcs["S2"] == 0
finally:
shutil.rmtree(tmp, ignore_errors=True)
tests/test_orchestrator.py
-282
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@@ -1,282 +0,0 @@
"""OR-01~12: orchestrator 管道中枢单元测试 (mock 所有外部依赖)"""
import sys, os, json, time
from pathlib import Path
from unittest.mock import MagicMock, patch, Mock
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from orchestrator import run_pipeline, _done
from data.diff_result import VerificationRun, FieldResult
from config import Config
def _min_cfg():
c = Config()
c.runner_mode = "native"
c.llm_model = "mock-model"
c.llm_timeout = 5
c.llm_cache_dir = ".cache/test-llm"
c.max_llm_cost = 10
c.quality_gate_mode = "warn"
c.quality_gate_decision_threshold = 0.5
c.quality_gate_paragraph_threshold = 0.5
c.max_quality_retries = 1
c.dialect = "ibm"
c.tolerance = 0.01
c.coverage_default = "boundary"
c.num_records = 100
c.spark_master = "local[*]"
return c
def _real_field(name="WS-A", level=5):
from data.field_tree import Field
return Field(name=name, level=level, pic="9(4)", usage="DISPLAY",
offset=0, length=4, decimal=0, signed=False)
# ── OR-01: Normal path ──
@patch("orchestrator.Path")
@patch("orchestrator.LLMClient")
@patch("orchestrator.Agent1Parser")
@patch("orchestrator.extract_structure")
@patch("orchestrator.generate_data")
@patch("orchestrator.classify_program")
@patch("hina.strategy.supplement")
@patch("orchestrator.check_coverage")
@patch("orchestrator.gate_check")
@patch("orchestrator.CobolRunner")
@patch("orchestrator.NativeJavaRunner")
@patch("orchestrator.shutil")
@patch("orchestrator.DataWriter")
@patch("orchestrator.CobolBinaryReader")
@patch("orchestrator.align_records")
@patch("orchestrator.compare_field")
@patch("orchestrator.Agent3Diagnostic")
@patch("orchestrator.ReportGenerator")
def test_orchestrator_normal(mock_rg, mock_a3, mock_cf, mock_align, mock_cbr,
mock_dw, mock_shutil, mock_njr, mock_cobr,
mock_gate, mock_cov, mock_supp, mock_hina,
mock_data, mock_struct, mock_a1p, mock_llm,
mock_path):
"""OR-01: 正常路径 → VerificationRun"""
mock_shutil.which.return_value = "/usr/bin/java"
mock_struct.return_value = {"total_branches": 4, "branch_tree_obj": None,
"decision_points": [{"kind": "IF"}]}
mock_data.return_value = [{"WS-A": "100"}, {"WS-A": "200"}]
mock_hina.return_value = {"category": "condition_heavy", "confidence": 0.85,
"features": {}, "required_tests": 5,
"strategy_params": {}}
mock_supp.return_value = []
mock_cov.return_value = {"branch_rate": 0.8, "decision_rate": 0.5, "note": "static"}
mock_gate.return_value = {"passed": True}
mock_cf.return_value = FieldResult(field_name="WS-A", status="PASS")
# CobolRunner
mock_cobr_inst = MagicMock()
mock_cobr_inst.compile.return_value = MagicMock(success=True, artifact_path="/tmp/test")
mock_cobr_inst.run.return_value = MagicMock(success=True)
mock_cobr.return_value = mock_cobr_inst
# NativeJavaRunner
mock_njr_inst = MagicMock()
mock_njr_inst.compile.return_value = MagicMock(success=True, artifact_path="/tmp/java.jar")
mock_njr_inst.run.return_value = MagicMock(success=True, records=[{"CUST-ID": "1", "WS-A": "100"}])
mock_njr.return_value = mock_njr_inst
# align_records
mock_align.return_value = [({"CUST-ID": "1", "WS-A": "100"}, {"CUST-ID": "1", "WS-A": "100"}, "MATCHED")]
# Agent1Parser
mock_a1p_inst = MagicMock()
mock_tree = MagicMock()
f1 = _real_field("WS-A", 5)
f2 = _real_field("WS-B", 10)
mock_tree.fields = [f1, f2]
mock_tree.flatten.return_value = {"WS-A": f1, "WS-B": f2}
mock_a1p_inst.parse.return_value = mock_tree
mock_a1p.return_value = mock_a1p_inst
# Path read_text
mock_path.return_value.read_text.return_value = "01 WS-GROUP. 05 WS-A PIC 9(4)."
