Most of the Genetic-Algorithm-based regression test prioritization ordered test cases by computing fitness value based on the number of affected faults in the coverage information using the same severity of faults even if a fault was executed by the previous test case and evaluate their studies using Average Percentage of the rate of Fault Detection (APFD) metric. The objective of this research is to integrate the idea of GA with object-oriented programs to aid automated regression test case prioritization of the selected test cases, by proposing a regression test case prioritization strategy for selected test cases of object-oriented programs based on genetic algorithm for effective OOP regression test case prioritization using reduction of fault severity to zero (0%) when a fault is executed by the preceding test case, and its tool support. Moreover, a comprehensive empirical study of ten object-oriented programs by the use of mutation analysis was conducted in term of efficiency and effectiveness of fault detection. The evidence of the efficiency and effectiveness of the proposed strategy were tested using experiment and statistical tests (p<0.05). Therefore, the strategy could be used as an efficient and effective OOP automatic regression tests prioritization strategy
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