GraphCoder

• 📙Paper: GraphCoder: Enhancing Repository-Level Code Completion via Code Context Graph-based Retrieval and Language Model
• 📚Publisher: arxiv
• 🏠Author Affiliation: Peking University, Chinese Academy of Sciences, Huawei
• GitHub: https://github.com/oceaneLIU/GraphCoder
• Contributions:
  • An approach GraphCoder to enhance the effectiveness of retrieval by a coarse-to-fine process, which considers both structural and lexical context, as well as the dependence distance between the completion target and the context;
  • A graph-based representation CCG (code context graph) of source code to capture relevant long-distance context for predicting the semantics of code completion target instead of the widely adopted sequence-based one;
  • Extensive experiments upon 5 LLMs and across 8000 code completion tasks from 20 repositories demonstrate that GraphCoder achieves higher exact match values with reduced retrieval time and overhead in database storage space.