89 citations · 104 across the 14 of their papers we have counts for
15 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…
EvalSVA: Multi-Agent Evaluators for Next-Gen Software Vulnerability Assessment
Xin-Cheng Wen, Jiaxin Ye, Cuiyun Gao +2
Software Vulnerability (SV) assessment is a crucial process of determining different aspects of SVs (e.g., attack vectors and scope) for developers to effectively prioritize effort…
Repository-Level Graph Representation Learning for Enhanced Security Patch Detection
Xin-Cheng Wen, Zirui Lin, Cuiyun Gao +3
Software vendors often silently release security patches without providing sufficient advisories (e.g., Common Vulnerabilities and Exposures) or delayed updates via resources (e.g.…
VulEval: Towards Repository-Level Evaluation of Software Vulnerability Detection
Xin-Cheng Wen, Xinchen Wang, Yujia Chen +3
Deep Learning (DL)-based methods have proven to be effective for software vulnerability detection, with a potential for substantial productivity enhancements for detecting vulnerab…
SCALE: Constructing Structured Natural Language Comment Trees for Software Vulnerability Detection
Xin-Cheng Wen, Cuiyun Gao, Shuzheng Gao +2
Recently, there has been a growing interest in automatic software vulnerability detection. Pre-trained model-based approaches have demonstrated superior performance than other Deep…
ReposVul: A Repository-Level High-Quality Vulnerability Dataset
Xinchen Wang, Ruida Hu, Cuiyun Gao +3
Open-Source Software (OSS) vulnerabilities bring great challenges to the software security and pose potential risks to our society. Enormous efforts have been devoted into automate…
Game Rewards Vulnerabilities: Software Vulnerability Detection with Zero-Sum Game and Prototype Learning
Xin-Cheng Wen, Cuiyun Gao, Xinchen Wang +3
Recent years have witnessed a growing focus on automated software vulnerability detection. Notably, deep learning (DL)-based methods, which employ source code for the implicit acqu…
When Less is Enough: Positive and Unlabeled Learning Model for Vulnerability Detection
Xin-Cheng Wen, Xinchen Wang, Cuiyun Gao +3
Automated code vulnerability detection has gained increasing attention in recent years. The deep learning (DL)-based methods, which implicitly learn vulnerable code patterns, have…
LIVABLE: Exploring Long-Tailed Classification of Software Vulnerability Types
Xin-Cheng Wen, Cuiyun Gao, Feng Luo +3
Prior studies generally focus on software vulnerability detection and have demonstrated the effectiveness of Graph Neural Network (GNN)-based approaches for the task. Considering t…
What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?
Shuzheng Gao, Xin-Cheng Wen, Cuiyun Gao +3
Pre-trained models of source code have gained widespread popularity in many code intelligence tasks. Recently, with the scaling of the model and corpus size, large language models…