4 papers
Skilled AI Agents for Embedded and IoT Systems Development
Yiming Li, Yuhan Cheng, Mingchen Ma +6
Large language models (LLMs) and agentic systems have shown promise for automated software development, but applying them to hardware-in-the-loop (HIL) embedded and Internet-of-Thi…
Reducing False Positives in Static Bug Detection with LLMs: An Empirical Study in Industry
Xueying Du, Jiayi Feng, Yi Zou +6
Static analysis tools (SATs) are widely adopted in both academia and industry for improving software quality, yet their practical use is often hindered by high false positive rates…
Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG
Xueying Du, Geng Zheng, Kaixin Wang +9
Although LLMs have shown promising potential in vulnerability detection, this study reveals their limitations in distinguishing between vulnerable and similar-but-benign patched co…
Minimizing False Positives in Static Bug Detection via LLM-Enhanced Path Feasibility Analysis
Xueying Du, Kai Yu, Chong Wang +6
Static bug analyzers play a crucial role in ensuring software quality. However, existing analyzers for bug detection in large codebases often suffer from high false positive rates.…