Secure Code Generation
Collection
Datasets and models created for secure code generation. • 3 items • Updated
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YAML Metadata Warning:The task_categories "code-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
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 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).
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