Teaching Code Refactoring Using LLMs

• URL: http://arxiv.org/abs/2508.09332v1
• Date: Tue, 12 Aug 2025 20:41:19 GMT
• Title: Teaching Code Refactoring Using LLMs
• Authors: Anshul Khairnar, Aarya Rajoju, Edward F. Gehringer,
• Abstract summary: Large Language Models (LLMs) can enhance the teaching of code in software engineering courses through real-time, context-aware feedback.<n>Refactoring improves code quality but is difficult to teach, especially with complex, real-worlds.
• Score: 0.7407754140732635
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This Innovative Practice full paper explores how Large Language Models (LLMs) can enhance the teaching of code refactoring in software engineering courses through real-time, context-aware feedback. Refactoring improves code quality but is difficult to teach, especially with complex, real-world codebases. Traditional methods like code reviews and static analysis tools offer limited, inconsistent feedback. Our approach integrates LLM-assisted refactoring into a course project using structured prompts to help students identify and address code smells such as long methods and low cohesion. Implemented in Spring 2025 in a long-lived OSS project, the intervention is evaluated through student feedback and planned analysis of code quality improvements. Findings suggest that LLMs can bridge theoretical and practical learning, supporting a deeper understanding of maintainability and refactoring principles.

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