A cost-effective test case selection and prioritization using hybrid battle royale-based remora optimization

Due to the reason, that many test cases in the software industry can be reused, selection and prioritizing techniques are essential during the regression and validation testing phases. However, time and project-specific limits must be observed. We present a hybrid optimization strategy to solve test case selection and prioritizing challenges in this research. The proposed method is the hybridization of Battle Royale Optimization (BRO) and Remora Optimization (RO) algorithm, which is named as hybrid Battle Royale-based Remora Optimization (HBR 2 O) algorithm. We focus on issues with pseudo-polynomial time complexity and low memory usage, which may be used to tackle problems like selection-prioritization and selection across collections of test suites or test cases. Dynamic programming optimization approaches require a large amount of memory, yet memory is limited. As a result of the decreased memory usage, the selection method includes a larger number of test cases. During the selection of software test cases, the proposed method’s effectiveness is validated using multiple state-of-the-art techniques, resulting in improved performance.