feat: Phase 2 complete — 13 Phases of COBOL type classification and test benchmark

P0.6: gcov infrastructure
P1: extract_structure output expansion (11 new feature fields)
P2: Confusion group rule engine (8 pairs + contradiction + backtrack)
P3: 4-factor confidence calculation + quality gate update
P4: 33+2 COBOL program type test samples (22 files, 7 categories)
P5: parametrized/ test data generation engine
P6: japanese_data.py lookup tables
P7-10: Type-specific test suites (~159 parametrized tests)
P11: Full classification pipeline (classify_program) + orchestrator integration
P12: Documentation (module-interfaces, test-plan v3.0, coverage-matrix)

Architecture decisions:
- classification_pipeline/ merged to hina/pipeline/
- parametrized/ as independent module
- japanese_data.py as root-level file
- hina/__all__ only exports classify_program()

Co-Authored-By: Claude <noreply@anthropic.com>

config/__init__.py

@@ -2,6 +2,12 @@ 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:
@@ -24,6 +30,8 @@ class Config:
     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