Bio-Inspired Gradient Genetic Optimization for Test Suite Generation - Ramasundaram, T; Sangeetha, V (International Journal of Computer Sciences and Engineering, 2019)
Software testing is an essential process during the software development process. Test suite generation process is employed to detect test cases with sources. Recently, many research works have been developed for automatically generate the software test suites. However, software testing is a time consuming and unable to obtain high coverage rate. In this paper, Gradient Advanced Genetic Parameter Control Based Test Suite Generation (GAGPC-TSG) technique is proposed. Based on the fitness value, the best test case is selected using roulette wheel selection. Later, the gradient approach is applied to obtain the optimal test case to generate the test suites for increasing the software quality. This enhances the better performance in terms of optimal test suite generation with minimum time and maximum fault coverage rate.