Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises (Uncertainty, Computational Techniques, and Decision Intelligence)
Language: English
Published by Academic Press, 2022
- Softcover
- New
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Condition: New
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In English.
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- Title
- Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises (Uncertainty, Computational Techniques, and Decision Intelligence)
- Author
- Tahvili, Sahar; Hatvani, Leo
- Publisher
- Academic Press
- Publication year
- 2022
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0323919138
- ISBN 13
- 9780323919135
- Item weight
- 508 grams
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
"Synopsis" may belong to another edition of this title.
About the Author
Leo Hatvani is a Lecturer at Mälardalen University. Leo holds a Licentiate degree in the verification of embedded systems from Mälardalen University. His current research focuses on artificial intelligence (AI) and advanced methods for testing complex software-intensive systems. His teaching is focused on improving Industry 4.0 production processes and product development by integrating artificial intelligence, augmented and virtual reality. He is working closely with Mälardalen Industrial Technology Centre (MITC) which cooperates with a number of regional companies to introduce Industry 4.0 practices into Swedish industry.
"About the title" may belong to another edition of this title.
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