Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles
This addresses the need for more precise and interpretable automated debugging tools for software developers, though it appears incremental as it builds on existing patch-and-test concepts with LLMs.
The authors tackled the problem of low precision and limited interpretability in LLM-based software engineering by developing Repeton, a structured patch-and-test framework that achieved good performance on the SWE-bench Lite benchmark compared to RAG-based methods.
Large Language Models (LLMs) have shown strong capabilities in code generation and comprehension, yet their application to complex software engineering tasks often suffers from low precision and limited interpretability. We present Repeton, a fully open-source framework that leverages LLMs for precise and automated code manipulation in real-world Git repositories. Rather than generating holistic fixes, Repeton operates through a structured patch-and-test pipeline: it iteratively diagnoses issues, proposes code changes, and validates each patch through automated testing. This stepwise process is guided by lightweight heuristics and development tools, avoiding reliance on embedding-based retrieval systems. Evaluated on the SWE-bench Lite benchmark, our method shows good performance compared to RAG-based methods in both patch validity and interpretability. By decomposing software engineering tasks into modular, verifiable stages, Repeton provides a practical path toward scalable and transparent autonomous debugging.