Butterfly Algorithm Approach for Test Case Prioritization

Abstract

Regression testing is the costly, time-consuming and critical testing activity that guarantees the improvements made in code have not changed features already in use. After any code update, running the entire test suite is just an infeasible task due to time and effort constraints. To achieve the early fault detection objective, the test case prioritization technique encourages deciding on the test case execution sequence. The optimization of software testing is still an important task, as the average percentage of detected failures (APFD), the average percentage of Branch Coverage detection (APBCD), and output of time are unsatisfactory in priority test cases. In this paper, we had proposed the Butterfly algorithm for test case optimization. We use Butterfly Algorithm with a fitness function specified with a similitude-distance model to optimise the ordering of test cases. Three testing suites selected from the software testing case repository were experimented with within 3 benchmarking programmes. Our Test Case Prioritization technique (TCP) was seen well as current works with the Butterfly APFD Algorithm as the output matrix. Overall APFD results show Butterfly Algorithm being a successful competitor in TCP applications.