Development of a Programmed Generation of t-way Test cases Using an Improved Particle Swarm Optimization Strategy

Extensive testing is constrained by a lack of resources and time limitations. As a result, producing appropriate testing data in real-time is critical for advancing the entire application process. A search-based optimization technique has been used to create application testing data since 1992, and interest and action in this area had also recently increased. According to the study, modifying the t-way parametric interaction could indeed drastically reduce the amount of testing data. Based on this idea, many t-way test data procedures have already emerged over the past decade. According to the latest research, utilizing synthetic intelligence-based searching to start generating test data can yield near-optimal results. Acquiring the finest test data, on either hand, appears to be tricky. As a result, generating the biggest selection of testing data for a methodology is practically impossible. This study proposed a swarm smart exploring technique for trying to generate relatively close test records based on the review of recent research of legitimate diverse search-based optimal control methodologies. The results obtained are compared to those of other well-known techniques. According to experiment findings, the suggested technique is extremely fair in terms of test data dimension.