RepoHyper: Search-Expand-Refine on Semantic Graphs for Repository-Level Code Completion

Code

• github.com/fsoft-ai4code/repohyper
  OfficialIn paperpytorch★ 72

Abstract

Code Large Language Models (CodeLLMs) have demonstrated impressive proficiency in code completion tasks. However, they often fall short of fully understanding the extensive context of a project repository, such as the intricacies of relevant files and class hierarchies, which can result in less precise completions. To overcome these limitations, we present , a multifaceted framework designed to address the complex challenges associated with repository-level code completion. Central to RepoHYPER is the Repo-level Semantic Graph (RSG), a novel semantic graph structure that encapsulates the vast context of code repositories. Furthermore, RepoHyper leverages Expand and Refine retrieval method, including a graph expansion and a link prediction algorithm applied to the RSG, enabling the effective retrieval and prioritization of relevant code snippets. Our evaluations show that markedly outperforms existing techniques in repository-level code completion, showcasing enhanced accuracy across various datasets when compared to several strong baselines. Our implementation of RepoHYPER can be found at https://github.com/FSoft-AI4Code/RepoHyper.

Tasks

Reproductions