program-repair.html 关键词 program repair 的长期追踪 RSS，汇总历史命中文献。 zh-CN Sun, 28 Jun 2026 05:24:06 +0000 ../papers/arxiv-b661505d2f8b.html https://arxiv.org/abs/2606.27205v1#2026-06-26#program-repair Fri, 26 Jun 2026 13:16:53 +0800 Language Models (LLMs) are powerful toolsand have been increasingly adopted for complex software engineering tasks. As the number of parameters increases, results can often be improved, but this also imposes substantialmemory requirements. While quantization effectively reduces thememory footprint, its overall impact is often summarized onlyby benchmark scores, which mask changes in model behaviorand non-functional overheads. In this work, we conduct anempirical evaluation of LLM quantization u… ../papers/arxiv-f2d059b8979b.html https://arxiv.org/abs/2606.26978v1#2026-06-26#program-repair Fri, 26 Jun 2026 13:16:53 +0800 LLM-based agents for program repair are increasingly built on a "generate-run-revise" paradigm, iteratively executing tests to evaluate and refine patches. This execution-based approach has become standard practice in state-of-the-art systems. However, executions can be time-consuming and expensive, yet their impact on these agents remains underexplored. In this paper, we conduct a two-stage empirical study over execution behavior in LLM-based program repair. To characterize execution behavior… ../papers/arxiv-18e76ca79373.html https://arxiv.org/abs/2606.03870#2026-06-03#program-repair Wed, 03 Jun 2026 14:09:56 +0800 The development of complex software systems, e.g., cyber-physical systems (CPSs), involves continuous evolution of both system implementations and their requirements. These two artifacts often proceed independently, creating a risk of misalignment. For example, a system may be updated due to implementation-level concerns, yielding a new version that no longer satisfies its original requirements. Traditional compliance recovery techniques, e.g., automated program repair, address this problem by… ../papers/arxiv-4ff8b4048b9a.html https://arxiv.org/abs/2605.27238v1#2026-05-27#program-repair Wed, 27 May 2026 13:23:19 +0800 LLM-based agents have moved automated program repair (APR) from fixed-context patch generation to interactive repository-level repair. However, existing agentic APR systems still struggle to use execution evidence to guide localization, patch generation, and validation. We propose EviACT (Evidence-to-Action), an agentic APR framework that coordinates three evidence-driven guardrails across repair stages. The retrieval scaffold grounds repair context, the compile gate filters invalid edits, and…