A Survey on Software Test Case Minimization

Abstract

Software testing consumes the most time and resource-intensive phase of software testing. Test case minimization techniques are used to reduce the test suite which in turn saves time and resources. The main purpose of test case minimization is to eliminate the ineffective test cases in a way that the remaining test cases satisfy all the requirements as before. Many techniques are used for test case minimization. The use of a convoluted neural net, a nature-inspired algorithm like fire algorithm, data mining technique, and coverage-based and hybrid techniques has been reviewed in this paper. In this study, a few of the most recent takes on test case minimization has been summarized and sorted depending on their approach. This is a survey paper that reviews the way each paper handled their problem, which dataset they used, their accuracy on the respective dataset, and the shortcomings.