Search for Prioritized Test Cases in Multi-Objective Environment During Web Application Testing

Abstract

Regression testing is an expensive procedure that is implemented during maintenance phase of the Software Development Life Cycle of evolving software. During this process, test case prioritization is one of the strategies followed in which test cases are organized in a fashion so as to enhance efficiency in achieving some performance goal. During the process, there could be several aspects to be kept in mind due to resources constraints such as fault severity detected per unit of test cost, severity detection per test case execution, and execution time of test cases to detect all the faults. Keeping all such constraints in mind, the test case prioritization problem becomes a multi-objective problem where some of the objectives have to be maximized and the remaining ones minimized. In this study, experiments were performed on different versions of five web applications. The problem instance was found to vary from 5 $$\times $$ 5 test cases versus fault matrix, to 125 $$\times $$ 125 matrix. Random approach, 2-opt algorithm, improved 2-opt algorithm, greedy approach, additional greedy approach, Weighted Genetic Algorithm and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were applied to a generate prioritized test sequence which maximizes the Cost Cognizant Average Percentage of Fault Detection value, severity detection and minimizes test case execution cost to expose all the faults. The performances of these algorithms are compared, keeping these parameters in mind, and it is concluded that the performance of NSGA-II algorithm is better than that of all the other tested algorithms throughout all the experiments.