(An) effective fault aware test case prioritization by incorporating a fault localization technique

Abstract

Regression testing is an expensive testing process used to make sure that the modified parts did not affect the existing ones. To reduce the cost of regression testing, testers may prioritize test cases according to given performance goals such as increasing the rate of fault detection. In order to maximize the rate of fault detection, researchers have proposed coverage-based test case prioritization techniques. Prior coverage-based test case prioritization techniques aimed to increase fault detection rates by ordering the test cases according to given coverage criteria. However, in practice, since detected faults are typically removed, test cases that already covered the previously executed areas might not perform as well as expected, irrespective of their coverage. In this case, the ordering of test cases based on coverage information might not be effective. In this thesis, we introduce a new test case prioritization approach that considers both coverage and historical fault information by incorporating fault localization technique. Using the historical fault detection information of test cases, our approach adjusts the priorities of fault-found test cases while maintaining test cases with high coverage in high priority. Our approach can reduce the total cost of executing entire test suite(s) and enables us to detect faults earlier in a testing process by improving the testing effectiveness compared to the prior coverage-based techniques.