Deep learning (DL) systems can make our life much easier, and thus are gaining more and
more attention from both academia and industry. Meanwhile, bugs in DL systems can be …

The rapid growth of applying Machine Learning (ML) in different domains, especially in
safety-critical areas, increases the need for reliable ML components, ie, a software …

Powered by advanced Artificial Intelligence (AI) techniques, conversational AI systems, such
as ChatGPT, and digital assistants like Siri, have been widely deployed in daily life …

As Deep Neural Networks (DNNs) are rapidly being adopted within large software systems,
software developers are increasingly required to design, train, and deploy such models into …

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 …

As Deep Learning (DL) systems are widely deployed for mission-critical applications,
debugging such systems becomes essential. Most existing works identify and repair …

The exponential growth of social media platforms such as Twitter and Facebook has
revolutionized textual communication and textual content publication in human society …

Graph Neural Networks (GNNs) have achieved promising performance in a variety of
practical applications. Similar to traditional DNNs, GNNs could exhibit incorrect behavior that …

Deep Learning (DL) components are routinely integrated into software systems that need to
perform complex tasks such as image or natural language processing. The adequacy of the …