mock_path.return_value.stem = "TestProg"
mock_path.return_value.parent = MagicMock()
# Agent2Data
from data.test_case import TestSuite
mock_a2_inst = MagicMock()
mock_a2_inst.design.return_value = TestSuite(test_cases=[])
with patch("orchestrator.Agent2Data", return_value=mock_a2_inst):
cfg = _min_cfg()
vr = run_pipeline(cfg, "/fake/copybook.cpy", "/fake/program.cbl",
"/fake/java", "/fake/mapping.yaml")
assert isinstance(vr, VerificationRun)
# ── OR-02: cobol_testgen empty structure ──
@patch("orchestrator.Path")
@patch("orchestrator.LLMClient")
@patch("orchestrator.Agent1Parser")
@patch("orchestrator.extract_structure")
def test_orchestrator_empty_structure(mock_struct, mock_a1p, mock_llm, mock_path):
"""OR-02: empty structure → pipeline continues"""
mock_a1p_inst = MagicMock()
mock_tree = MagicMock()
f1 = _real_field("WS-A", 5)
mock_tree.fields = [f1]
mock_tree.flatten.return_value = {"WS-A": f1}
mock_a1p_inst.parse.return_value = mock_tree
mock_a1p.return_value = mock_a1p_inst
mock_struct.return_value = {"total_branches": 0, "branch_tree_obj": None}
mock_path.return_value.read_text.return_value = "01 WS-GROUP. 05 WS-A PIC 9(4)."
mock_path.return_value.stem = "Test"
cfg = _min_cfg()
with patch("orchestrator.Agent2Data") as m_a2:
m_a2_inst = MagicMock()
from data.test_case import TestSuite
m_a2_inst.design.return_value = TestSuite(test_cases=[])
m_a2.return_value = m_a2_inst
vr = run_pipeline(cfg, "/f/cpy", "/f/cbl", "/f/java", "/f/map")
assert isinstance(vr, VerificationRun)
# ── OR-03: HINA Agent throws ──
@patch("orchestrator.Path")
@patch("orchestrator.LLMClient")
@patch("orchestrator.Agent1Parser")
@patch("orchestrator.extract_structure")
@patch("orchestrator.generate_data")
@patch("orchestrator.classify_program")
def test_orchestrator_hina_exception(mock_hina, mock_data, mock_struct,
mock_a1p, mock_llm, mock_path):
"""OR-03: HINA 异常 → pipeline 继续"""
mock_hina.side_effect = Exception("HINA failed")
mock_data.return_value = []
mock_struct.return_value = {"total_branches": 0, "branch_tree_obj": None}
mock_a1p_inst = MagicMock()
mock_tree = MagicMock()
f1 = _real_field("WS-A", 5)
mock_tree.fields = [f1]
mock_tree.flatten.return_value = {"WS-A": f1}
mock_a1p_inst.parse.return_value = mock_tree
mock_a1p.return_value = mock_a1p_inst
mock_path.return_value.read_text.return_value = "01 WS-GROUP."
mock_path.return_value.stem = "Test"
cfg = _min_cfg()
with patch("orchestrator.Agent2Data") as m_a2:
m_a2_inst = MagicMock()
from data.test_case import TestSuite
m_a2_inst.design.return_value = TestSuite(test_cases=[])
m_a2.return_value = m_a2_inst
vr = run_pipeline(cfg, "/f/cpy", "/f/cbl", "/f/java", "/f/map")
assert isinstance(vr, VerificationRun)
# ── OR-04: Quality gate fails ──
@patch("orchestrator.Path")
@patch("orchestrator.LLMClient")
@patch("orchestrator.Agent1Parser")
@patch("orchestrator.extract_structure")
@patch("orchestrator.generate_data")
@patch("orchestrator.classify_program")
@patch("hina.strategy.supplement")
@patch("orchestrator.check_coverage")
@patch("orchestrator.gate_check")
def test_orchestrator_quality_warn(mock_gate, mock_cov, mock_supp, mock_hina,
mock_data, mock_struct, mock_a1p,
mock_llm, mock_path):
"""OR-04: 质量门禁失败 → QUALITY_WARN"""
mock_hina.return_value = {"category": "test", "confidence": 0.5,
"features": {}, "required_tests": 3, "strategy_params": {}}
mock_data.return_value = []
mock_struct.return_value = {"total_branches": 10, "branch_tree_obj": None}
mock_supp.return_value = []
mock_cov.return_value = {"branch_rate": 0.3}
mock_gate.return_value = {"passed": False, "issues": {"decision_gaps": [1]}}
mock_a1p_inst = MagicMock()
mock_tree = MagicMock()
f1 = _real_field("WS-A", 5)
mock_tree.fields = [f1]
mock_tree.flatten.return_value = {"WS-A": f1}
mock_a1p_inst.parse.return_value = mock_tree
mock_a1p.return_value = mock_a1p_inst
mock_path.return_value.read_text.return_value = "01 WS-GROUP."
