Artificial Intelligence and Software Testing: Building systems you can trust

✍ Scribed by Mr. Rex Black, James Davenport, Joanna Olszewska, Jeremias Rößler, Jonathon Wright, Adam Leon Smith (editor)

• Publisher: BCS, The Chartered Institute for IT
• Year: 2022
• Tongue: English
• Leaves: 194
• Category: Library

✦ Synopsis

WINNER Independent Press Awards 2023 - Category: Technology. AI presents a new paradigm in software development, 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, aimed at testing and quality management practitioners who want to understand more, covers trustworthiness of AI and the complexities of testing machine learning systems, before pivoting to how AI can be used itself in software test automation.

✦ Table of Contents

Front Cover
Half-Title Page
Bcs, The Chartered Institute For It
Title Page
Copyright Page
Contents
List of figures and tables
About the authors
Abbreviations
Glossary
Preface
1. Introduction
The challenges of testing AI
Summary
2. AI Trustworthiness and Quality
Trustworthiness
AI quality problems
A model for measuring AI quality
Regulation of AI quality
Summary
3. Quality and Bias
Consequences of the bias definition
Bias in everyday life
Unintended bias
Simpson’s paradox
Summary
4. Testing Machine Learning Systems
The role of a tester
The nature of ML
Testing metrics
Testing techniques
Testing AI-specific characteristics
Non-deterministic systems
Transparency, explainability and interpretability
Summary
5. AI-based Test Automation
Quality assurance
Testing versus test automation
AI in unit test automation
AI in UI level test automation
Applying AI to other tasks in software quality assurance
Evaluating tool support for testing
Tasks that will likely remain challenging for AI
Summary
6. Ontologies for Software Testing
About ontologies
Using ontologies for software testing
Trends in ontology-driven software testing
Summary
7. Shifting Right into the Metaverse with Digital Twin Testing
The shift-right approach to testing
Cognitive engineering principles
Digital twin concept in shifting right
Case study: helping the community stay safe during the pandemic
Case study: Smart City Data Exchange – testing in the metaverse
Shifting right into the metaverse
Evolution, over revolution
Summary
References
Index