Test optimisation: an approach based on modified algorithm for software network. (8th May 2020)

• Record Type: Journal Article
• Authors: Khari, Manju; Kumar, Prabhat; Shrivastava, Gulshan
• Is Part Of: International journal of advanced intelligence paradigms. Volume 17:Number 3/4(2020)
• Page Start: 208
• Page End: 237
• Publication Date: 2020-05-08
• Subjects: genetic -- cuckoo search -- artificial bee -- test suite optimisation -- hybrid algorithm -- software network -- test data; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

Testing is an indispensable part of the software development life cycle. It is performed to improve the performance, quality, efficiency and reliability of the software. In this paper, three algorithms are implemented namely: genetic algorithm, cuckoo search algorithm, and artificial bee colony for the purpose of test suite optimisation and with the help of results obtained a novel algorithm will be proposed to enhance the result of optimisation. To test a system, suitable test cases are developed but these test cases need to be optimised, as executing all the test cases is a time-consuming process. An idea to reduce the number of test cases which in turn reduces the testing time and work of a software tester. In order to optimise test cases, nature-inspired algorithms are used as they provide the best optimisation techniques. Experimental results show that proposed algorithm generates better results as compared to the existing algorithms.