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Optimization of automated software testing using meta-heuristic techniques

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimization of automated software testing using meta-heuristic techniquesedited by Manju Khari ... [et al.].
other author:	Khari, Manju.
Published:	Cham :Springer International Publishing :2022.
Description:	x, 184 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computer softwareTesting
Online resource:	https://doi.org/10.1007/978-3-031-07297-0
ISBN:	9783031072970$q(electronic bk.)

Optimization of automated software testing using meta-heuristic techniques
Optimization of automated software testing using meta-heuristic techniques[electronic resource] /edited by Manju Khari ... [et al.]. - Cham :Springer International Publishing :2022. - x, 184 p. :ill., digital ;24 cm. - EAI/Springer innovations in communication and computing,2522-8609. - EAI/Springer innovations in communication and computing..

Introduction -- Testing Fundamentals -- Strategies and Methods For Test Cases -- Automated Testing Levels -- Polices and Plans for Testing -- Test Organization -- Controlling and Monitoring Testing Process -- Evaluating Automated Software Quality -- Defect Analysis and Prevention -- Optimization -- Security Testing -- Conclusion.

This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing. Supports the advancement in the artificial intelligence used in software development; Advances knowledge on artificial intelligence based metaheuristic approach in software testing; Encourages innovation in traditional software testing field using recent artificial intelligence.

ISBN: 9783031072970$q(electronic bk.)

Standard No.: 10.1007/978-3-031-07297-0doiSubjects--Topical Terms:

582127
Computer software
--Testing

LC Class. No.: QA76.76.T48 / O67 2022

Dewey Class. No.: 005.14

Optimization of automated software testing using meta-heuristic techniques
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505 0 $a Introduction -- Testing Fundamentals -- Strategies and Methods For Test Cases -- Automated Testing Levels -- Polices and Plans for Testing -- Test Organization -- Controlling and Monitoring Testing Process -- Evaluating Automated Software Quality -- Defect Analysis and Prevention -- Optimization -- Security Testing -- Conclusion.
520 $a This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing. Supports the advancement in the artificial intelligence used in software development; Advances knowledge on artificial intelligence based metaheuristic approach in software testing; Encourages innovation in traditional software testing field using recent artificial intelligence.
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