“Artificial intelligence and Software Testing” is edited by Adam Leon Smith and has recently been published by the British Computer Society. The book covers both using Artificial Intelligence (AI) to test software and testing AI systems. The book will help testers who want to learn about AI and testing.
Rex Black writes in the introduction about how AI is a wave of change and that we need to test AI in order to learn if we can trust AI. Testing AI provides new challenges as AI changes its behaviour in response to testing, and we need to rethink many aspects of testing.
In the first chapter Adam Leon Smith writes about AI trustworthiness and quality. He writes about the importance of being able to trust AI, about quality problems such as understanding how an AI system optimises itself, and also gives useful examples.
Quality and bias are the subjects of the second chapter by James Davenport. The chapter is an exceptionally good explanation of the issues relating to bias in AI. The chapter covers the difference between bias and fairness and issues with bias in AI.The examples given in the chapter about bias in AI and in everyday life give a deeper picture of the issues relating to bias.
The fourth chapter is about testing machine learning (ML) systems. In this chapter Adam Leon Smith writes about the role of the tester, the nature of machine learning systems and what testing metrics and testing techniques are appropriate for ML systems. The role of a tester in ML is described in a way that a tester in a team that does not use AI can relate to. The examples of testing metrics and techniques are different to those in non AI projects and so are really interesting.
Jeremias Rößler writes about AI based test automation in the next chapter. He writes about the problems in using AI for test automation and also covers AI being used to generate unit tests and UI tests.
Ontologies for software testing are described by Joanna Isabelle Olszewska in the sixth chapter. She explains what ontologies are, how they relate to AI and gives examples of several ontologies for software testing.
In the seventh chapter Jonathan Wright describes a shift-right approach to testing called “digital twin testing” which he used when collaborating with MIT. This approach was used when Jonathan led the QA and testing efforts for the COVID Pathcheck Foundation.
Many testers are now thinking about how to use AI to assist testing and how to test and this book will help them. Reading this book is a great way to become better informed about AI and software testing. You can get your copy from: https://shop.bcs.org/store/221