Ontology-based Negative Selection Algorithm For Pairwise Testing

Abstract

Pairwise testing is one of the most widely used methods for testing combinations of parameters in software applications. The semantic relationships between parameters may not be taken into consideration by traditional pairwise testing methods, which may result in missing important test cases. It is the objective of this study to evaluate the possibility of improving software testing by combining combinatorial testing algorithms. The proposed technique uses the negative selection algorithm (NSA) approach to change detection and classify the problem domains. To reduce the number of test cases, the researcher combines the model developed using the ontology method for the semantic web with the NSA. In contrast, previous research used a variety of different types of model types when generating test cases. This method proposal proved effective in reducing the testing problem.