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@@ -47,8 +47,20 @@ dataset_info:
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  <!-- Provide a quick summary of the dataset. -->
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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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  Code: https://github.com/gersteinlab/LocAgent
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@@ -57,7 +69,8 @@ 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")
 
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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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  <!-- Provide a quick summary of the dataset. -->
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+ This is a refined benchmark for evaluating code localization methods.
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+ Compared to the original version, V2 improves data quality by filtering out examples that do not involve any function-level code modifications.
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+ Each entry in the dataset corresponds to a real-world code change, providing rich contextual information for studying bug localization, feature location, and automated code understanding tasks.
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+ We recommend using Loc-Bench_V2 for a more accurate and reliable evaluation of code localization performance.
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+
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+ The table below shows the distribution of categories in the dataset.
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+
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+ | category | count |
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+ |:---------|:---------|
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+ | Bug Report | 275 |
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+ | Feature Request | 216 |
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+ | Performance Issue | 140 |
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+ | Security Vulnerability | 29 |
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+
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  Code: https://github.com/gersteinlab/LocAgent
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  ```
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  from datasets import load_dataset
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+ dataset = load_dataset("czlll/Loc-Bench_V2", split="test")
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+
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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: