AI-Infused Test Automation: Revolutionizing Software Testing through Artificial Intelligence is an enlightening book that explores the transformative power of AI in software testing. It covers a wide range of AI-driven techniques, tools, and practices, providing readers with a comprehensive understanding of how AI has revolutionized the field. The book inspires readers to embrace AI and leverage its capabilities to enhance test case generation, bug detection, performance testing, and test management. With AI, readers can achieve higher productivity, improved software quality, and enhanced customer satisfaction. This book catalyzes readers to embark on their AI-infused testing journey, driving innovation and shaping the future of software testing.

.....

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 well known issues around AI manifest 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.

This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing. ​Supports the advancement in the artificial intelligence used in software development; Advances knowledge on artificial intelligence based metaheuristic approach in software testing; Encourages innovation in traditional software testing field using recent artificial intelligence. ·

Software testing is expensive. Through up-front and recurring investment in labor and assets, organizations spend roughly half of their engineering budget on testing activities. The good news is that automated testing efforts have begun to improve through recent advances in AI and machine learning. With this report, you'll learn how AI-driven approaches are helping organizations overcome problems that traditional automated testing tools can't touch. Author Tariq King, chief scientist at test.ai, helps you examine several AI-driven solutions for software testing issues. You'll explore the application of AI and ML to functional, structural performance, and user design testing, and then dive into techniques for automating graphically intensive solutions such as video streaming and gaming applications. You'll learn the current benefits and limitations of AI-driven testing, available applications, and insights into the future of this new and emerging discipline. Learn the challenges and limitations of traditional approaches to software test automation Explore how AI is advancing the state of the art in automated functional, structural, performance, and user design testing in several application domains Examine the costs, benefits, and possible applications of AI-driven testing Look at ways that AI-driven test automation tools will evolve over the next decade.

Software testing is becoming increasingly important because more and more products are software-intensive. Cars, for example, contain more and more control software (ECUs) that are networked with each other. With new rail vehicles, software problems delay commissioning by months, even years, because the different components are not coordinated with each other. A timely system test would help, but there is a lack of time and resources. The functionality of the software is simply too great. So, you must automate. Automation is not only necessary for the execution of tests, but above all for the generation of suitable test cases. This is possible with Combinatory Logic, the Analytic Hierarchy Process (AHP), and Quality Function Deployment (QFD). When today’s cars use map services from the cloud, or their own sensors, for an Advanced Driving Assistance System (ADAS) to perform driving decisions; or when in the future an autonomous car meets another; or with truck platooning; or when adding a new, previously unknown device to an IoT orchestra, the original base system expands its functionality. Therefore, such an expanding system needs being retested before it can do decisions with the potential of affecting harm to humans or things, after each update, after each learning. This is Continuous Testing during operation; it supplements Continuous Delivery and Continuous Integration. Disruptive innovations in automotive require an equally disruptive new approach to testing of software-intense systems. This requires moving from once-upon-a-time testing before release to autonomous real-time software & systems testing during operations, with indications to users and suppliers about the actual state and testing results. This book explains the theory and the implementation approach for a framework for Autonomous Real-time Testing (ART) of a software-intense system while in operation.

Testing in the digital age brings a new vision on test engineering, using new quality attributes that tackle intelligent machines and a roadmap split up in fi ve hops. With everything digital there are more possibilities for test automation and piles of (test) data growing out of control. Working together with robots (cobotics), using artifi cial intelligence in testing and eventually predict the occurrence of defects brings your testing to the digital age. We have interviewed companies on their view of digital testing. A glossary brings an extensive list of terms that supports you in all your test communications.