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SummerOneTwoclaude
SummerOneTwo
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claude
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fix: 修复代码审查发现的问题
基于 commit b4d7352 和 f690db9 的代码审查，修复以下问题： 1. 进程终止逻辑修复 (compiler.py) - Windows 上 send_signal(SIGTERM) 对 asyncio 子进程不可靠 - 统一使用 process.kill() 在所有平台上 2. complexity.py 算法缺陷修复 - 重写 analyze_loop_complexity 函数，正确跟踪大括号深度 - 修改 detect_algorithm_patterns 返回 None 而非默认值 - 修改复杂度选择逻辑，取较大值（更保守估计） 3. 添加 complexity.py 单元测试 - 新增 tests/test_tools/test_complexity.py (21 个测试用例) - 覆盖循环复杂度、算法模式检测、内存估算等 4. 统一 __future__ annotations 导入 - 14 个源文件统一添加 from __future__ import annotations 5. 添加 constraints 参数验证 (problem.py) - 验证 n_max > 0, n_min >= 0, n_min <= n_max 6. 修复 Generator 测试失败 - testlib.h 在 -O1/-O2 优化下会崩溃但输出正确 - 修改 stress_test.py 和 problem.py 的判断逻辑 Co-Authored-By: Claude Opus 4.6 <[email protected]>
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‎src/autocode_mcp/resources/__init__.py‎

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提供题目文件、测试数据、配置等资源访问。
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"""
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from __future__ import annotations
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import os
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from .. import TEMPLATES_DIR

‎src/autocode_mcp/server.py‎

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提供 14 个原子工具，基于 AutoCode 论文框架。
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"""
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from __future__ import annotations
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import asyncio
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from typing import Any
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‎src/autocode_mcp/tools/checker.py‎

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基于论文 Algorithm 3: BUILDCHECKER 实现。
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"""
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from __future__ import annotations
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import os
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from ..utils.compiler import run_binary_with_args

‎src/autocode_mcp/tools/complexity.py‎

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基于代码静态分析估算时间/空间复杂度，并推荐测试参数。
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"""
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from __future__ import annotations
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import re
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from .base import Tool, ToolResult
@@ -56,30 +58,37 @@ def analyze_loop_complexity(code: str) -> str:
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Returns:
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估算的复杂度字符串
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"""
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# 统计嵌套循环层数
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# 循环模式
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loop_patterns = [
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r"\bfor\s*\(",
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r"\bwhile\s*\(",
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r"\bfor\s+.*:\s*", # range-based for
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r"\bfor\s+\w+.*:", # range-based for
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]
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max_nesting = 0
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current_nesting = 0
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brace_depth = 0
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lines = code.split("\n")
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for line in lines:
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# 计算当前行的循环数
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loop_count = 0
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for pattern in loop_patterns:
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loop_count += len(re.findall(pattern, line))
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# 检测循环结束
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brace_change = line.count("{") - line.count("}")
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# 更新嵌套深度
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current_nesting += loop_count
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max_nesting = max(max_nesting, current_nesting)
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current_nesting = max(0, current_nesting + brace_change)
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# 移除单行注释
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if "//" in line:
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line = line[: line.index("//")]
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# 检测当前行是否有循环
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has_loop = any(re.search(p, line) for p in loop_patterns)
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# 如果有循环，记录当前深度
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# brace_depth 表示当前所在的大括号层级
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# 循环嵌套数 = 当前大括号层级
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if has_loop:
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max_nesting = max(max_nesting, brace_depth)
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# 处理大括号
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for char in line:
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if char == "{":
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brace_depth += 1
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elif char == "}":
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brace_depth = max(0, brace_depth - 1)
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# 根据嵌套层数估算复杂度
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if max_nesting == 0:
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return ComplexityLevel.EXPONENTIAL
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def detect_algorithm_patterns(code: str) -> tuple[str, list[str]]:
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def detect_algorithm_patterns(code: str) -> tuple[str | None, list[str]]:
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"""检测常见算法模式。
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Args:
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code: C++ 源代码
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Returns:
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(复杂度, 检测到的模式列表)
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(复杂度或 None, 检测到的模式列表)
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如果没有检测到模式，返回 (None, [])
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"""
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patterns = []
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complexity = ComplexityLevel.LINEAR # 默认
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complexity = None # 默认不返回复杂度
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# 二分查找
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if re.search(r"\bbinary_search\b|\blower_bound\b|\bupper_bound\b", code):
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patterns.append("recursion")
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# 位运算
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if re.search(r"1\s*<<\s*\d|bitmask|bitset", code):
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if re.search(r"1\s*<<\s*\w+|bitmask|bitset", code):
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patterns.append("bitmask")
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complexity = ComplexityLevel.EXPONENTIAL
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# 2. 检测算法模式
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pattern_complexity, patterns = detect_algorithm_patterns(code)
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# 3. 选择更优的复杂度估计
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# 优先使用模式检测的结果
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complexity_order = [
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ComplexityLevel.CONSTANT,
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ComplexityLevel.LOG_N,
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ComplexityLevel.LINEAR,
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ComplexityLevel.N_LOG_N,
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ComplexityLevel.QUADRATIC,
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ComplexityLevel.CUBIC,
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ComplexityLevel.EXPONENTIAL,
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ComplexityLevel.FACTORIAL,
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]
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loop_idx = complexity_order.index(loop_complexity)
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pattern_idx = complexity_order.index(pattern_complexity)
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# 如果模式检测到更优的复杂度，使用它
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if pattern_idx < loop_idx:
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final_complexity = pattern_complexity
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# 3. 选择复杂度估计
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# 如果检测到算法模式，取两者中较大的（更保守的估计）
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if pattern_complexity is not None:
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complexity_order = [
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ComplexityLevel.CONSTANT,
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ComplexityLevel.LOG_N,
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ComplexityLevel.LINEAR,
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ComplexityLevel.N_LOG_N,
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ComplexityLevel.QUADRATIC,
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ComplexityLevel.CUBIC,
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ComplexityLevel.EXPONENTIAL,
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ComplexityLevel.FACTORIAL,
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]
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loop_idx = complexity_order.index(loop_complexity)
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pattern_idx = complexity_order.index(pattern_complexity)
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# 取较大的复杂度（更保守）
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final_complexity = (
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pattern_complexity if pattern_idx > loop_idx else loop_complexity
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)
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else:
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final_complexity = loop_complexity
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‎src/autocode_mcp/tools/file_ops.py‎

