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s2e-lab/SecurityEval

Dataset Card for SecurityEval This dataset is from the paper titled SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques. The project is accepted for The first edition of the International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S '22). The paper describes the dataset for evaluating machine learning-based code generation output and the application of the dataset to the… See the full description on the dataset page: https://huggingface.co/datasets/s2e-lab/SecurityEval.

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Dataset Card

Dataset Card for SecurityEval

This dataset is from the paper titled SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques. The project is accepted for The first edition of the International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S '22). The paper describes the dataset for evaluating machine learning-based code generation output and the application of the dataset to the code generation tools.

Dataset Details

Dataset Description

  • —Curated by: Mohammed Latif Siddiq & Joanna C. S. Santos
  • —Language(s): Python

Dataset Sources

  • —Repository: https://github.com/s2e-lab/SecurityEval
  • —Paper: "SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques". International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S '22). https://s2e-lab.github.io/preprints/msr4ps22-preprint.pdf

Dataset Structure

  • —dataset.jsonl: dataset file in jsonl format. Every line contains a JSON object with the following fields:
  • —ID: unique identifier of the sample.
  • —Prompt: Prompt for the code generation model.
  • —Insecure_code: code of the vulnerability example that may be generated from the prompt.

Citation

BibTeX:

@inproceedings{siddiq2022seceval,
  author={Siddiq, Mohammed Latif and Santos, Joanna C. S. },
  booktitle={Proceedings of the 1st International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S22)}, 
  title={SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques}, 
  year={2022},
  doi={10.1145/3549035.3561184}
}

APA:

Siddiq, M. L., & Santos, J. C. (2022, November). SecurityEval dataset: mining vulnerability examples to evaluate machine learning-based code generation techniques. In Proceedings of the 1st International Workshop on Mining Software Repositories Applications for Privacy and Security (pp. 29-33).