Co-PatcheR: Collaborative Software Patching with Component-specific Small Reasoning Models

Motivated by the success of general purpose large language models (LLMs) in software patching, recent works started to train specialized patching models. Most works trained one model to handle the end to end patching pipeline (including issue localization, patch generation, and patch validation). However, it is hard for a small model to handle all tasks, as different sub-tasks have different workflows and require different expertise. As such, by using a 70 billion model, SOTA methods can only reach up to 41% resolved rate on SWE-bench-Verified. Motivated by the collaborative nature, we propose Co-PatcheR, the first collaborative patching system with small and specialized reasoning models for individual components.