22 citations · 40 across the 22 of their papers we have counts for
12 papers · 1 filter
PRWeaver: Evaluating LLM-Based Code Auditors against Long-Horizon Malicious Pull Requests
Yuekun Wang, Mingfei Cheng, Xiaofei Xie
LLM-based code auditors are increasingly integrated into pull-request (PR) workflows, yet their reliability against adversarial changes distributed across repository evolution rema…
EvoEye: Self-Evolving Runtime Monitoring for Autonomous Driving Systems
Mingfei Cheng, Lionel Briand, Xiaofei Xie
Runtime monitoring is essential for detecting impending hazards in autonomous driving systems (ADSs). However, existing ADS runtime monitors have fixed detection capabilities: rule…
Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference
Xuyan Ma, Yawen Wang, Junjie Wang +5
Platform-orchestrated agentic workflows have become a popular paradigm for developing LLM-based applications. However, their reliability remains a major challenge due to the uncert…
PentestEval: Benchmarking LLM-based Penetration Testing with Modular and Stage-Level Design
Ruozhao Yang, Mingfei Cheng, Gelei Deng +3
Penetration testing is essential for assessing and strengthening system security against real-world threats, yet traditional workflows remain highly manual, expertise-intensive, an…
Enhancing Automated Program Repair via Faulty Token Localization and Quality-Aware Patch Refinement
Jiaolong Kong, Xiaofei Xie, Yiheng Xiong +2
Large language models (LLMs) have recently demonstrated strong potential for automated program repair (APR). However, existing LLM-based techniques primarily rely on coarse-grained…
STCLocker: Deadlock Avoidance Testing for Autonomous Driving Systems
Mingfei Cheng, Renzhi Wang, Xiaofei Xie +2
Autonomous Driving System (ADS) testing is essential to ensure the safety and reliability of autonomous vehicles (AVs) before deployment. However, existing techniques primarily foc…
Foundation Models for Autonomous Driving System: An Initial Roadmap
Xiongfei Wu, Mingfei Cheng, Xiaoning Ren +8
Recent advances in foundation models (FMs), including large language models (LLMs), vision-language models (VLMs), and world models, have opened new opportunities for autonomous dr…
MoDitector: Module-Directed Testing for Autonomous Driving Systems
Renzhi Wang, Mingfei Cheng, Xiaofei Xie +2
Testing Autonomous Driving Systems (ADS) is crucial for ensuring their safety, reliability, and performance. Despite numerous testing methods available that can generate diverse an…
DriveTester: A Unified Platform for Simulation-Based Autonomous Driving Testing
Mingfei Cheng, Yuan Zhou, Xiaofei Xie
Simulation-based testing plays a critical role in evaluating the safety and reliability of autonomous driving systems (ADSs). However, one of the key challenges in ADS testing is t…
A Comprehensive Study on Static Application Security Testing (SAST) Tools for Android
Jingyun Zhu, Kaixuan Li, Sen Chen +3
To identify security vulnerabilities in Android applications, numerous static application security testing (SAST) tools have been proposed. However, it poses significant challenges…
FT2Ra: A Fine-Tuning-Inspired Approach to Retrieval-Augmented Code Completion
Qi Guo, Xiaohong Li, Xiaofei Xie +6
The rise of code pre-trained models has significantly enhanced various coding tasks, such as code completion, and tools like GitHub Copilot. However, the substantial size of these…
ContrastRepair: Enhancing Conversation-Based Automated Program Repair via Contrastive Test Case Pairs
Jiaolong Kong, Mingfei Cheng, Xiaofei Xie +3
Automated Program Repair (APR) aims to automatically generate patches for rectifying software bugs. Recent strides in Large Language Models (LLM), such as ChatGPT, have yielded enc…