AI编程助手找对文件但漏关键行，SWE-Explore基准揭示问题
AI coding agents find the right file but miss the exact lines that matter, study shows
AI编程助手找不准关键行
一项新研究显示，Claude Code和Codex等AI编程助手在定位文件时准确率较高，但会错过文件中大部分关键代码行。
新发布的SWE-Explore基准首次将代码搜索与修复步骤分离测试，发现缺乏足够上下文时，即使最佳修复也会失败。该基准评估了多个模型，结果显示它们平均只能找到约30%的关键行。
这表明AI编码代理在精确理解代码逻辑方面仍有显著短板。
AI coding agents find the right file but miss the exact lines that matter, study shows
AI coding agents like Claude Code or Codex reliably find the right file but miss most of the critical lines within it. The new SWE-Explore benchmark is the first to test code search separately from the actual repair, and it shows that without enough context, even the best fix will fail. The article AI coding agents find the right file but miss the exact lines that matter, study shows appeared first on The Decoder .
This report is categorized under AITOP's "Papers" desk. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include Claude Code, Codex, SWE-Explore, 编程助手.
Source attribution: curated from Decoder (@Jonathan Kemper).
