Generating Optimal Test Case Generation Using Shuffled Shepherd Flamingo Search Model

Software testing is considered as the basic procedure and it is genuinely supportive for several software developers. Developing an automatic test case generation helps the software professionals to conserve more time. In recent years, with the aim of saving cost and time, majority of the software is delivered without sufficient testing resulting in revenue loss. Simultaneously, the testing cost minimizes with the diminution of testing time. To overcome the above-mentioned limitations, this paper proposes a shuffled shepherd flamingo search ((SFS)-F-2) approach for an optimized and automatic test case generation with minimum execution time. The (SFS)-F-2 approach is an integration of two different metaheuristic algorithms namely the shuffled shepherd optimization algorithm and flamingo search optimization (FSO) algorithm. The significant intention of the proposed approach is to evaluate the efficiency and effectiveness thereby enhancing the generation of test cases. In addition to this, this paper also determines the efficiency of the proposed technique based on ATM operation with respect to total number of test case generations. The test cases of ATM are provided as an input to the proposed (SFS)-F-2 approach to determine an optimal test case. Finally, the experimental evaluations and comparative analysis are performed to determine the effectiveness of the proposed technique.