English(EN) Externalizing Requirement-to-Repair Artifacts as Observable Traces for LLM-Based Program Repair

新研究详细介绍了可审计的基于 LLM 的软件修复工作流

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-15 04:00

一篇新研究论文介绍了一种名为 THEMIS 的工作流，旨在使使用大型语言模型修复软件错误的流程更加透明和可审计。该系统将需求修复的产物外部化，创建语义解释和运行时需求-代码图。对 300 个 SWE-bench Lite 案例的回顾性审计表明，THEMIS 提供了全面的开发者理由和审计记录，便于跨阶段检查和分析修复决策。 AI

影响增强了 LLM 驱动的软件修复的透明度和可审计性，可能提高 AI 生成代码修复的可靠性和信任度。

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Zewen Tao, Shin-nosuke Ishikawa · 2026-09-15 04:00

将需求修复构件外部化为基于 LLM 的程序修复的可观察跟踪

arXiv:2609.14913v1 Announce Type: new Abstract: Repository-level repair requires not only correct patches but also inspectable records that explain how issue requirements are translated into code changes and post-edit evidence. We contribute THEMIS, a stage-aware repair workflow …

本文如何被排名

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将需求修复构件外部化为基于 LLM 的程序修复的可观察跟踪

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