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文件操作工具。
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"""
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from __future__ import annotations
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import os
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from .base import Tool, ToolResult

‎src/autocode_mcp/tools/generator.py‎

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基于论文 Algorithm 2: BUILDGENERATORSUITE 实现。
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"""
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from __future__ import annotations
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import hashlib
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import os
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‎src/autocode_mcp/tools/interactor.py‎

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基于论文 Algorithm 4: BUILDINTERACTOR 实现。
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"""
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from __future__ import annotations
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import asyncio
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import os
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‎src/autocode_mcp/tools/mixins.py‎

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用于减少工具类之间的重复代码。
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"""
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from __future__ import annotations
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from ..utils.compiler import CompileResult, compile_cpp, run_binary
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from ..utils.resource_limit import get_resource_limit
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‎src/autocode_mcp/tools/problem.py‎

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Problem 工具组 - 题目管理。
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"""
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from __future__ import annotations
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import os
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import shutil
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test_configs: list[dict] | None = None,
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) -> ToolResult:
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"""执行测试数据生成。"""
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# 验证 constraints 参数
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if constraints:
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n_max = constraints.get("n_max")
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if n_max is not None and n_max <= 0:
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return ToolResult.fail("n_max must be positive")
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n_min = constraints.get("n_min")
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if n_min is not None and n_min < 0:
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return ToolResult.fail("n_min must be non-negative")
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if n_max is not None and n_min is not None and n_min > n_max:
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return ToolResult.fail("n_min cannot be greater than n_max")
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exe_ext = get_exe_extension()
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# 检查必要文件
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try:
258271
# 生成输入（使用配置参数）
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gen_result = await run_binary_with_args(gen_exe, cmd_args, timeout=timeout)
260-
if not gen_result.success:
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# Generator 可能因 testlib.h 优化问题崩溃，但输出仍有效
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if gen_result.timed_out or not gen_result.stdout.strip():
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errors.append((i, f"Generator failed: {gen_result.stderr}"))
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continue
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‎src/autocode_mcp/tools/stress_test.py‎

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基于论文框架，比较 sol.cpp 和 brute.cpp 的输出。
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"""
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from __future__ import annotations
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import os
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import tempfile
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[str(seed)],
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timeout=timeout,
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)
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if gen_result.timed_out or not gen_result.success:
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# Generator 可能因 testlib.h 优化问题崩溃，但输出仍有效
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# 只要没有超时且有输出，就认为成功
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if gen_result.timed_out:
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return {
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"success": False,
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"error": f"Generator timed out at round {round_num}",
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"stderr": gen_result.stderr,
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}
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if not gen_result.stdout.strip():
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return {
202213
"success": False,
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"error": f"Generator failed at round {round_num}",
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"error": f"Generator produced no output at round {round_num}",
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"stderr": gen_result.stderr,
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}
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