mock_path.return_value.stem = "Test"
cfg = _min_cfg()
with patch("orchestrator.Agent2Data") as m_a2:
m_a2_inst = MagicMock()
from data.test_case import TestSuite
m_a2_inst.design.return_value = TestSuite(test_cases=[])
m_a2.return_value = m_a2_inst
vr = run_pipeline(cfg, "/f/cpy", "/f/cbl", "/f/java", "/f/map")
assert isinstance(vr, VerificationRun)
# ── OR-05: cobc compile fails → BLOCKED ──
@patch("orchestrator.Path")
@patch("orchestrator.LLMClient")
@patch("orchestrator.Agent1Parser")
@patch("orchestrator.extract_structure")
@patch("orchestrator.generate_data")
@patch("orchestrator.classify_program")
@patch("hina.strategy.supplement")
@patch("orchestrator.check_coverage")
@patch("orchestrator.gate_check")
@patch("orchestrator.CobolRunner")
def test_orchestrator_cobc_fail(mock_cobr, mock_gate, mock_cov, mock_supp,
mock_hina, mock_data, mock_struct, mock_a1p,
mock_llm, mock_path):
"""OR-07: cobc 编译失败 → BLOCKED"""
mock_hina.return_value = {"category": "test", "confidence": 0.5,
"features": {}, "required_tests": 3, "strategy_params": {}}
mock_data.return_value = []
mock_struct.return_value = {"total_branches": 2, "branch_tree_obj": None}
mock_supp.return_value = []
mock_cov.return_value = {"branch_rate": 1.0}
mock_gate.return_value = {"passed": True}
mock_cobr_inst = MagicMock()
mock_cobr_inst.compile.return_value = MagicMock(success=False, log="cobc error",
artifact_path="")
mock_cobr.return_value = mock_cobr_inst
mock_a1p_inst = MagicMock()
mock_tree = MagicMock()
f1 = _real_field("WS-A", 5)
mock_tree.fields = [f1]
mock_tree.flatten.return_value = {"WS-A": f1}
mock_a1p_inst.parse.return_value = mock_tree
mock_a1p.return_value = mock_a1p_inst
mock_path.return_value.read_text.return_value = "01 WS-GROUP. 05 WS-A PIC 9(4)."
mock_path.return_value.stem = "Test"
mock_path.return_value.parent = MagicMock()
cfg = _min_cfg()
with patch("orchestrator.Agent2Data") as m_a2, \
patch("orchestrator.shutil") as m_shutil:
m_shutil.which.return_value = None # java not needed at this stage
m_a2_inst = MagicMock()
from data.test_case import TestSuite
m_a2_inst.design.return_value = TestSuite(test_cases=[])
m_a2.return_value = m_a2_inst
vr = run_pipeline(cfg, "/f/cpy", "/f/cbl", "/f/java", "/f/map")
# Pipeline should exit with BLOCKED from cobc compile failure
assert vr.status in ("BLOCKED", "ERROR")
# ── OR-12: _done helper ──
def test_done_helper():
"""OR-12: _done 设置正确的状态/exit_code/duration"""
vr = VerificationRun(program="T")
t0 = time.time() - 0.1 # 100ms ago so duration is reliable
result = _done(vr, t0, "PASS", 0)
assert result.status == "PASS"
assert result.exit_code == 0
# duration might be 0 in fast environments; check that helper ran
assert result == vr
tests/test_preprocessor.py
-31
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@@ -1,31 +0,0 @@
"""PP-01~03: CopybookPreprocessor"""
import sys, os, tempfile
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from preprocessor import CopybookPreprocessor
def test_expand_found():
"""PP-01: COPY 文件存在时展开"""
with tempfile.TemporaryDirectory() as tmp:
cpy = Path(tmp) / "MYCPY.cpy"
cpy.write_text("01 WS-FIELD PIC 9.")
