Files
cobol-java-v3/cobol_testgen/design_mcdc.py
T
NB-076 e2a8d53e60 fix: 覆盖率统计全面修复 + 5漏洞修正
## 修复内容

### C1: _mark_eval 反向操作符 (coverage.py)
- EVALUATE 约束匹配支持  操作符
- WHEN OTHER 的自动检测(全部 WHEN 被否定时)

### C2: _mark_perform 反向操作符 (coverage.py)
- PERFORM 同 _mark_if 的反向操作符匹配
- PERFORM UNTIL 条件截断后桥接器通过 branch_names 识别类型

### H1: parse_single_condition 传递 fields (coverage.py)
- collect_decision_points 调用时传 fields 参数
- NOT 前缀条件解析 (NOT WS-X > 50 → WS-X <= 50)

### H4: generate_data 输入约束 (__init__.py)
- 文档注明接收原始源码,非预处理后文本

### M1: not_map break (cond.py)
- NOT 操作符映射循环添加 break

## 覆盖测试结果
- IF: 100% (T/F)
- NOT IF: 100% (NOT_TRUE/NOT_FALSE)
- PERFORM UNTIL: 100% (ENTER/SKIP)
- EVALUATE: 100% (4 WHENs)
- Nested IF: 100% (4 branches)
- S15 回归: 17/17 PASS

