Intelligent Automation (IA) in automobiles combines robotic process automation and artificial
intelligence, allowing digital transformation in autonomous vehicles. IA can completely …

Autonomous driving has shown great potential to reform modern transportation. Yet its
reliability and safety have drawn a lot of attention and concerns. Compared with traditional …

Safe deployment of self-driving cars (SDC) necessitates thorough simulated and in-field
testing. Most testing techniques consider virtualized SDCs within a simulation environment …

Deep Learning (DL) solutions are increasingly adopted, but how to test them remains a
major open research problem. Existing and new testing techniques have been proposed for …

Automated Driving Systems (ADS) have made great achievements in recent years thanks to
the efforts from both academia and industry. A typical ADS is composed of multiple modules …

Deep Learning (DL) has been successfully applied to a wide range of application domains,
including safety-critical ones. Several DL testing approaches have been recently proposed …

Automated online recognition of unexpected conditions is an indispensable component of
autonomous vehicles to ensure safety even in unknown and uncertain situations. In this …

Assessing the quality of Deep Learning (DL) systems is crucial, as they are increasingly
adopted in safety-critical domains. Researchers have proposed several input generation …

We report on the organization, challenges, and results of the tenth edition of the Java Unit
Testing Competition as well as the second edition of the Cyber-Physical Systems (CPS) …

Testing Autonomous Driving Systems (ADSs) is a critical task for ensuring the reliability and
safety of autonomous vehicles. Existing methods mainly focus on searching for safety …