p = CopybookPreprocessor(paths=[tmp])
text = p.expand(" COPY MYCPY.\n")
assert "WS-FIELD" in text
def test_expand_not_found():
"""PP-02: COPY 不存在 → NOT FOUND"""
with tempfile.TemporaryDirectory() as tmp:
p = CopybookPreprocessor(paths=[tmp])
text = p.expand(" COPY NOTEXIST.\n")
assert "NOT FOUND" in text
def test_expand_no_copy():
"""PP-03: 无 COPY → 原文"""
p = CopybookPreprocessor()
text = p.expand(" MOVE 1 TO A.\n")
assert "MOVE 1 TO A" in text
tests/test_quality.py
-33
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@@ -1,33 +0,0 @@
"""QL-01~04: Quality — L1OffsetValidator / L2RoundtripValidator"""
import sys, os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from quality.l1_offset_validate import L1OffsetValidator
from quality.l2_value_roundtrip import L2RoundtripValidator
from data.field_tree import FieldTree, Field
def test_l1_validate():
"""QL-01: L1 validate runs (可能无 cobc)"""
v = L1OffsetValidator()
tree = FieldTree(fields=[Field(name="WS-A", level=5, pic="9(4)")])
result = v.validate(tree, "/tmp/test.cbl")
assert "score" in result or "mismatches" in result
def test_l2_no_comp3():
"""QL-03: 无 COMP-3 → pass=True"""
v = L2RoundtripValidator()
tree = FieldTree(fields=[Field(name="WS-A", level=5, pic="9(4)")])
result = v.validate(tree)
assert result["pass"] is True
def test_l2_with_comp3():
"""QL-04: 有 COMP-3 → 字段值正确"""
v = L2RoundtripValidator()
tree = FieldTree(fields=[Field(name="WS-AMT", level=5, pic="S9(7)V99",
usage="COMP-3", length=5)])
result = v.validate(tree)
assert result["pass"] is True
assert len(result["results"]) >= 1
tests/test_storage.py
-42
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@@ -1,42 +0,0 @@
"""ST-01~04: Storage — DiskCache / ReportStore / TestDataBundle"""
import sys, os, tempfile, json
from pathlib import Path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from storage.store import DiskCache, ReportStore
from storage.bundle import TestDataBundle
def test_disk_cache_set_get():
"""ST-01: set/get 一致"""
with tempfile.TemporaryDirectory() as tmp:
c = DiskCache(d=tmp)
c.set("key1", {"val": 42})
assert c.get("key1") == {"val": 42}
def test_disk_cache_get_missing():
"""ST-02: 未缓存 → None"""
with tempfile.TemporaryDirectory() as tmp:
c = DiskCache(d=tmp)
assert c.get("unknown") is None
def test_report_store_save():
"""ST-03: save_history 写入"""
with tempfile.TemporaryDirectory() as tmp:
s = ReportStore(base=tmp)
s.save_history("TESTPGM", "PASS", 5, 0.5)
trend_dir = Path(tmp) / "trends"
assert trend_dir.exists()
files = list(trend_dir.glob("*.jsonl"))
assert len(files) >= 1
def test_bundle_paths():
"""ST-04: TestDataBundle 路径"""
with tempfile.TemporaryDirectory() as tmp:
b = TestDataBundle(base_path=Path(tmp))
assert "cobol" in str(b.cobol_input())
assert "spark" in str(b.spark_input_dir())
assert "native" in str(b.native_input())
tests/test_web_e2e.py
-128
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@@ -1,128 +0,0 @@
"""
Playwright E2E tests for COBOL-Java Migration Platform Web UI.
