Loc-Bench_V1 / README.md
czlll's picture
Update README.md
c44cf3b verified
---
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
- name: __index_level_0__
dtype: int64
splits:
- name: test
num_bytes: 8489578
num_examples: 560
download_size: 3084430
dataset_size: 8489578
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# LOC-BENCH: A Benchmark for Code Localization
LOC-BENCH is a dataset specifically designed to evaluate code localization methods in software repositories. LOC-BENCH provides diverse issues, including bug reports, feature requests, security vulnerabilities, and performance optimizations.
Code: https://github.com/gersteinlab/LocAgent
## πŸ“Š Details
[`Loc-Bench_V1`](https://huggingface.co/datasets/czlll/Loc-Bench_V1) is our **official** dataset for comparison with our approach.
The table below shows the distribution of categories in the dataset.
| category | count |
|:---------|:---------|
| Bug Report | 242 |
| Feature Request | 150 |
| Performance Issue | 139 |
| Security Vulnerability | 29 |
<details>
<summary>Previous Versions</summary>
- [`Loc-Bench_V0.1`](https://huggingface.co/datasets/czlll/Loc-Bench_V0.1): The dataset used in [the early version of our paper](https://arxiv.org/abs/2503.09089).
Some examples in this dataset do not involve function-level code modifications but instead focus on modifying classes.
V1 filters out 100 examples without function-level code modifications, creating a cleaner subset of the dataset.
- [`Loc-Bench_V0.2`](https://huggingface.co/datasets/czlll/Loc-Bench_V0.2): Filtering out examples that do not involve function-level code modifications and then supplementing the dataset to restore it to the original size of 660 examples.
</details>
## πŸ”§ 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_V1", 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}
}
```