Total coverage based regression test case prioritization using genetic algorithm

Regression Testing is a test to ensure that a program that was changed is still working. Changes introduced to a software product often come with defects. Additional test cases are, this could reduce the main challenges of regression testing is test case prioritization. Time, effort and budget needed to retest the software. Former studies in test case prioritization confirm the benefits of prioritization techniques. Most prioritization techniques concern with choosing test cases based on their ability to cover more faults. Other techniques aim to maximize code coverage. Thus, the test cases selected should secure the total coverage to assure the adequacy of software testing. In this paper, we present an algorithm to prioritize test cases based on total coverage using a modified genetic algorithm. Its performance on the average percentage of condition covered and execution time are compared with five other approaches.