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This program is tentative and subject to change.

Fri 2 May 2025 14:15 - 14:30 at 215 - SE for AI with Quality 2

Recent advances in Deep Neural Networks (DNNs) and sensor technologies are enabling autonomous driving systems (ADSs) with an ever-increasing level of autonomy. However, assessing their dependability remains a critical concern. State-of-the-art ADS testing approaches modify the controllable attributes of a simulated driving environment until the ADS misbehaves. In such approaches, environment instances in which the ADS is successful are discarded, despite the possibility that they could contain hidden driving conditions in which the ADS may misbehave. In this paper, we present GenBo (GENerator of BOundary state pairs), a novel test generator for ADS testing. GenBo mutates the driving conditions of the ego vehicle (position, velocity and orientation), collected in a failure-free environment instance, and efficiently generates challenging driving conditions at the behavior boundary (i.e., where the model starts to misbehave) in the same environment instance. We use such boundary conditions to augment the initial training dataset and retrain the DNN model under test. Our evaluation results show that the retrained model has, on average, up to 3 _ higher success rate on a separate set of evaluation tracks with respect to the original DNN model.

This program is tentative and subject to change.

Fri 2 May

Displayed time zone: Eastern Time (US & Canada) change

14:00 - 15:30
SE for AI with Quality 2Journal-first Papers at 215
14:00
15m
Talk
Beyond Accuracy: An Empirical Study on Unit Testing in Open-source Deep Learning Projects
Journal-first Papers
Han Wang Monash University, Sijia Yu Jilin University, Chunyang Chen TU Munich, Burak Turhan University of Oulu, Xiaodong Zhu Jilin University
14:15
15m
Talk
Boundary State Generation for Testing and Improvement of Autonomous Driving Systems
Journal-first Papers
Matteo Biagiola Università della Svizzera italiana, Paolo Tonella USI Lugano
14:30
15m
Talk
D3: Differential Testing of Distributed Deep Learning with Model Generation
Journal-first Papers
Jiannan Wang Purdue University, Hung Viet Pham York University, Qi Li , Lin Tan Purdue University, Yu Guo Meta Inc., Adnan Aziz Meta Inc., Erik Meijer
14:45
15m
Talk
Evaluating the Impact of Flaky Simulators on Testing Autonomous Driving Systems
Journal-first Papers
Mohammad Hossein Amini University of Ottawa, Shervin Naseri University of Ottawa, Shiva Nejati University of Ottawa
15:00
15m
Talk
Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study
Journal-first Papers
Luca Giamattei Università di Napoli Federico II, Matteo Biagiola Università della Svizzera italiana, Roberto Pietrantuono Università di Napoli Federico II, Stefano Russo Università di Napoli Federico II, Paolo Tonella USI Lugano
15:15
15m
Talk
Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing
Journal-first Papers
Matteo Biagiola Università della Svizzera italiana, Andrea Stocco Technical University of Munich, fortiss, Vincenzo Riccio University of Udine, Paolo Tonella USI Lugano
Pre-print
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