Co-Authored-By: Claude <noreply@anthropic.com>
2026-06-24 21:14:50 +08:00

234 lines
8.3 KiB
Python

"""Non-exploding path enumeration — per-decision-point coverage, O(N) paths.
Strategy:
1. Walk the tree once to collect ALL decision points and their "access paths"
2. For each decision point D, generate 2 paths:
- D=True with ancestor and descendant access constraints
- D=False with ancestor and descendant access constraints
3. Total: 2 * N paths, where N = number of decision points
This guarantees every branch is exercised at least once, without O(2^N) explosion.
"""
import re
import logging
from .models import BrSeq, BrIf, BrEval, BrPerform, BrSearch, Assign, CallNode, CondNot, CondLeaf, ExitNode, GoTo
from .cond import parse_single_condition, parse_compound_condition, is_field, collect_leaves, mcdc_sets
logger = logging.getLogger(__name__)
_STOP = ('__STOP__', '', None, True)
def _parse_condition(condition_text, fields):
"""Parse an IF condition into (field, op, value) or None."""
parsed = parse_single_condition(condition_text, fields)
if parsed and is_field(parsed[0], fields):
return parsed
if parsed:
return parsed
return None
def _invert_condition(parsed):
"""Invert a parsed condition (True ↔ False)."""
if parsed is None:
return None
field, op, val = parsed
inv_op = {'=': '<>', '<>': '=', '>': '<=', '<': '>=', '>=': '<', '<=': '>'}.get(op, op)
return (field, inv_op, val)
# ── Collect all decision points with access paths ──
def _collect_all_dps(node, fields, path_cons=None, path_assign=None, depth=0):
"""Walk tree, collect list of (decision_point, access_path) tuples.
Returns list of dicts:
{ "node": decision_point_node,
"kind": "IF"|"EVALUATE"|"PERFORM"|"SEARCH"|"AT_END",
"access_constraints": [constraints to reach this point],
"branches": list of (branch_label, body_node_children)
"true_idx": index of "True" branch in branches,
"false_idx": index of "False" branch (or None),
}
"""
path_cons = list(path_cons or [])
path_assign = dict(path_assign or {})
result = []
if isinstance(node, BrIf):
parsed = _parse_condition(node.condition, fields)
dp = {
"node": node, "kind": "IF",
"condition": node.condition,
"parsed": parsed,
"access_constraints": list(path_cons),
"true_idx": 0,
"false_idx": 1 if parsed else None,
}
result.append(dp)
# Recurse into both branches
t_cons = list(path_cons)
f_cons = list(path_cons)
if parsed:
field, op, val = parsed
t_cons.append((field, op, val, True))
f_cons.append((field, op, val, False))
result.extend(_collect_all_dps(node.true_seq, fields, t_cons, path_assign, depth + 1))
result.extend(_collect_all_dps(node.false_seq, fields, f_cons, path_assign, depth + 1))
elif isinstance(node, BrEval):
dp = {
"node": node, "kind": "EVALUATE",
"subject": node.subject,
"access_constraints": list(path_cons),
}
result.append(dp)
for value, seq in node.when_list:
w_cons = list(path_cons)
if is_field(node.subject, fields):
w_cons.append((node.subject, '=', value, True))
result.extend(_collect_all_dps(seq, fields, w_cons, path_assign, depth + 1))
if node.has_other:
result.extend(_collect_all_dps(node.other_seq, fields, list(path_cons), path_assign, depth + 1))
elif isinstance(node, BrPerform):
if node.perf_type in ('until', 'para_until', 'varying', 'para_varying'):
parsed = _parse_condition(node.condition, fields)
dp = {
"node": node, "kind": "PERFORM",
"condition": node.condition,
"parsed": parsed,
"access_constraints": list(path_cons),
}
result.append(dp)
if parsed:
field, op, val = parsed
body_cons = list(path_cons) + [(field, op, val, False)]
else:
body_cons = list(path_cons)
result.extend(_collect_all_dps(node.body_seq, fields, body_cons, path_assign, depth + 1))
else:
result.extend(_collect_all_dps(node.body_seq, fields, list(path_cons), path_assign, depth + 1))
elif isinstance(node, BrSeq):
for child in node.children:
result.extend(_collect_all_dps(child, fields, path_cons, path_assign, depth))
elif isinstance(node, BrSearch):
dp = {
"node": node, "kind": "SEARCH",
"access_constraints": list(path_cons),
}
result.append(dp)
result.extend(_collect_all_dps(node.at_end_seq, fields, list(path_cons), path_assign, depth + 1))
for _, seq in node.when_list:
result.extend(_collect_all_dps(seq, fields, list(path_cons), path_assign, depth + 1))
return result
def _make_path_for_branch(dp, branch_idx, fields):
"""Create a single path (constraints, assignments) for one branch of a decision point."""
constraints = list(dp.get("access_constraints", []))
kind = dp["kind"]
if kind == "IF":
parsed = dp.get("parsed")
if parsed is None:
return ([], {})
field, op, val = parsed
want_true = (branch_idx == dp.get("true_idx", 0))
if not want_true:
field2, op2, val2 = _invert_condition(parsed)
field, op, val = field2, op2, val2
constraints.append((field, op, val, True))
# Pick body, just take first assignment
node = dp["node"]
body_seq = node.true_seq if branch_idx == 0 else node.false_seq
return (constraints, {})
if kind == "EVALUATE":
node = dp["node"]
n_when = len(node.when_list)
if branch_idx < n_when:
value, seq = node.when_list[branch_idx]
if is_field(node.subject, fields):
constraints.append((node.subject, '=', value, True))
prior_cases = [v for v, _ in node.when_list[:branch_idx]]
for prior in prior_cases:
constraints.append((node.subject, '<>', prior, True))
return (constraints, {})
if kind == "PERFORM":
parsed = dp.get("parsed")
if parsed is None:
return ([], {})
field, op, val = parsed
if branch_idx == 0:
constraints.append((field, op, val, False))
else:
constraints.append((field, op, val, True))
return (constraints, {})
return ([], {})
# ── Public API ──
def enum_paths(node, fields):
"""Linear path enumeration: one True + one False per decision point.
Returns list of (constraints, assignments) tuples.
Total paths = 2 * number_of_decision_points (capped at 1000).
"""
all_dps = _collect_all_dps(node, fields)
MAX_PATH = 1000
paths = []
# Start with one neutral path (no constraints)
paths.append(([], {}))
for dp in all_dps:
kind = dp["kind"]
if kind == "IF":
true_path = _make_path_for_branch(dp, dp.get("true_idx", 0), fields)
false_path = _make_path_for_branch(dp, dp.get("false_idx", 1) if dp.get("false_idx") is not None else dp.get("true_idx", 0), fields)
if true_path:
paths.append(true_path)
if false_path:
paths.append(false_path)
elif kind == "EVALUATE":
node = dp["node"]
for i in range(len(node.when_list)):
bp = _make_path_for_branch(dp, i, fields)
if bp: paths.append(bp)
if node.has_other:
other_cons = list(dp.get("access_constraints", []))
for v, _ in node.when_list:
if is_field(node.subject, fields):
other_cons.append((node.subject, '<>', v, True))
paths.append((other_cons, {}))
elif kind == "PERFORM":
enter_path = _make_path_for_branch(dp, 0, fields)
skip_path = _make_path_for_branch(dp, 1, fields)
if enter_path: paths.append(enter_path)
if skip_path: paths.append(skip_path)
if len(paths) >= MAX_PATH:
paths = paths[:MAX_PATH]
break
return paths
def _filter_stop(cons):
return [c for c in cons if c is not _STOP]