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>

runners/__init__.py

@@ -1 +1,31 @@
+"""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
+]