SWE-Edit: Rethinking Code Editing for Efficient SWE-Agent 文章

ArXiv CS.CL2026-05-27NEWSen作者: Yikai Zhang, Jiaxin Pei, Kenan Li, Qirui Jin, Maoquan Wang, Jin Pan, Yu Kang, Shengyu Fu, Elsie Nallipogu, Junjie Hu, Yufan Huang, Zijian Jin

摘要

arXiv:2604.26102v2 Announce Type: replace-cross Abstract: Large language model agents have made strong progress on software engineering, yet current systems suffer from a context coupling problem: the standard code editing interface conflates code inspection, modification planning, and edit execution within a single context window, forcing agents to interleave exploratory viewing with strictly formatted edit generation. Irrelevant context accumulates and edit reliability degrades. We propose SWE-Edit, which decomposes the editing interface into two specialized subagents: a Viewer that extracts task-relevant code on demand, and an Editor that executes modifications from high-level natural language plans -- letting the main agent focus on reasoning while delegating context-intensive operations to clean context windows. On SWE-Bench Verified, this decomposition raises resolve rate by 2.1 pp and cuts inference cost by 17.