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ACL Findings2025

DependEval: Benchmarking LLMs for Repository Dependency Understanding

Junjia Du, Yadi Liu, Hongcheng Guo, Jiawei Wang, Haojian Huang, Yunyi Ni, Zhoujun Li

Abstract

While large language models (LLMs) have shown considerable promise in code generation, real-world software development demands advanced repository-level reasoning. This includes understanding dependencies, project structures, and managing multi-file changes. However, the ability of LLMs to effectively comprehend and handle complex code repositories has yet to be fully explored. To address challenges, we introduce a hierarchical benchmark designed to evaluate repository dependency understanding (DEPENDEVAL). Benchmark is based on 2683 repositories collected from real-world websites. It evaluates models on three core tasks: Dependency Recognition, Repository Construction, and Multi-file Editing, across 8 programming languages from actual code repositories. Our evaluation of over 25 LLMs reveals substantial performance gaps and provides valuable insights into repositorylevel code understanding 1 * Corresponding author. 1 We provide code and datasets at https://github.com/ink7- sudo/DependEval.

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Cited by top-tier papers2

  1. EvoEmpirBench: Dynamic Spatial Reasoning with Agent-ExpVerPukun Zhao, Longxiang Wang, Miaowei Wang, Chen Chen et al.AAAI 2026 · 2 citations
  2. Latent Inter-User Difference Modeling for LLM PersonalizationYilun Qiu, Tianhao Shi, Xiaoyan Zhao, Fengbin Zhu et al.EMNLP 2025 · 1 citation

Builds on9

  1. Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah et al.NeurIPS 2020 · 64,255 citations
  2. CodeBERT: A Pre-Trained Model for Programming and Natural LanguagesZhangyin Feng, Daya Guo, Duyu Tang, Nan Duan et al.EMNLP Findings 2020 · 2,828 citations
  3. Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code GenerationJiawei Liu, Chunqiu Steven Xia, Yuyao Wang, Lingming ZhangNeurIPS 2023 · 2,317 citations
  4. SWE-bench: Can Language Models Resolve Real-world Github Issues?Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao et al.ICLR 2024 · 2,082 citations
  5. RepoBench: Benchmarking Repository-Level Code Auto-Completion SystemsTianyang Liu, Canwen Xu, Julian J. McAuleyICLR 2024 · 338 citations

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