Effective and Efficient Context Retrieval via Partial Dependency Graph for Repository-Level Code Generation
LLM-based repository-level code generation aims to generate code using the context available in a software repository, requiring LLMs to reason over complex code dependencies. Due to limited context windows and insufficient repository-specific understanding, LLMs typically rely on retrieval-augmented generation (RAG) to incorporate relevant code. Early RAG approaches primarily employ similarity-based retrieval, which often fails to retrieve code snippets that the target function depends on. Recent work introduces graph-based retrieval to model such dependencies, but typically relies on manually designed rules and static global graphs, leading to limited flexibility and high construction a...
| Authors | Zhongxin Liu, Zhonghao Jiang, Zhifan Ye et al. |
|---|---|
| Primary category | cs.SE |
| Published | 3 August 2026 |
| Last updated at source | 3 August 2026 |
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