CodeR: Issue Resolving with Multi-Agent and Task Graphs
Dong Chen
Shaoxin Lin
Muhan Zeng
Daoguang Zan
Jian-Gang Wang
Anton Cheshkov
Jun Sun
Hao Yu
Guoliang Dong
Artem Aliev
Jie Wang
Xiao Cheng
Guangtai Liang
Yuchi Ma
Pan Bian
Tao Xie
Qianxiang Wang

Abstract
GitHub issue resolving recently has attracted significant attention from academia and industry. SWE-bench is proposed to measure the performance in resolving issues. In this paper, we propose CodeR, which adopts a multi-agent framework and pre-defined task graphs to Repair & Resolve reported bugs and add new features within code Repository. On SWE-bench lite, CodeR is able to solve 28.33% of issues, when submitting only once for each issue. We examine the performance impact of each design of CodeR and offer insights to advance this research direction.
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