Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises

Artificial Intelligence Methods for Optimization of the Software Testing Process provides practical examples and exercises to overcome uncertainty in initial testing problems. It presents intelligent decision-making as a multi-criteria, multi-objective undertaking to improve processes in various industries.

Format: Paperback / softback
Length: 230 pages
Publication date: 26 July 2022
Publisher: Elsevier Science & Technology

Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises delves into diverse AI-based solutions aimed at mitigating the uncertainty prevalent in initial testing challenges. The concept of intelligent decision-making is portrayed as a multifaceted and multi-objective endeavor. This comprehensive book offers guidelines on effectively managing various forms of uncertainty through intelligent decision-making, empowering subject matter experts across diverse industries to enhance various processes in a more streamlined and efficient manner.

Given the substantial number of required test cases for product testing, which often exceeds 10,000 in the industry, the sequential execution of all these test cases without a specific order can significantly influence the outcomes of the test execution. Consequently, this book serves as a valuable resource, addressing the need for a comprehensive exploration of the hows, whats, and whys related to uncertainty, computational techniques, and decision intelligence.

For further insights into Elseviers 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

Weight: 388g
Dimension: 151 x 226 x 19 (mm)
ISBN-13: 9780323919135