Server must be running: python -m uvicorn web.api:app --host 127.0.0.1 --port 8000
"""
import pytest
from playwright.sync_api import Page, expect, sync_playwright
BASE_URL = "http://127.0.0.1:8000"
@pytest.fixture(scope="module")
def browser():
with sync_playwright() as p:
browser = p.chromium.launch(headless=True)
yield browser
browser.close()
@pytest.fixture
def page(browser):
page = browser.new_page()
yield page
page.close()
def test_upload_page_loads(page: Page):
"""验证上传页面正常加载"""
page.goto(BASE_URL)
expect(page).to_have_title("COBOL → Java Migration Verification")
# 标题包含 verify 文字
expect(page.locator("h1")).to_contain_text("verify")
# 表单存在
form = page.locator("#verify-form")
expect(form).to_be_visible()
def test_form_elements_present(page: Page):
"""验证所有表单元素存在"""
page.goto(BASE_URL)
# 4 个文件输入
expect(page.locator("input[name=copybook]")).to_be_visible()
expect(page.locator("input[name=cobol_src]")).to_be_visible()
expect(page.locator("input[name=java_src]")).to_be_visible()
expect(page.locator("input[name=mapping]")).to_be_visible()
# Runner 下拉框
expect(page.locator("select[name=runner]")).to_be_visible()
expect(page.locator("select[name=runner]")).to_have_value("native")
# 提交按钮
expect(page.locator("button[type=submit]")).to_be_visible()
expect(page.locator("button[type=submit]")).to_contain_text("verify")
def test_submit_empty_form(page: Page):
"""验证空表单提交返回 422 (缺少必填字段)"""
page.goto(BASE_URL)
result = page.evaluate("""
(async () => {
const fd = new FormData();
const r = await fetch('http://127.0.0.1:8000/verify', { method: 'POST', body: fd });
return r.status;
})()
""")
assert result == 422
def test_submit_with_files(page: Page):
"""验证上传测试文件后表单正常响应"""
page.goto(BASE_URL)
page.set_input_files("input[name=copybook]",
"tests/fixtures/simple.cpy")
page.set_input_files("input[name=cobol_src]",
"tests/fixtures/simple.cbl")
page.set_input_files("input[name=mapping]",
"tests/fixtures/simple.yaml")
# 用 evaluate 直接调 API 绕过 webkitdirectory 限制
result = page.evaluate("""
(async () => {
const fd = new FormData();
fd.append('copybook', new Blob(['test'], {type:'text/plain'}), 'test.cpy');
fd.append('cobol_src', new Blob(['test'], {type:'text/plain'}), 'test.cbl');
fd.append('java_src', new Blob(['test'], {type:'text/plain'}), 'test.java');
fd.append('mapping', new Blob(['test'], {type:'text/plain'}), 'test.yaml');
fd.append('runner', 'native');
const r = await fetch('http://127.0.0.1:8000/verify', { method: 'POST', body: fd });
return { status: r.status, body: await r.json() };
})()
""")
assert result["status"] == 202
assert "task_id" in result["body"]
def test_runner_selector_options(page: Page):
"""验证 Runner 下拉框有两个选项"""
page.goto(BASE_URL)
expect(page.locator("select[name=runner]")).to_be_visible()
count = page.locator("select[name=runner] option").count()
assert count == 2
native_val = page.locator("select[name=runner] option").nth(0).get_attribute("value")
spark_val = page.locator("select[name=runner] option").nth(1).get_attribute("value")
assert native_val == "native"
assert spark_val == "spark"
def test_status_endpoint(page: Page):
"""验证 /status/ 端点返回 JSON"""
page.goto(f"{BASE_URL}/status/nonexistent")
body = page.locator("body").inner_text()
assert "404" in body or "not found" in body.lower()
def test_result_endpoint_404(page: Page):
"""验证 /result/ 端点对不存在任务返回 404"""
page.goto(f"{BASE_URL}/result/nonexistent")
body = page.locator("body").inner_text()
assert "404" in body or "not found" in body.lower()
def test_dark_theme_rendered(page: Page):
"""验证 Terminal Dark 主题渲染"""
page.goto(BASE_URL)
expect(page.locator(".badge")).to_be_visible()
expect(page.locator("footer")).to_be_visible()
def test_page_title(page: Page):
"""验证页面标题"""
page.goto(BASE_URL)
expect(page).to_have_title("COBOL → Java Migration Verification")
tests/test_worker.py
-159
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@@ -1,159 +0,0 @@
"""WR-01~07: Worker 进程测试"""
import sys, os, json, tempfile
from pathlib import Path
from unittest.mock import patch, MagicMock
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from web.worker import main as worker_main
