HAFixAgent：历史感知的自动化程序修复智能体

HAFixAgent: History-Aware Automated Program Repair Agent

November 2, 2025

作者: Yu Shi, Hao Li, Bram Adams, Ahmed E. Hassan

cs.AI

摘要

近年来，自动化程序修复（APR）研究已转向大语言模型和基于智能体的系统，但现有系统大多依赖本地快照上下文，忽略了代码库历史。已有研究表明，代码库历史有助于单行错误的修复，因为最后修改错误代码行的提交往往就是引入该错误的提交。本文系统性地探究代码库历史能否在大规模场景下提升智能体式APR系统的性能，特别是针对复杂的多区块错误。我们提出HAFixAgent——一种历史感知的错误修复智能体，它将基于代码追溯的仓库启发式信息注入修复循环。通过对Defects4J中全部854个真实错误的初步研究，我们发现与错误相关的历史信息不仅广泛存在且高度集中，这为系统设计提供了依据。HAFixAgent与两种前沿基准方法的实证对比表明：（1）有效性：相较基于智能体的基准方法提升212.3%，较针对多区块错误的基准方法提升29.9%；（2）效率：历史信息未显著增加智能体步骤，令牌成本保持相当水平，且在复杂多文件-多区块错误场景下中位数成本显著降低；（3）实用性：组合不同历史启发式策略可修复更多错误，形成清晰的成本效益权衡。HAFixAgent为历史感知的智能体式APR提供了实用方案：将智能体锚定于版本控制历史，优先采用基于差异的历史上下文，并在需要时整合互补性启发式策略。

English

Automated program repair (APR) has recently shifted toward large language models and agent-based systems, yet most systems rely on local snapshot context, overlooking repository history. Prior work shows that repository history helps repair single-line bugs, since the last commit touching the buggy line is often the bug-introducing one. In this paper, we investigate whether repository history can also improve agentic APR systems at scale, especially for complex multi-hunk bugs. We present HAFixAgent, a History-Aware Bug-Fixing Agent that injects blame-derived repository heuristics into its repair loop. A preliminary study of all 854 real-world bugs from Defects4J motivates our design, showing that bug-relevant history is both widely available and highly concentrated. Empirical comparison of HAFixAgent with two state-of-the-art baselines shows: (1) Effectiveness: HAFixAgent significantly improves over the agent-based baseline (by 212.3%) and the multi-hunk baseline (by 29.9%). (2) Efficiency: history does not significantly increase agent steps and keeps token costs comparable, with notably lower median costs for complex multi-file-multi-hunk bugs. (3) Practicality: combining different historical heuristics repairs more bugs, offering a clear cost-benefit trade-off. HAFixAgent offers a practical recipe for history-aware agentic APR: ground the agent in version control history, prioritize diff-based historical context, and integrate complementary heuristics when needed.