Code Change

Code change research focuses on understanding, analyzing, and automating the processes involved in modifying software. Current efforts concentrate on leveraging large language models (LLMs), like GPT variants, and reinforcement learning to improve code generation, bug detection, and automated code optimization, often using techniques like mutation testing and fuzzing to evaluate model performance. This field is crucial for enhancing software reliability and development efficiency, with applications ranging from improving autonomous driving system safety to accelerating game development and streamlining cross-language software maintenance.