Title: Applying genetic algorithm to optimise the software testing efficiency with Euclidean distance
Authors: Rijwan Khan; Mohd Amjad
Addresses: Department of Computer Science and Engineering, Faculty of Engineering, Jamia Millia Islamia, New Delhi, India ' Department of Computer Science and Engineering, Faculty of Engineering, Jamia Millia Islamia, New Delhi, India
Abstract: Software testing ensures that the developed software is error free and reliable for customer use. For verification and validation of software products, testing has been applied to these products in various software industries. So, before the delivery of the software to the customer, all the types of testing have been applied. In this paper, automatic test cases have been developed with the help of a genetic algorithm for data flow testing and these tests are divided into different groups using Euclidean distance. Elements of each group are applied to the data flow diagram of the program/software and all the du-paths are found, covering the given test suits. New test suits are generated with the help of the genetic algorithm to cover all du-paths.
Keywords: software testing; automatic test cases; data flow testing; genetic algorithm.
DOI: 10.1504/IJAIP.2022.125234
International Journal of Advanced Intelligence Paradigms, 2022 Vol.23 No.1/2, pp.72 - 88
Received: 21 Feb 2017
Accepted: 03 Jun 2017
Published online: 05 Sep 2022 *