6 papers
Evaluating and Improving the Robustness of LiDAR Odometry and Localization Under Real-World Corruptions
Bo Yang, Tri Minh Triet Pham, Jinqiu Yang
LiDAR odometry and localization are two widely used and fundamental applications in robotic and autonomous driving systems. Although state-of-the-art (SOTA) systems achieve high ac…
BabelCoder: Agentic Code Translation with Specification Alignment
Fazle Rabbi, Soumit Kanti Saha, Tri Minh Triet Pham +2
As software systems evolve, developers increasingly work across multiple programming languages and often face the need to migrate code from one language to another. While automatic…
ADPerf: Investigating and Testing Performance in Autonomous Driving Systems
Tri Minh-Triet Pham, Diego Elias Costa, Weiyi Shang +1
Obstacle detection is crucial to the operation of autonomous driving systems, which rely on multiple sensors, such as cameras and LiDARs, combined with code logic and deep learning…
On the Robustness Evaluation of 3D Obstacle Detection Against Specifications in Autonomous Driving
Tri Minh Triet Pham, Bo Yang, Jinqiu Yang
Autonomous driving systems (ADSs) rely on real-time sensor data, such as cameras and LiDARs, for time-critical decisions using deep neural networks. The accuracy of these decisions…
Time to Retrain? Detecting Concept Drifts in Machine Learning Systems
Tri Minh Triet Pham, Karthikeyan Premkumar, Mohamed Naili +1
With the boom of machine learning (ML) techniques, software practitioners build ML systems to process the massive volume of streaming data for diverse software engineering tasks su…
Perception-Guided Fuzzing for Simulated Scenario-Based Testing of Autonomous Driving Systems
Tri Minh Triet Pham, Bo Yang, Jinqiu Yang
Autonomous Driving Systems (ADS) have made huge progress and started on-road testing or even commercializing trials. ADS are complex and difficult to test: they receive input data…