5 papers
Lingxi: Repository-Level Issue Resolution Framework Enhanced by Procedural Knowledge Guided Scaling
Xu Yang, Jiayuan Zhou, Michael Pacheco +5
Driven by the advancements of Large Language Models (LLMs), LLM-powered agents are making significant improvements in software engineering tasks, yet struggle with complex, reposit…
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…
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…
One-for-All Does Not Work! Enhancing Vulnerability Detection by Mixture-of-Experts (MoE)
Xu Yang, Shaowei Wang, Jiayuan Zhou +1
Deep Learning-based Vulnerability Detection (DLVD) techniques have garnered significant interest due to their ability to automatically learn vulnerability patterns from previously…
Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM
Xu Yang, Wenhan Zhu, Michael Pacheco +4
Detecting vulnerability fix commits in open-source software is crucial for maintaining software security. To help OSS identify vulnerability fix commits, several automated approach…