DependEval: Benchmarking LLMs for Repository Dependency Understanding

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

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.373
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
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article

DependEval: Benchmarking LLMs for Repository Dependency Understanding

Yadi Liu, Zhoujun Li, Hongcheng Guo, Jiawei Wang et al.
Software Engineering Research
article

DependEval: Benchmarking LLMs for Repository Dependency Understanding

Yadi Liu, Zhoujun Li, Hongcheng Guo, Jiawei Wang, Junping Du, Yu‐Qing Ni, Huabing Huang
article en

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

Openalex Percentile: Top 71%
Software Engineering Research
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