Test Case Optimization using Butterfly Optimization Algorithm

Abstract

Software cannot be release until unless it attains significant degree of confidence on quality parameters. In order to maintain the software quality, testing plays an important role. But this is a costly affair as it consumes almost 50 percent of the overall software development cost. The increasing competitiveness and ever updating technological change as well as customer requirements make regression testing a most important activity. So, regression testing is conducted before every release of the software which becomes expensive. Optimization of regression test suite is a way to reduce this higher cost. This paper proposes an efficient self adaptive butterfly optimization technique. The proposed approach is further utilized on regression test suite optimization problem to reduce the regression test suite size. Performance of proposed approach has been evaluated against Bat Search Optimization based approaches using fault detection as performance measures. Different tests are performed to analyze and validate the results. These results demonstrate the dominance of the proposed approach over the compared ones.