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cs.SE2025
A Study on Mixup-Inspired Augmentation Methods for Software Vulnerability Detection
Seyed Shayan Daneshvar, Da Tan, Shaowei Wang +1
Various deep learning (DL) methods have recently been utilized to detect software vulnerabilities. Real-world software vulnerability datasets are rare and hard to acquire, as there…
cs.SE2024
VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs
Seyed Shayan Daneshvar, Yu Nong, Xu Yang +2
Detecting vulnerabilities is vital for software security, yet deep learning-based vulnerability detectors (DLVD) face a data shortage, which limits their effectiveness. Data augmen…