AI-Powered Bug Fixing: A Collaborative Approach
Enhancing LLMs with programmer intent and collaborative behavior simulation
PATCH is a novel framework that transforms automated bug fixing by simulating real-world collaborative programming practices with LLMs.
Key innovations:
- Introduces programmer-intent guidance to understand bug context beyond just code snippets
- Implements a multi-agent collaborative system that mimics real-world debugging workflows
- Achieves superior bug fixing performance through specialized agent roles working together
- Demonstrates 35% improvement over existing approaches in complex bug scenarios
This research bridges critical gaps in automated software maintenance by incorporating human-like collaborative problem-solving, potentially reducing debugging costs and improving software reliability for engineering teams.