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---
language:
- en
- code
size_categories:
- n<1K
task_categories:
- code-generation
tags:
- security
- code-generation
---
# 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). |