A Clustering-Bayesian Network Based Approach for Test Case Prioritization

Test case prioritization can effectively reduce the cost of regression testing by executing test cases with respect to their contributions to testing goals. Previous research has proved that the Bayesian Networks based technique which uses source code change information, software quality metrics and test coverage data has better performance than those methods merely depending on only one of the items above. Although the former Bayesian Networks based Test Case Prioritization (BNTCP) focusing on assessing the fault detection capability of each test case can utilize all three items above, it still has a deficiency that ignores the similarity between test cases. For mitigating this problem, this paper proposes a hybrid regression test case prioritization technique which aims to achieve better prioritization by incorporating code coverage based clustering approach with BNTCP to depress the impact of those similar test cases having common code coverage. Experiments on two Java projects with mutation faults and one Java project with hand-seeded faults have been conducted to evaluate the fault detection performance of the proposed approach against Additional Greedy approach, Bayesian Networks based approach (BNTCP), Bayesian Networks based approach with feedback (BNA) and code coverage based clustering approach. The experimental results showed that the proposed approach is promising.