The rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …

Scarce and niche in the literature just a few years ago, the blockchain topic is now the main
subject in conference papers and books. However, the hype generated by the technology …

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 …

Mutation testing realizes the idea of using artificial defects to support testing activities.
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …

Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

Debugging software failures is still a painful, time consuming, and expensive process. For
instance, recent studies showed that debugging activities often account for about 50% of the …

Metamorphic testing is an approach to both test case generation and test result verification.
A central element is a set of metamorphic relations, which are necessary properties of the …

This paper provides a survey of the emerging area of Large Language Models (LLMs) for
Software Engineering (SE). It also sets out open research challenges for the application of …

Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

We introduce Sapienz, an approach to Android testing that uses multi-objective search-
based testing to automatically explore and optimise test sequences, minimising length, while …