RefactorAssist: Agentic Refinement for Reliable Code Refactoring

📰 ArXiv cs.AI

Learn how RefactorAssist uses agentic refinement to improve reliable code refactoring with Large Language Models (LLMs)

advanced Published 4 Aug 2026

Action Steps

Apply RefactorAssist to your codebase to automate refactoring tasks
Use Large Language Models (LLMs) to generate initial refactoring suggestions
Configure RefactorAssist to refine and validate the suggested refactorings
Test the refactored code to ensure functional behavior is preserved
Compare the results with manual refactoring to evaluate the effectiveness of RefactorAssist

Who Needs to Know This

Software engineers and developers can benefit from RefactorAssist to automate code refactoring tasks while ensuring reliability and accuracy

Key Insight

💡 Agentic refinement can improve the reliability of LLM-based code refactoring by reducing errors and preserving functional behavior

Key Takeaways

Learn how RefactorAssist uses agentic refinement to improve reliable code refactoring with Large Language Models (LLMs)

Full Article

Title: RefactorAssist: Agentic Refinement for Reliable Code Refactoring

Abstract:
arXiv:2608.00924v1 Announce Type: cross Abstract: Code refactoring aims to enhance the internal structure of source code without affecting its functional behavior. The recent advancements of Large Language Models (LLMs) have demonstrated potential for automating software engineering tasks, such as code refactoring. However, the refactorings produced by LLMs often introduce subtle errors, leading to functional behavior changes and failed unit tests, which limit their practical adoption. To addres

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