Flower Pollination Algorithm for Test Case Prioritization in Regression Testing

Abstract

Flower Pollination Algorithm (FPA) is a significant addition made to Nature Inspired Metaheuristic Optimization Algorithms (NIMOA). It is inspired by the pollination process of flowering plants. In this research, FPA is used for Test Case Prioritization (TCP) in Regression Testing (RT). The algorithm uses code coverage of test cases as the input. The algorithm has no prior information of faults covered by the test cases. This study deals with prioritizing (ordering) the test cases in such a way that only those test cases are executed that covers maximum faults in minimum time of execution. For validation of the results Average Percentage of Fault Detected (APFD) metrics is used. APFD values for different ordering of test cases is calculated for three applications written in Java. The empirical results of APFD metrics for FPA order (TS1) and FPA order (TSp) are better as compared to Random Order of Original Test Suite (TSo) and Reverse Random Order of (TSo). Therefore, this paper states that FPA for TCP gives efficient results in RT.