arxiv:2406.01304

CodeR: Issue Resolving with Multi-Agent and Task Graphs

Published on Jun 3, 2024

Authors:

Daoguang Zan ,

Abstract

CodeR uses a multi-agent framework and predefined task graphs to resolve bugs and add features in code repositories, achieving 28.33% issue resolution on SWE-bench lite.

AI-generated summary

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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