8 papers
Memoir: Learning, Verifying, and Evolving False-Positive Memories for Static Application Security Testing Tools
Shenyuan Guan, Qiaodan Hou, Yanjun Chen +4
Static Application Security Testing (SAST) tools have become indispensable in modern secure software devel- opment. However, these tools often generate false-positive (FP) alerts,…
StriderSPD: Structure-Guided Joint Representation Learning for Binary Security Patch Detection
Qingyuan Li, Chenchen Yu, Chuanyi Li +4
Vulnerabilities severely threaten software systems, making the timely application of security patches crucial for mitigating attacks. However, software vendors often silently patch…
Benchmarking LLMs for Fine-Grained Code Review with Enriched Context in Practice
Ruida Hu, Xinchen Wang, Xin-Cheng Wen +5
Code review is a cornerstone of software quality assurance, and recent advances in Large Language Models (LLMs) have shown promise in its automation. However, existing benchmarks f…
Vul-R2: A Reasoning LLM for Automated Vulnerability Repair
Xin-Cheng Wen, Zirui Lin, Yijun Yang +2
The exponential increase in software vulnerabilities has created an urgent need for automatic vulnerability repair (AVR) solutions. Recent research has formulated AVR as a sequence…
MLLM-Based UI2Code Automation Guided by UI Layout Information
Fan Wu, Cuiyun Gao, Shuqing Li +2
Converting user interfaces into code (UI2Code) is a crucial step in website development, which is time-consuming and labor-intensive. The automation of UI2Code is essential to stre…
Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning Data
Xin-Cheng Wen, Yijun Yang, Cuiyun Gao +2
Large language models (LLMs) demonstrate considerable proficiency in numerous coding-related tasks; however, their capabilities in detecting software vulnerabilities remain limited…