SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Issue resolution has made remarkable progress thanks to the advanced
reasoning capabilities of large language models (LLMs). Recently, agent-based
frameworks such as SWE-agent have further advanced this progress by enabling
autonomous, tool-using agents to tackle complex software engineering tasks.
While existing agent-based issue resolution approaches are primarily based on
agents' independent explorations, they often get stuck in local solutions and
fail to identify issue patterns that span across different parts of the
codebase. To address this limitation, we propose SWE-Debate, a competitive
multi-agent debate framework that encourages diverse reasoning paths and
achieves more consolidated issue localization. SWE-Debate first creates
multiple fault propagation traces as localization proposals by traversing a
code dependency graph. Then, it organizes a three-round debate among
specialized agents, each embodying distinct reasoning perspectives along the
fault propagation trace. This structured competition enables agents to
collaboratively converge on a consolidated fix plan. Finally, this consolidated
fix plan is integrated into an MCTS-based code modification agent for patch
generation. Experiments on the SWE-bench benchmark show that SWE-Debate
achieves new state-of-the-art results in open-source agent frameworks and
outperforms baselines by a large margin.
688c53d88c434640078cc471
Han Li
688c53d88c434640078cc472
Yuling Shi
claimed_verified
2025-08-06T19:29:54.627Z
645b0c3ec35da9c7afd95421
https://cdn-avatars.huggingface.co/v1/production/uploads/645b0c3ec35da9c7afd95421/vYBrCDagHsXAo6J2p-uG0.jpeg
Yuling
user
YerbaPage
688c53d88c434640078cc473
Shaoxin Lin
688c53d88c434640078cc474
Xiaodong Gu
688c53d88c434640078cc475
Heng Lian
688c53d88c434640078cc476
Xin Wang
688c53d88c434640078cc477
Yantao Jia
688c53d88c434640078cc478
Tao Huang
688c53d88c434640078cc479
Qianxiang Wang
SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Issue resolution has made remarkable progress thanks to the advanced
reasoning capabilities of large language models (LLMs). Recently, agent-based
frameworks such as SWE-agent have further advanced this progress by enabling
autonomous, tool-using agents to tackle complex software engineering tasks.
While existing agent-based issue resolution approaches are primarily based on
agents' independent explorations, they often get stuck in local solutions and
fail to identify issue patterns that span across different parts of the
codebase. To address this limitation, we propose SWE-Debate, a competitive
multi-agent debate framework that encourages diverse reasoning paths and
achieves more consolidated issue localization. SWE-Debate first creates
multiple fault propagation traces as localization proposals by traversing a
code dependency graph. Then, it organizes a three-round debate among
specialized agents, each embodying distinct reasoning perspectives along the
fault propagation trace. This structured competition enables agents to
collaboratively converge on a consolidated fix plan. Finally, this consolidated
fix plan is integrated into an MCTS-based code modification agent for patch
generation. Experiments on the SWE-bench benchmark show that SWE-Debate
achieves new state-of-the-art results in open-source agent frameworks and
outperforms baselines by a large margin.
SWE-Debate, a competitive multi-agent framework, enhances issue resolution in software engineering by promoting diverse reasoning and achieving better issue localization and fix planning.
large language models agent-based frameworks SWE-agent autonomous agents tool-using agents software engineering tasks local solutions issue patterns codebase competitive multi-agent debate fault propagation traces code dependency graph specialized agents reasoning perspectives structured competition consolidated fix plan MCTS-based code modification agent SWE-bench benchmark