Comparative Analysis of Sine Cosine and Social Network Search-Based Algorithm for Software Test Redundancy Reduction Optimization

The User Acceptance Testing (UAT) is an important part of software development. It involves evaluating a software application or system from the user's perspective to validate its operation, usability, and compliance with real-world scenarios. In the UAT, there are often many cases where one requirement is covered by more than one test. Often termed as test redundancy reduction (TRR), this unnecessary test repetition will impact the overall budget. Addressing this issue as an optimization problem, many existing works adopts metaheuristic algorithms to eliminate redundancy. Acknowledging the fact that no single metaheuristic algorithm is superior than its counterparts as well as taking the opportunity to adopt recent algorithm, our work present a comparative study (i.e., solving the TRR problem) using two recently developed metaheuristic algorithms namely the Social Network Search Algorithm (SNS) and the Sine Cosine Algorithm (SCA). More precisely, our work intents to investigate the algorithms' performance in terms of test reduction percentage and execution time. Experimental results demonstrated mixed results. Using the same population size and iteration, SCA excels in term of execution time yet SNS excels in terms of test reduction percentage.