A Brief Empirical Survey on Test Case Prioritization Techniques in Regression Testing

Software testing plays the most significant mechanism in improving the software system's quality. The software can be modified and validated by analyzing the new faults that gets evolved in the preceding tested code. Prior to the implementation phase, the early identification of faults, anomalies and bugs are detected and finally the software is moved to the maintenance stage. The anomalies can be effectively identified by the usage of accurate methodology. Here, regression testing is one of the most important methodologies in software testing. Any enhancement or updation can be implemented on the software and the changes do not have impact on remaining sections of the software because the test cases present in the regression testing are prioritized to reprocess the already available and new test cases in regression testing. The approaches available in test case prioritization are used to organize the test cases to maximize the effectiveness to attain their performance. The performance measure is the fault identification rate i.e. the rate of quickly analyzing the faults during the testing phase and enhanced fault identification rate imparts feedback quickly. Previous reports have proved that the test prioritization efficiently improves the fault detection rate. But there arises few questions related to the reports: a) Will the prioritization techniques are effective at target specified versions? b) What is the exact trade-off value that occurs between coarse and fine granularity techniques? c) Can the effectiveness get improved by collaborating the fault proneness measures into prioritization mechanisms? To answer the above statements, several methods are analyzed to improve the overall fault detection test suite rate and small improvements are performed by both fine and coarse granularity. This survey brings some of the effective measures in accosting the above questions.