Code Editing

Code editing research focuses on improving how large language models (LLMs) assist developers in modifying existing code, encompassing tasks like bug fixing, refactoring, and adding features. Current research emphasizes developing robust evaluation benchmarks and training datasets to assess and improve LLMs' code editing capabilities, often employing reinforcement learning and instruction tuning techniques to enhance accuracy and efficiency. This work is significant because it directly addresses the practical needs of software developers, potentially leading to more efficient and reliable code development processes through improved automated code assistance tools.