metadata

license: apache-2.0
task_categories:
  - text-generation
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: repo
      dtype: string
    - name: instance_id
      dtype: string
    - name: base_commit
      dtype: string
    - name: patch
      dtype: string
    - name: test_patch
      dtype: string
    - name: problem_statement
      dtype: string
    - name: hints_text
      dtype: string
    - name: created_at
      dtype: int64
    - name: labels
      sequence: string
    - name: category
      dtype: string
    - name: edit_functions
      sequence: string
    - name: added_functions
      sequence: string
    - name: edit_functions_length
      dtype: int64
  splits:
    - name: test
      num_bytes: 11007786
      num_examples: 660
  download_size: 3913633
  dataset_size: 11007786

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.

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

🔧 How to Use

You can easily load LOC-BENCH using Hugging Face's datasets library:

from datasets import load_dataset

dataset = load_dataset("czlll/Loc-Bench")

📄 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}
}