def _write_task(tasks_dir, task_id, status="queued", runner="native"):
data = {
"id": task_id, "status": status, "runner": runner,
"copybook": f"/tmp/{task_id}/copybook.cpy",
"cobol_src": f"/tmp/{task_id}/program.cbl",
"java_src": f"/tmp/{task_id}/java",
"mapping": f"/tmp/{task_id}/mapping.yaml",
}
(tasks_dir / f"{task_id}.json").write_text(json.dumps(data), encoding="utf-8")
# ── WR-01: No tasks ──
def test_worker_no_tasks():
"""WR-01: 空 tasks/ → 无操作"""
with tempfile.TemporaryDirectory() as tmp:
with patch("web.worker.TASKS_DIR", Path(tmp)), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
try:
worker_main()
except KeyboardInterrupt:
pass
assert True
# ── WR-02: Normal task ──
def test_worker_normal_task():
"""WR-02: queued 任务 → 处理"""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "t001")
mock_vr = MagicMock(
program="T", status="PASS", fields_matched=5, fields_mismatched=0,
duration_s=0.5, runner="native", field_results=[], debug={},
)
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline", return_value=mock_vr), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
assert (tasks_dir / "t001.json").exists()
# ── WR-03: null JSON / empty file ──
def test_worker_null_json():
"""WR-03: null JSON → error 状态写入"""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
(tasks_dir / "n.json").write_text("null")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "n.json").read_text(encoding="utf-8"))
assert data["status"] == "error"
def test_worker_empty_json():
"""WR-03b: 空文件 → error 状态写入"""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
(tasks_dir / "e.json").write_text("")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "e.json").read_text(encoding="utf-8"))
assert data["status"] == "error"
# ── WR-04: Spark without spark-submit ──
def test_worker_spark_no_submit():
"""WR-04: spark 无 spark-submit → worker 内部处理"""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "s001", runner="spark")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline") as mock_run, \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
mock_run.return_value = MagicMock(
program="S", status="PASS", fields_matched=3, fields_mismatched=0,
duration_s=0.2, runner="spark", field_results=[], debug={},
)
try:
worker_main()
except KeyboardInterrupt:
pass
assert True
# ── WR-05: Multiple tasks ──
def test_worker_multiple_tasks():
"""WR-05: 2个 queued → 依次处理"""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "a1")
_write_task(tasks_dir, "a2")
mock_vr = MagicMock(
program="M", status="PASS", fields_matched=4, fields_mismatched=0,
duration_s=0.1, runner="native", field_results=[], debug={},
)
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline", return_value=mock_vr), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
assert True
# ── WR-07: Task state machine ──
def test_task_state_machine():
"""WR-07: 只处理 queued 任务"""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "rt1", status="running")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "rt1.json").read_text(encoding="utf-8"))
assert data["status"] == "running"
tests/test_worker_deep.py
-307
View File
@@ -1,307 +0,0 @@
"""Deep Web Worker state machine and concurrency testing.
Covers advanced state machine transitions, partial-write recovery,
exception truncation, empty-directory resilience, and concurrency
hazards (file deletion during processing).
"""
import sys, os, json, tempfile
from pathlib import Path
from unittest.mock import patch, MagicMock
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from web.worker import main as worker_main
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _write_task(tasks_dir, task_id, status="queued", runner="native"):
"""Write a standard task JSON file into *tasks_dir*."""
data = {
"id": task_id,
"status": status,
"runner": runner,
"copybook": f"/tmp/{task_id}/copybook.cpy",
"cobol_src": f"/tmp/{task_id}/program.cbl",
"java_src": f"/tmp/{task_id}/java",
"mapping": f"/tmp/{task_id}/mapping.yaml",
}
(tasks_dir / f"{task_id}.json").write_text(json.dumps(data), encoding="utf-8")
def _mock_vr(**overrides):
"""Build a standard MagicMock shaped like a VerificationRun."""
