Open AccessImplementation of Sine Cosine Algorithm (SCA) for Combinatorial Testing
Author(s) -
Jalal M. Altmemi,
Rozmie Razif Othman,
Robiah Ahmad,
Md. Asraf Ali
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/767/1/012009
Subject(s) - algorithm , test suite , computer science , sine , trigonometric functions , suite , software , minification , test strategy , test case , mathematics , machine learning , programming language , geometry , regression analysis , archaeology , history
Before being released to the market, software should be screened to ensure that the quality assurance measurement goals have been attained. To achieve this, one of the types of testing sorts is combinatorial testing (CT) aimed at discovering the faults that occur by interacting with the software. A minimization strategy for test cases is indeed important for optimizing test cases and reducing time. As NP hard (where NP is a non-deterministic polynomial) is the problem of generating the minimum test suite of combinatorial interaction testing (CIT). this paper discusses the implementation, and validation of an efficient strategy for t-way testing. The main contribution of the sine cosine algorithm SCA is to show that the strategy was sufficiently competitive as compared to other strategies in terms of the generated test suite size. Unlike most paper. The main contribution of SCA is to show the generation of test data for a high coverage strength (t < 12).