Datasets › Draper VDisc Dataset

Draper VDisc Dataset (reza)

Introduced by Rebecca L. Russell et al. in Automated Vulnerability Detection in Source Code Using Deep Representation Learning11 Jul 2018 archive 2025-07-28

Draper VDISC Dataset - Vulnerability Detection in Source Code

The dataset consists of the source code of 1.27 million functions mined from open source software, labeled by static analysis for potential vulnerabilities. For more details on the dataset and benchmark results, see https://arxiv.org/abs/1807.04320.

The data is provided in three HDF5 files corresponding to an 80:10:10 train/validate/test split, matching the splits used in our paper. The combined file size is roughly 1 GB. Each function's raw source code, starting from the function name, is stored as a variable-length UTF-8 string. Five binary 'vulnerability' labels are provided for each function, corresponding to the four most common CWEs in our data plus all others:

  • CWE-120 (3.7% of functions)
  • CWE-119 (1.9% of functions)
  • CWE-469 (0.95% of functions)
  • CWE-476 (0.21% of functions)
  • CWE-other (2.7% of functions)

Functions may have more than one detected CWE each.

Please cite our paper if you use this dataset in a publication: https://arxiv.org/abs/1807.04320

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 4 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

CC-By Attribution 4.0 International

Modalities archive 2025-07-28

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Languages archive 2025-07-28

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Variants archive 2025-07-28

  • Draper VDisc Dataset

1 variant name, as the archive lists them.

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