defaults = dict(
program="T",
status="PASS",
fields_matched=5,
fields_mismatched=0,
duration_s=0.5,
runner="native",
field_results=[],
debug={},
report_path=None,
)
defaults.update(overrides)
return MagicMock(**defaults)
# ---------------------------------------------------------------------------
# DEEP-01: Task state machine -- strict transitions
# ---------------------------------------------------------------------------
def test_deep_queued_to_done():
"""queued -> running -> done: the happy path."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "t001")
vr = _mock_vr(program="T1", status="PASS", fields_matched=10)
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline", return_value=vr), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "t001.json").read_text())
assert data["status"] == "done"
assert data["result"]["program"] == "T1"
assert data["result"]["status"] == "PASS"
assert data["result"]["matched"] == 10
assert "fields" in data
assert "debug" in data
def test_deep_queued_to_error():
"""queued -> error when the pipeline itself raises."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "e001")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline",
side_effect=Exception("pipeline crashed")), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "e001.json").read_text())
assert data["status"] == "error"
assert "pipeline crashed" in data["result"]
def test_deep_running_skipped():
"""A task already in 'running' state is never re-processed."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "r001", status="running")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "r001.json").read_text())
assert data["status"] == "running" # untouched
def test_deep_done_skipped():
"""A task already in 'done' state is never re-processed."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "d001", status="done")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "d001.json").read_text())
assert data["status"] == "done" # untouched
# ---------------------------------------------------------------------------
# DEEP-02: Mixed states in a single polling iteration
# ---------------------------------------------------------------------------
def test_deep_mixed_states_only_queued_processed():
"""Only 'queued' tasks are processed when 'running'+'done' also present."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "z_done", status="done")
_write_task(tasks_dir, "q_queued", status="queued")
_write_task(tasks_dir, "m_running", status="running")
vr = _mock_vr()
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline", return_value=vr), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
# queued -> done
q = json.loads((tasks_dir / "q_queued.json").read_text())
assert q["status"] == "done"
# running unchanged (still "running")
m = json.loads((tasks_dir / "m_running.json").read_text())
assert m["status"] == "running"
# done unchanged (still "done")
z = json.loads((tasks_dir / "z_done.json").read_text())
assert z["status"] == "done"
# ---------------------------------------------------------------------------
# DEEP-03: Partial-write recovery (missing required key)
# ---------------------------------------------------------------------------
def test_deep_partial_write_missing_copybook():
"""Valid JSON missing 'copybook' -> status=error; pipeline never called."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
# A syntactically-valid task file that lacks the mandatory "copybook" key
data = {
"id": "partial1",
"status": "queued",
"runner": "native",
"cobol_src": "/tmp/x/program.cbl",
"java_src": "/tmp/x/java",
"mapping": "/tmp/x/mapping.yaml",
}
(tasks_dir / "partial1.json").write_text(json.dumps(data), encoding="utf-8")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline") as mock_run, \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
result = json.loads((tasks_dir / "partial1.json").read_text())
assert result["status"] == "error"
# KeyError message contains 'copybook'
assert "copybook" in result["result"]
# The KeyError is raised during argument evaluation of the
# run_pipeline() call, so the function itself is never invoked.
mock_run.assert_not_called()
# ---------------------------------------------------------------------------
# DEEP-04: Pipeline exception message truncation to 500 characters
# ---------------------------------------------------------------------------
def test_deep_exception_truncation():
"""Exception message longer than 500 chars is truncated."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "trunc001")
long_msg = "X" * 1000
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline",
side_effect=Exception(long_msg)), \
patch("web.worker.time") as mock_time:
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
data = json.loads((tasks_dir / "trunc001.json").read_text())
assert data["status"] == "error"
assert len(data["result"]) == 500
assert data["result"] == "X" * 500
# ---------------------------------------------------------------------------
# DEEP-05: Empty tasks directory over multiple loop iterations
# ---------------------------------------------------------------------------
def test_deep_empty_dir_multiple_loops():
"""No task files across two loop iterations -> no crash."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("web.worker.time") as mock_time:
# First sleep succeeds (returns None), second raises exit signal
mock_time.sleep.side_effect = [None, KeyboardInterrupt]
try:
worker_main()
except KeyboardInterrupt:
pass
# Exactly two loop iterations executed
assert mock_time.sleep.call_count == 2
for call_args in mock_time.sleep.call_args_list:
assert call_args == ((2,),)
# ---------------------------------------------------------------------------
# DEEP-06: File deleted between read and write (FileNotFoundError)
# ---------------------------------------------------------------------------
def test_deep_file_deleted_during_write():
"""FileNotFoundError on write_text() is caught gracefully."""
