A GENETIC ALGORITHM FOR REGRESSION TEST CASE PRIORITIZATION USING CODE COVERAGE
Arvinder Kaur, Shubhra Goyal
Abstract
Arvinder Kaur, Shubhra Goyal
Abstract
Abstract — Regression testing is a testing technique which is used to validate the modified software. The regression test suite is typically large and needs an intelligent method to choose those test cases which will detect maximum or all faults at the earliest. Many existing prioritization techniques arrange the test cases on the basis of code coverage with respect to older version of the modified software. In this approach, a new Genetic Algorithm to prioritize the regression test suite is introduced that will prioritize test cases on the basis of complete code coverage. The genetic algorithm would also automate the process of test case prioritization. The results representing the effectiveness of algorithms are presented with the help of an Average Percentage of Code Covered (APCC) metric.
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Abstract — Regression testing is a testing technique which is used to validate the modified software. The regression test suite is typically large and needs an intelligent method to choose those test cases which will detect maximum or all faults at the earliest. Many existing prioritization techniques arrange the test cases on the basis of code coverage with respect to older version of the modified software. In this approach, a new Genetic Algorithm to prioritize the regression test suite is introduced that will prioritize test cases on the basis of complete code coverage. The genetic algorithm would also automate the process of test case prioritization. The results representing the effectiveness of algorithms are presented with the help of an Average Percentage of Code Covered (APCC) metric.
Key concepts: Regression testing, Test suite, Computer science, Test Management Approach, Data mining, Test case, Risk-based testing, Code (set theory)