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@@ -47,21 +47,30 @@ dataset_info:
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  LOC-BENCH is a dataset specifically designed for evaluating code localization methods in software repositories.
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  LOC-BENCH provides a diverse set of issues, including bug reports, feature requests, security vulnerabilities, and performance optimizations.
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- Note:
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- This is the dataset that was used in [paper](https://arxiv.org/abs/2503.09089).
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- Actually, this dataset is the first version;
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- We later released a refined version, [`czlll/Loc-Bench`](https://huggingface.co/datasets/czlll/Loc-Bench), with improved data quality by filtering out examples that do not modify any functions.
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- We recommend using the refined dataset to evaluate code localization performance.
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- <!-- Code: https://github.com/gersteinlab/LocAgent -->
 
 
 
 
 
 
 
 
 
 
 
 
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  ## 🔧 How to Use
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  You can easily load LOC-BENCH using Hugging Face's datasets library:
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  ```
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  from datasets import load_dataset
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- dataset = load_dataset("czlll/Loc-Bench_V0", split='test')
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  ```
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  ## 📄 Citation
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  If you use LOC-BENCH in your research, please cite our paper:
 
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  LOC-BENCH is a dataset specifically designed for evaluating code localization methods in software repositories.
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  LOC-BENCH provides a diverse set of issues, including bug reports, feature requests, security vulnerabilities, and performance optimizations.
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+ Please refer to [**`Loc-Bench_V1`**](https://huggingface.co/datasets/czlll/Loc-Bench_V1) for evaluating code localization methods and for easy comparison with our approach.
 
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+ Code: https://github.com/gersteinlab/LocAgent
 
 
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+
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+ ## 📊 Details
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+ This is the dataset that was used in [the early version of our paper](https://arxiv.org/abs/2503.09089).
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+ We later released a refined version, [`czlll/Loc-Bench_V1`](https://huggingface.co/datasets/czlll/Loc-Bench_V1), with improved data quality by filtering out examples that do not modify any functions.
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+ We **recommend** using the refined dataset to evaluate code localization performance.
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+
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+ The table below shows the distribution of categories in the dataset `Loc-Bench_V0.1`.
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+ | category | count |
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+ |:---------|:---------|
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+ | Bug Report | 282 |
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+ | Feature Request | 203 |
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+ | Performance Issue | 144 |
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+ | Security Vulnerability | 31 |
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  ## 🔧 How to Use
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  You can easily load LOC-BENCH using Hugging Face's datasets library:
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  ```
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  from datasets import load_dataset
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+ dataset = load_dataset("czlll/Loc-Bench_V0.1", split='test')
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  ```
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  ## 📄 Citation
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  If you use LOC-BENCH in your research, please cite our paper: