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A Repository-Level Dataset For Detecting, Classifying and Repairing Software Vulnerabilities. (arXiv:2401.13169v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Open-Source Software (OSS) vulnerabilities bring great challenges to the
software security and pose potential risks to our society. Enormous efforts
have been devoted into automated vulnerability detection, among which deep
learning (DL)-based approaches have proven to be the most effective. However,
the current labeled data present the following limitations: (1) \textbf{Tangled
Patches}: Developers may submit code changes unrelated to vulnerability fixes
within patches, leading to tangled patches. (2) \textbf{Lacking
Inter-procedural Vulnerabilities}: The existing vulnerability datasets
typically contain function-level and file-level …
arxiv automated automated vulnerability detection challenges current data dataset deep learning detection great open-source software oss repository risks security society software software security software vulnerabilities vulnerabilities vulnerability vulnerability detection