6 papers
Debt Behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild
Yue Liu, Ratnadira Widyasari, Yanjie Zhao +3
AI coding assistants are now widely used in software development. Software developers increasingly integrate AI-generated code into their codebases to improve productivity. Prior s…
Revisiting Vulnerability Patch Identification on Data in the Wild
Ivana Clairine Irsan, Ratnadira Widyasari, Ting Zhang +7
Attacks can exploit zero-day or one-day vulnerabilities that are not publicly disclosed. To detect these vulnerabilities, security researchers monitor development activities in ope…
Back to the Basics: Rethinking Issue-Commit Linking with LLM-Assisted Retrieval
Huihui Huang, Ratnadira Widyasari, Ting Zhang +8
Issue-commit linking, which connects issues with commits that fix them, is crucial for software maintenance. Existing approaches have shown promise in automatically recovering thes…
Let the Trial Begin: A Mock-Court Approach to Vulnerability Detection using LLM-Based Agents
Ratnadira Widyasari, Martin Weyssow, Ivana Clairine Irsan +6
Detecting vulnerabilities in source code remains a critical yet challenging task, especially when benign and vulnerable functions share significant similarities. In this work, we i…
CleanVul: Automatic Function-Level Vulnerability Detection in Code Commits Using LLM Heuristics
Yikun Li, Ting Zhang, Ratnadira Widyasari +13
Accurate identification of software vulnerabilities is crucial for system integrity. Vulnerability datasets, often derived from the National Vulnerability Database (NVD) or directl…
JavaVFC: Java Vulnerability Fixing Commits from Open-source Software
Tan Bui, Yan Naing Tun, Yiran Cheng +3
We present a comprehensive dataset of Java vulnerability-fixing commits (VFCs) to advance research in Java vulnerability analysis. Our dataset, derived from thousands of open-sourc…