CodeRAG Bench

CodeRAG-Bench is a new benchmark designed to evaluate the effectiveness of retrieval-augmented generation (RAG) in improving code generation by large language models (LLMs). Current research focuses on identifying scenarios where retrieving external context (like documentation or code examples) significantly benefits code generation, and on understanding the limitations of current retrieval and generation methods. This benchmark is significant because it provides a standardized evaluation framework to advance the development of more robust and efficient code generation techniques, ultimately impacting software development and AI-assisted programming.