size_categories:100K<n<1M format:parquet modality:tabular modality:text library:datasets library:dask library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: category
    dtype: string
  - name: file_name
    dtype: string
  - name: verification_finished
    dtype: string
  - name: vulnerable_line
    dtype: int64
  - name: column
    dtype: int64
  - name: function
    dtype: string
  - name: violated_property
    dtype: string
  - name: error_type
    dtype: string
  - name: code_snippet
    dtype: string
  - name: source_code
    dtype: string
  - name: num_lines
    dtype: int64
  - name: cyclomatic_complexity
    dtype: float32
  splits:
  - name: train
    num_bytes: 960684901
    num_examples: 331000
  download_size: 133615536
  dataset_size: 960684901
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Dataset Card for Dataset Name

<!-- Provide a quick summary of the dataset. -->
Lanuage model generated c code with security vulnerabilities 
From

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** https://github.com/FormAI-Dataset/FormAI-dataset/?tab=readme-ov-file
- **Paper:** https://dl.acm.org/doi/10.1145/3617555.3617874



## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**
@inproceedings{10.1145/3617555.3617874,
author = {Tihanyi, Norbert and Bisztray, Tamas and Jain, Ridhi and Ferrag, Mohamed Amine and Cordeiro, Lucas C. and Mavroeidis, Vasileios},
title = {The FormAI Dataset: Generative AI in Software Security through the Lens of Formal Verification},
year = {2023},
isbn = {9798400703751},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3617555.3617874},
doi = {10.1145/3617555.3617874},
booktitle = {Proceedings of the 19th International Conference on Predictive Models and Data Analytics in Software Engineering},
pages = {33–43},
numpages = {11},
keywords = {Artificial Intelligence, Dataset, Formal Verification, Large Language Models, Software Security, Vulnerability Classification},
location = {<conf-loc>, <city>San Francisco</city>, <state>CA</state>, <country>USA</country>, </conf-loc>},
series = {PROMISE 2023}
}