Open AccessUtilization of Gravitational Search Algorithm for Combinatorial T-Way Testing
Author(s) -
Khin Maung Htay,
Rozmie Razif Othman,
Amiza Amir
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1755/1/012007
Subject(s) - cover (algebra) , computer science , algorithm , test suite , software , suite , point (geometry) , quality (philosophy) , software testing , combinatorial explosion , newton's law of universal gravitation , test case , gravitation , theoretical computer science , machine learning , mathematics , programming language , engineering , law , mechanical engineering , philosophy , physics , regression analysis , geometry , epistemology , combinatorics , classical mechanics , political science
Different techniques of software testing are adopted to deal with bugs found in the highly complicated multifunctional software. However, those techniques have difficulty detecting bugs effectively because most of the bugs are triggered by interaction failures between the input parameters and values in the system. Thus, combinatorial t-way testing strategies have come into existence to produce quality minimized test cases, as well as those test cases can cover all the necessary interactions of parameters once at the least. Besides, as t-way testing is considered as an NP-hard problem, new strategies are always welcomed in this research area in pursuit of the optimum test suite. The main point of this paper is to propose the concept of a type of artificial intelligence (AI) algorithm called gravitational search algorithm (GSA) for t-way interaction testing. GSA is a stochastic optimization algorithm inspired by Newton’s law of gravity and motion and has been widely applied to figure out optimal solutions to real-world issues.