Test Cases Minimization Strategy Based on Flower Pollination Algorithm

Abstract

Exhaustive testing in software testing is hard to implement due to a huge number of test cases and time-consuming in order to find bugs. Hence, a test cases minimization strategy is an essential to obtain an optimize test cases and reduce time. The major objective of this study is to propose a new test case minimization strategy called Test Generator Flower Pollination Strategy (TGFP) based the Flower Pollination Algorithm (FPA). The analytical and experimental findings evaluate the performance of the proposed strategy with existing combinatorial testing strategies. The research findings that have been obtained from the evaluation indicated that TGFP able to reduce a large number of test cases. On the basis of the findings of this research, it can be concluded that the TGFP has the potential to optimize the number of test cases compared to others t-way strategies no matter is optimization based or non-optimization based.