19 citations · 62 across the 19 of their papers we have counts for
7 papers · 1 filter
From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing
Linfeng Liang, Xiao Cheng, Tsong Yueh Chen +1
Simulation-based testing of autonomous driving systems (ADS) must uncover realistic and diverse failures in dense, heterogeneous traffic. However, existing search-based seeding met…
NeuroStrata: Harnessing Neurosymbolic Paradigms for Improved Design, Testability, and Verifiability of Autonomous CPS
Xi Zheng, Ziyang Li, Ivan Ruchkin +2
Autonomous cyber-physical systems (CPSs) leverage AI for perception, planning, and control but face trust and safety certification challenges due to inherent uncertainties. The neu…
Grey-Box Fuzzing in Constrained Ultra-Large Systems: Lessons for SE Community
Jiazhao Yu, Yanlun Tu, Zhanlei Zhang +5
Testing ultra-large microservices-based FinTech systems presents significant challenges, including restricted access to production environments, complex dependencies, and stringent…
Testing learning-enabled cyber-physical systems with Large-Language Models: A Formal Approach
Xi Zheng, Aloysius K. Mok, Ruzica Piskac +5
The integration of machine learning (ML) into cyber-physical systems (CPS) offers significant benefits, including enhanced efficiency, predictive capabilities, real-time responsive…
DSHGT: Dual-Supervisors Heterogeneous Graph Transformer -- A pioneer study of using heterogeneous graph learning for detecting software vulnerabilities
Tiehua Zhang, Rui Xu, Jianping Zhang +4
Vulnerability detection is a critical problem in software security and attracts growing attention both from academia and industry. Traditionally, software security is safeguarded b…
TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction
Yao Deng, Jiaohong Yao, Zhi Tu +3
Recent incidents with autonomous vehicles highlight the need for rigorous testing to ensure safety and robustness. Constructing test scenarios for autonomous driving systems (ADSs)…
A Declarative Metamorphic Testing Framework for Autonomous Driving
Yao Deng, Xi Zheng, Tianyi Zhang +4
Autonomous driving has gained much attention from both industry and academia. Currently, Deep Neural Networks (DNNs) are widely used for perception and control in autonomous drivin…