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: 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

《軟體測試過程優化的人工智慧方法：實例與練習》介紹了不同基於人工智慧的解決方案，以克服許多初始測試問題中的不確定性。本書將智能決策的概念作為一種多準則、多目標的工作呈現。該書提供了如何通過智能決策來管理各種不確定性的指南，可以幫助許多行業的專家以更高效的方式改善各種流程。

由於測試一個產品所需的測試用例數量可能很大（在工業界通常會創建超過10,000個測試用例），無特定順序地執行所有這些測試用例可能會影響測試執行的結果，因此本書填補了對於如何、為什麼以及為何的相關主題的全面資源的需求。

要了解更多關於愛思唯爾（Elsevier）系列《不確定性、計算技術和決策智能》的資訊，請訪問以下連結：https://www.elsevier.com/books-and-journals/book-series/uncertainty-computational-techniques-and-decision-intelligence