Software Testing based on Artificial Intelligence Technology

Yinglei Song

ISBN 10: 6209154352 / ISBN 13: 9786209154355

Published by Scholars' Press, 2025

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Seller Inventory # 9786209154355

Bibliographic Details

• Title: Software Testing based on Artificial Intelligence Technology
• Publisher: Scholars' Press
• Publication Date: 2025
• Language: English
• ISBN 10: 6209154352
• ISBN 13: 9786209154355
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 16D millimeters 220 millimeters width by 150 millimeters height by 16 millimeters depth
• Weight: 405 grams

About this title

Synopsis

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.