Automated regression test generation
Bogdan Korel, Ali M. Al-Yami
Abstract
Bogdan Korel, Ali M. Al-Yami
Abstract
Regression testing involves testing the modified program in order to establish the confidence in the modifications. Existing regression testing methods generate test cases to satisfy selected testing criteria in the hope that this process may reveal faults in the modified program. In this paper we present a novel approach of automated regression test generation in which all generated test cases uncover an error(s). This approach is used to test the common functionality of the original program and its modified version, i.e., it is used for programs whose functionality is unchanged after modifications. The goal in this approach is to identify test cases for which the original program and the modified program produce different outputs. If such a test is found, then this test uncovers an error. The problem of finding such a test case may be reduced to the problem of finding program input on which a selected statement is executed. As a result, existing methods of automated test data generation for white-box testing may be used to generate these tests. Our experiments have shown that our approach may improve the chances of finding software errors as compared to the existing methods of regression testing. The advantage of our approach is that it is fully automated and that all generated test cases reveal an error(s).
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Regression testing involves testing the modified program in order to establish the confidence in the modifications. Existing regression testing methods generate test cases to satisfy selected testing criteria in the hope that this process may reveal faults in the modified program. In this paper we present a novel approach of automated regression test generation in which all generated test cases uncover an error(s). This approach is used to test the common functionality of the original program and its modified version, i.e., it is used for programs whose functionality is unchanged after modifications. The goal in this approach is to identify test cases for which the original program and the modified program produce different outputs. If such a test is found, then this test uncovers an error. The problem of finding such a test case may be reduced to the problem of finding program input on which a selected statement is executed. As a result, existing methods of automated test data generation for white-box testing may be used to generate these tests. Our experiments have shown that our approach may improve the chances of finding software errors as compared to the existing methods of regression testing. The advantage of our approach is that it is fully automated and that all generated test cases reveal an error(s).
Key concepts: Regression testing, Test Management Approach, Computer science, Test script, Keyword-driven testing, Test (biology), White-box testing, Test case