Optimal control based regression test selection for service-oriented workflow applications

Abstract

Regression test selection problem is treated as an optimal control issue.Three rules are given to transform BPEL application into an universal BPEL form.Our approach can select fewer test cases to test BPEL applications effectively.We prove our optimal control strategy is safe under controlled regression testing. Regression test selection, which is well known as an effective technology to ensure the quality of modified BPEL applications, is regarded as an optimal control issue. The BPEL applications under test serves as a controlled object and the regression test selection strategy functions as the corresponding controller. The performance index is to select fewest test cases to test modified BPEL applications. In addition, a promising controller (regression test selection approach) should be safe, which means that it can select all test cases in which faults might be exposed in modified versions under controlled regression testing from the original test suite. However, existing safe controllers may rerun some test cases without exposing fault. In addition, the unique features (e.g., dead path elimination semantics, communication mechanism, multi-assignment etc.) of BPEL applications also raise enormous problems in regression test selection. To address these issues, we present in this paper a safe optimal controller for BPEL applications. Firstly, to handle the unique features mentioned above, we transform BPEL applications and their modified versions into universal BPEL forms. Secondly, For our optimal controller, BPEL program dependence graphs corresponding to the two universal BPEL forms are established. Finally, guided by behavioral differences between the two versions, we construct an optimal controller and select test cases to be rerun. By contrast with the previous approaches, our approach can eliminate some unnecessary test cases to be selected. We conducted experiments with 8 BPEL applications to compare our approach with other typical approaches. Experimental results show that the test cases selected using our approach are fewer than other approaches.