Sinossi
This book presents a comprehensive framework that revolutionizes software quality assurance by leveraging the power of artificial intelligence and machine learning. Through the innovative integration of ensemble learning techniques and intelligent optimization algorithms, this book offers practical solutions to two critical challenges: efficient test case generation and accurate code smell detection. The author masterfully combines theoretical foundations with real-world applications, introducing novel approaches such as combinatorial optimization with improved genetic algorithms and enhanced harmony search for regression testing. Whether you're a software engineer, quality assurance professional, or researcher, this book provides the tools and methodologies needed to dramatically improve testing efficiency while reducing costs. With detailed case studies, empirical evaluations, and clear implementation guidelines, readers will learn how to implement state-of-the-art testing strategies that adapt to the increasing demands of modern software development.
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Paperback. Condizione: new. Paperback. This book presents a comprehensive framework that revolutionizes software quality assurance by leveraging the power of artificial intelligence and machine learning. Through the innovative integration of ensemble learning techniques and intelligent optimization algorithms, this book offers practical solutions to two critical challenges: efficient test case generation and accurate code smell detection. The author masterfully combines theoretical foundations with real-world applications, introducing novel approaches such as combinatorial optimization with improved genetic algorithms and enhanced harmony search for regression testing. Whether you're a software engineer, quality assurance professional, or researcher, this book provides the tools and methodologies needed to dramatically improve testing efficiency while reducing costs. With detailed case studies, empirical evaluations, and clear implementation guidelines, readers will learn how to implement state-of-the-art testing strategies that adapt to the increasing demands of modern software development. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9786209154355
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Taschenbuch. Condizione: Neu. Software Testing based on Artificial Intelligence Technology | Yinglei Song | Taschenbuch | Englisch | 2025 | Scholars' Press | EAN 9786209154355 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Codice articolo 134327046
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Software Testing based on Artificial Intelligence Technology
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a comprehensive framework that revolutionizes software quality assurance by leveraging the power of artificial intelligence and machine learning. Through the innovative integration of ensemble learning techniques and intelligent optimization algorithms, this book offers practical solutions to two critical challenges: efficient test case generation and accurate code smell detection. The author masterfully combines theoretical foundations with real-world applications, introducing novel approaches such as combinatorial optimization with improved genetic algorithms and enhanced harmony search for regression testing. Whether you're a software engineer, quality assurance professional, or researcher, this book provides the tools and methodologies needed to dramatically improve testing efficiency while reducing costs. With detailed case studies, empirical evaluations, and clear implementation guidelines, readers will learn how to implement state-of-the-art testing strategies that adapt to the increasing demands of modern software development.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 260 pp. Englisch. Codice articolo 9786209154355
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