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>

comparator/__init__.py

@@ -0,0 +1,25 @@
+"""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
+]