1 citations · 1 across the 6 of their papers we have counts for
8 papers
UAMTERS: Uncertainty-Aware Mutation Analysis for DL-enabled Robotic Software
Chengjie Lu, Jiahui Wu, Shaukat Ali +5
Self-adaptive robots adjust their behaviors in response to unpredictable environmental changes. These robots often incorporate deep learning (DL) components into their software to…
A Tool for Benchmarking Large Language Models' Robustness in Assessing the Realism of Driving Scenarios
Jiahui Wu, Chengjie Lu, Aitor Arrieta +1
In recent years, autonomous driving systems have made significant progress, yet ensuring their safety remains a key challenge. To this end, scenario-based testing offers a practica…
Vision Language Model-based Testing of Industrial Autonomous Mobile Robots
Jiahui Wu, Chengjie Lu, Aitor Arrieta +2
PAL Robotics, in Spain, builds a variety of Autonomous Mobile Robots (AMRs), which are deployed in diverse environments (e.g., warehouses, retail spaces, and offices), where they w…
Foundation Models for Software Engineering of Cyber-Physical Systems: the Road Ahead
Chengjie Lu, Pablo Valle, Jiahui Wu +4
Foundation Models (FMs), particularly Large Language Models (LLMs), are increasingly used to support various software engineering activities (e.g., coding and testing). Their adopt…
Reinforcement Learning for Testing Interdependent Requirements in Autonomous Vehicles: An Empirical Study
Jiahui Wu, Chengjie Lu, Aitor Arrieta +1
Autonomous vehicles (AVs) make driving decisions without humans, making dependability assurance critical. Scenario-based testing is widely used to evaluate AVs under diverse condit…
Assessing the Uncertainty and Robustness of the Laptop Refurbishing Software
Chengjie Lu, Jiahui Wu, Shaukat Ali +1
Refurbishing laptops extends their lives while contributing to reducing electronic waste, which promotes building a sustainable future. To this end, the Danish Technological Instit…
Reality Bites: Assessing the Realism of Driving Scenarios with Large Language Models
Jiahui Wu, Chengjie Lu, Aitor Arrieta +2
Large Language Models (LLMs) are demonstrating outstanding potential for tasks such as text generation, summarization, and classification. Given that such models are trained on a h…
Uncertainty-Aware Test Prioritization: Approaches and Empirical Evaluation
Man Zhang, Jiahui Wu, Shaukat Ali +1
Complex software systems, e.g., Cyber-Physical Systems (CPSs), interact with the real world; thus, they often behave unexpectedly in uncertain environments. Testing such systems is…