Proposed Method of Seeding and Constraint in One-Parameter-At-a- Time Approach for t-way Testing

T -way testing has become a popular way to software testing since it can often deliver good error detection at a low cost, and the test case generation process is one of its biggest drawbacks. One difficulty in this field is the combinatorial explosion problem, which aims to discover the best final test suite that covers all possible combinations of interaction strength. Looking at this limitation, nowadays researchers are focusing more on t-way based strategies. As such, this research examines the present state-of-the-art and proposed an effective combinatorial t-way test case generation strategy that support seeding and constraint support based on One-Parameter-At-a-Time approach, as part of an effort to build an optimized strategy for paired testing. The performance of the proposed approach to achieve a minimal test suite size has been evaluated. The results have undergone statistical analysis using the Wilcoxon Rank and Friedman tests. The suggested approach, however, consistently produces outcomes that are competitive.