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English(EN) BLAgent: Agentic RAG for File-Level Bug Localization

BLAgent框架通过代理式RAG增强文件级错误定位

研究人员开发了BLAgent,一个新颖的代理式检索增强生成(RAG)框架,旨在改进软件维护中的文件级错误定位。BLAgent集成了代码结构感知编码、双视角查询转换和两阶段代理式重排序过程。该方法在本地化准确性和计算成本之间取得了平衡,在使用开源模型时,在SWE-bench Lite上实现了超过78%的Top-1准确率,在使用闭源模型时,准确率超过86%,同时比现有方法更具成本效益。当集成到自动化程序修复框架中时,BLAgent已证明端到端修复成功率可提高高达25%。 AI

影响 提高了软件调试和自动化程序修复的效率和准确性。

排序理由 该集群包含一篇详细介绍新颖错误定位框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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BLAgent框架通过代理式RAG增强文件级错误定位

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该集群包含一篇详细介绍新颖错误定位框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Md Afif Al Mamun, Gias Uddin ·

    BLAgent:用于文件级 Bug 定位的 Agentic RAG

    arXiv:2605.17965v2 Announce Type: replace-cross Abstract: Bug localization remains a key bottleneck for large language model (LLM)-based software maintenance, where accurately identifying faulty code is essential for debugging, root cause analysis, triage, and automated program r…