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LOC-BENCH: A Benchmark for Code Localization

LOC-BENCH is a dataset specifically designed for evaluating code localization methods in software repositories. LOC-BENCH provides a diverse set of issues, including bug reports, feature requests, security vulnerabilities, and performance optimizations.

Please refer to the official version Loc-Bench_V1 for evaluating code localization methods and for easy comparison with our approach.

Code: https://github.com/gersteinlab/LocAgent

πŸ“Š Details

This is the dataset that was used in the early version of our paper. We later released a refined version, czlll/Loc-Bench_V1, with improved data quality by filtering out examples that do not modify any functions. We recommend using the refined dataset to evaluate code localization performance.

The table below shows the distribution of categories in the dataset Loc-Bench_V0.1.

category count
Bug Report 282
Feature Request 203
Performance Issue 144
Security Vulnerability 31

πŸ”§ How to Use

You can easily load LOC-BENCH using HF Mirror's datasets library:

from datasets import load_dataset

dataset = load_dataset("czlll/Loc-Bench_V0.1", split='test')

πŸ“„ Citation

If you use LOC-BENCH in your research, please cite our paper:

@article{chen2025locagent,
title={LocAgent: Graph-Guided LLM Agents for Code Localization},
author={Chen, Zhaoling and Tang,Xiangru and Deng,Gangda and Wu,Fang and Wu,Jialong and Jiang,Zhiwei and Prasanna,Viktor and Cohan,Arman and Wang,Xingyao},
journal={arXiv preprint arXiv:2503.09089},
year={2025}
}
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Paper for czlll/Loc-Bench_V0.1