Artificial Intelligence and Software Testing by Adam Leon Smith(.PDF)+

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File Size: 17.0 MB

Artificial Intelligence and Software Testing: Building systems you can trust by Adam Leon Smith, Rex Black, James Harold Davenport
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Overview: 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. Chapter 4 moves on to the complexities and challenges in testing Machine Learning systems, which make up the largest proportion of AI deployments today.
Genre: Non-Fiction > Tech & Devices

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