Название: Artificial Intelligence and Software Testing: Building systems you can trust
Автор: Adam Leon Smith, Rex Black, James Harold Davenport
Издательство: BCS Learning and Development Ltd
Год: 2022
Страниц: 194
Язык: английский
Формат: pdf, epub (true)
Размер: 17.0 MB

Artificial Intelligence (AI) presents a new paradigm in the development of software, representing the biggest change to how we think about quality and testing in decades. Many of the well known issues around AI, such as bias, manifest themselves as quality management problems. This book explores AI from that angle and is aimed at testing and quality management practitioners who want to understand more, starting with the relationship between AI and trustworthiness, the issue of bias, and the complexities of testing machine learning systems. The book then pivots to cover how AI can be used itself in software test automation, before exploring the more advanced topic of ontologies, and how they can be brought together with AI and testing. Finally, examples of shift-right testing and AIOps are considered.

This book is a journey through a number of topics relating to AI and quality, which is a hot topic for practitioners, as well as policy-makers and academics.
AI quality is different from conventional software quality. Chapter 2 of this book explains why that is, covering topics from bias to drift. We talk about these issues from a quality perspective, but many of them are of keen interest to practitioners who would not normally consider themselves interested in quality. For example, those who are more focused on the ethical application of AI, or the legal issues surrounding AI, are likely to worry about bias and drift.

One of the more complex issues is unintended bias, which can arise from different sources, and can have significant legal and societal effects. This is explained in detail in Chapter 3, from a conceptual as well as a mathematical perspective.

Chapter 4 moves on to the complexities and challenges in testing Machine Learning systems, which make up the largest proportion of AI deployments today. This chapter is particularly useful for practitioners planning to obtain the ISTQB Certified AI Tester qualification.

Then we will pivot in Chapter 5 to cover how AI can be used to support software testing processes. While this is almost the inverse of testing AI, many of the same issues – such as bias and drift – need to be considered.

Next, in Chapter 6, we explore the more advanced topic of ontologies. Ontologies are basically formal representations of knowledge that we have, in this case about testing. By establishing ontologies we can allow automated reasoning through AI to further support testing.

Finally, as the earlier chapters will have explained that AI is in need of constant monitoring for quality issues, we explore some examples of shift-right testing and AIOps in Chapter 7.

Contents:





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