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Artificial Intelligence Methods in Software Testing

Author: Horst Bunke

Publisher: World Scientific

Published: 2004

Total Pages: 221

ISBN-13: 9812794751

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Artificial Intelligence Methods For Software Engineering

Author: Meir Kalech

Publisher: World Scientific

Published: 2021-06-15

Total Pages: 457

ISBN-13: 9811239932

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Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)

Artificial Intelligence Methods for Optimization of the Software Testing Process

Author: Sahar Tahvili

Publisher: Academic Press

Published: 2022-07-21

Total Pages: 232

ISBN-13: 0323912826

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Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises presents different AI-based solutions for overcoming the uncertainty found in many initial testing problems. The concept of intelligent decision making is presented as a multi-criteria, multi-objective undertaking. The book provides guidelines on how to manage diverse types of uncertainty with intelligent decision-making that can help subject matter experts in many industries improve various processes in a more efficient way. As the number of required test cases for testing a product can be large (in industry more than 10,000 test cases are usually created). Executing all these test cases without any particular order can impact the results of the test execution, hence this book fills the need for a comprehensive resource on the topics on the how's, what's and whys. To learn more about Elsevier’s Series, Uncertainty, Computational Techniques and Decision Intelligence, please visit this link: https://www.elsevier.com/books-and-journals/book-series/uncertainty-computational-techniques-and-decision-intelligence Presents one of the first empirical studies in the field, contrasting theoretical assumptions on innovations in a real industrial environment with a large set of use cases from developed and developing testing processes at various large industries Explores specific comparative methodologies, focusing on developed and developing AI-based solutions Serves as a guideline for conducting industrial research in the artificial intelligence and software testing domain Explains all proposed solutions through real industrial case studies

The Future of Software Quality Assurance

Author: Stephan Goericke

Publisher: Springer Nature

Published: 2019-11-19

Total Pages: 272

ISBN-13: 3030295095

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This open access book, published to mark the 15th anniversary of the International Software Quality Institute (iSQI), is intended to raise the profile of software testers and their profession. It gathers contributions by respected software testing experts in order to highlight the state of the art as well as future challenges and trends. In addition, it covers current and emerging technologies like test automation, DevOps, and artificial intelligence methodologies used for software testing, before taking a look into the future. The contributing authors answer questions like: "How is the profession of tester currently changing? What should testers be prepared for in the years to come, and what skills will the next generation need? What opportunities are available for further training today? What will testing look like in an agile world that is user-centered and fast-paced? What tasks will remain for testers once the most important processes are automated?" iSQI has been focused on the education and certification of software testers for fifteen years now, and in the process has contributed to improving the quality of software in many areas. The papers gathered here clearly reflect the numerous ways in which software quality assurance can play a critical role in various areas. Accordingly, the book will be of interest to both professional software testers and managers working in software testing or software quality assurance.

Artificial Intelligence Methods in Software Testing

Author: Mark Last

Publisher: World Scientific

Published: 2004-06-03

Total Pages: 220

ISBN-13: 9814482609

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An inadequate infrastructure for software testing is causing major losses to the world economy. The characteristics of software quality problems are quite similar to other tasks successfully tackled by artificial intelligence techniques. The aims of this book are to present state-of-the-art applications of artificial intelligence and data mining methods to quality assurance of complex software systems, and to encourage further research in this important and challenging area. Contents:Fuzzy Cause–Effect Models of Software Testing (W Pedrycz & G Vukovich)Black-Box Testing with Info-Fuzzy Networks (M Last & M Friedman)Automated GUI Regression Testing Using AI Planning (A M Memon)Test Set Generation and Reduction with Artificial Neural Networks (P Saraph et al.)Three-Group Software Quality Classification Modeling Using an Automated Reasoning Approach (T M Khoshgoftaar & N Seliya)Data Mining with Resampling in Software Metrics Databases (S Dick & A Kandel) Readership: Students, researchers and professionals in computer science, information systems, software testing and data mining. Keywords:Artificial Intelligence;Data Mining;Software Testing;System Testing;Software Quality;Software Engineering;Software MetricsKey Features:Coverage of novel methods for software testing and software quality assuranceIntroduction to state-of-the-art data mining models and techniquesAnalyses of new and promising application domains of artificial intelligence and data mining in software quality engineeringContributions from leading authors in the fields of software engineering and data mining

Human-Centered AI

Author: Ben Shneiderman

Publisher: Oxford University Press

Published: 2022

Total Pages: 390

ISBN-13: 0192845292

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The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.

Software Testing Fundamentals

Author: Marnie L. Hutcheson

Publisher: John Wiley & Sons

Published: 2003-04-07

Total Pages: 434

ISBN-13: 0471468444

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A highly anticipated book from a world-class authority who has trained on every continent and taught on many corporate campuses, from GTE to Microsoft First book publication of the two critically acclaimed and widely used testing methodologies developed by the author, known as MITs and S-curves, and more methods and metrics not previously available to the public Presents practical, hands-on testing skills that can be used everyday in real-life development tasks Includes three in-depth case studies that demonstrate how the tests are used Companion Web site includes sample worksheets, support materials, a discussion group for readers, and links to other resources

Artificial Intelligence and Software Engineering

Author: Derek Partridge

Publisher: Routledge

Published: 2013-04-11

Total Pages: 296

ISBN-13: 1136594531

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Managers, business owners, computer literate individuals, software developers, students, and researchers--all are looking for an understanding of artificial intelligence (AI) and what might be in the future. In this literate yet easy-to-read discussion, Derek Partridge explains what artificial intelligence can and cannot do, and what it holds for applications such as banking, financial services, and expert systems of all kinds. Topics include: the strengths and weaknesses of software development and engineering; machine learning and its promises and problems; expert systems and success stories; and practical software through artificial intelligence.

AI-Infused Test Automation: Revolutionizing Software Testing through Artificial Intelligence

Author: Anup Sahoo

Publisher: OrangeBooks Publication

Published: 2023-11-27

Total Pages: 348

ISBN-13:

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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.

Artificial Intelligence

Author: Melanie Mitchell

Publisher: Farrar, Straus and Giroux

Published: 2019-10-15

Total Pages: 336

ISBN-13: 0374715238

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Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.