Abstract Context: A Machine Learning based System (MLS) is a software system including
one or more components that learn how to perform a task from a given data set. The …

Verification and validation (V&V) hold a significant position in the research and development
of automated vehicles (AVs). Current literature indicates that different V&V techniques have …

This paper provides a comprehensive survey of techniques for testing machine learning
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …

With the increasing adoption of Deep Learning (DL) for critical tasks, such as autonomous
driving, the evaluation of the quality of systems that rely on DL has become crucial. Once …

Deep Neural Networks (DNNs) are the core component of modern autonomous driving
systems. To date, it is still unrealistic that a DNN will generalize correctly to all driving …

With the recent advances of Deep Neural Networks (DNNs) in real-world applications, such
as Automated Driving Systems (ADS) for self-driving cars, ensuring the reliability and safety …

Autonomous, or self-driving, cars are emerging as the solution to several problems primarily
caused by humans on roads, such as accidents and traffic congestion. However, those …

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 …

As shown by recent studies, machine intelligence-enabled systems are vulnerable to test
cases resulting from either adversarial manipulation or natural distribution shifts. This has …

Automated Driving Systems (ADSs) have seen rapid progress in recent years. To ensure the
safety and reliability of these systems, extensive testings are being conducted before their …