Coverage Based Test Case Prioritization Technique for Regression Testing

Regression testing to make sure the latest round of changes to the software has not adversely affected what it could do before. Unfortunately, there may be insufficient time and resources to execute all test cases during regression testing. In that situation, test case prioritization techniques will order the test cases based on certain constraints so that the most beneficial test cases may be executed first. Previous study on search algorithms for regression test case prioritization shows that the difference between the performance of Heuristics search algorithm (Additional Greedy and 2-Optimal Greedy) and metaheuristic search algorithm (Hill Climbing and Genetic algorithms) was not statistically significant. Due to computational complexity and space those algorithms will take little effort to implement and consumes reasonable time to prioritize the test cases. In this paper, we proposed new algorithm, which is computationally simple, reduction in time to implement. The proposed algorithm is assessed using two standard application Library Management Systems and Students Marks Analyzing System for the practicality of the proposed algorithm. The empirical studies shows that the proposed algorithm is significantly performed well.