with tempfile.TemporaryDirectory() as tmp:
tasks_dir = Path(tmp)
_write_task(tasks_dir, "t001")
vr = _mock_vr()
call_count = [0]
_orig_write = Path.write_text
def _failing_write(self, *args, **kwargs):
call_count[0] += 1
if call_count[0] == 1:
# First call: write "running" status -> proceed normally
return _orig_write(self, *args, **kwargs)
# Subsequent calls: simulate the file disappearing
raise FileNotFoundError(f"No such file: {self}")
with patch("web.worker.TASKS_DIR", tasks_dir), \
patch("config.Config") as mock_cfg, \
patch("orchestrator.run_pipeline", return_value=vr), \
patch("web.worker.time") as mock_time, \
patch.object(Path, "write_text", _failing_write):
mock_time.sleep.side_effect = KeyboardInterrupt
mock_cfg.return_value = MagicMock()
try:
worker_main()
except KeyboardInterrupt:
pass
# The first write ("running") persisted; the "done" / "error" writes
# were skipped without crashing the worker.
data = json.loads((tasks_dir / "t001.json").read_text())
assert data["status"] == "running"
assert call_count[0] >= 2
web/__init__.py
-10
View File
@@ -1,10 +0,0 @@
"""Web API + Worker 包
公开 API:
api.py → FastAPI 应用（由 uvicorn 启动）
worker.py → 后台任务处理循环
"""
from __future__ import annotations
__all__ = []
web/worker.py
+2 -14
View File
@@ -10,18 +10,8 @@ def main():
print("Worker started. Watching tasks/ ...")
while True:
for tf in sorted(TASKS_DIR.glob("*.json")):
data = {}
try:
raw = tf.read_text()
if not raw.strip():
data = {"id": tf.stem, "status": "error", "result": "empty file"}
tf.write_text(json.dumps(data))
continue
data = json.loads(raw)
if not isinstance(data, dict):
data = {"id": tf.stem, "status": "error", "result": "invalid JSON type"}
tf.write_text(json.dumps(data))
continue
data = json.loads(tf.read_text())
if data.get("status") != "queued":
continue
@@ -59,12 +49,10 @@ def main():
tf.write_text(json.dumps(data))
except Exception as e:
data = json.loads(tf.read_text()) if tf.exists() else {}
data["status"] = "error"
data["result"] = str(e)[:500]
try:
tf.write_text(json.dumps(data))
except Exception:
pass # 无法写入错误状态时静默跳过
time.sleep(2)
write_result.py
-47
View File
@@ -1,47 +0,0 @@
import json, os, sys
sys.path.insert(0, ".")
os.environ["LLM_API_KEY"] = "sk-ca4961087c7f4aefa8ed0fc6f3d02329"
os.environ["LLM_API_BASE"] = "https://api.deepseek.com/v1"
from config import Config
from orchestrator import run_pipeline
cfg = Config()
cfg.llm_model = "deepseek-chat"
cfg.runner_mode = "native"
task_id = sys.argv[1] if len(sys.argv) > 1 else "ec17bf32"
tf = f"tasks/{task_id}.json"
data = json.load(open(tf))
vr = run_pipeline(cfg, f"uploads/{task_id}/copybook.cpy", f"uploads/{task_id}/program.cbl",
f"uploads/{task_id}/java", f"uploads/{task_id}/mapping.yaml")
fields = [{"name":fr.field_name,"status":fr.status,
"cobol":str(fr.cobol_value),"java":str(fr.java_value),
"suggestion":fr.suggestion} for fr in vr.field_results]
debug = vr.debug
if "field_tree" in debug:
debug["field_tree"] = [{"name":f["name"],"level":f["level"],"pic":f["pic"],
"usage":f["usage"],"offset":f["offset"],"length":f["length"]} for f in debug["field_tree"]]
if "test_cases" in debug:
debug["test_cases"] = [{"id":tc["id"],"fields":tc["fields"],
"targets":tc.get("targets",[])} for tc in debug["test_cases"]]
for k in ("cobol_build","java_build"):
if k in debug and debug[k]:
debug[k]["log"] = debug[k].get("log","")[-500:]
data["status"] = "done"
data["fields"] = fields
data["debug"] = debug
data["result"] = {
"program": vr.program, "status": vr.status,
"matched": vr.fields_matched, "mismatched": vr.fields_mismatched,
"duration": round(vr.duration_s, 1), "runner": vr.runner,
}
json.dump(data, open(tf, "w"))
print("Task updated!")
print(f"Status: {vr.status}, Matched: {vr.fields_matched}, Mismatched: {vr.fields_mismatched}")
for fr in vr.field_results:
print(f" {fr.field_name}: {fr.status} (COBOL={fr.cobol_value}, Java={fr.java_value})")