Optimization Using Different Criterion for Test Case Selection in Regression Testing

Modification in the software can cause the breaking of the previously verified functionalities of the system, causing the regression faults. One of the regression testing approaches is to rerun existing test cases. But this leads potentially costly task. Cost minimization can be carried out by optimization of testing effort by executing only a selected subset of test cases that believed to have a better chance of revealing faults. This proposes an approach for selecting and ordering a predetermined number of test cases from existing test cases. These are then prioritized using a greedy algorithm that maximizes minimum coverage in an iterative manner. The proposed approach would provide more consistency compared to existing approaches. TheIndividual running times of the test cases and total time required for the approach is providing better results than the existing system