هوش مصنوعی و تست نرم‌افزار: ساخت سیستم‌هایی که می‌توانید به آن‌ها اعتماد کنید

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. 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 Independent Press Awards 2023 - Technology 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.