Selection of Regression Test Suite using Crow Search Algorithm

Abstract

Testing has been an inevitable activity in Software Development Life Cycle. In the current scenario, most of the software development remains evolutionary in nature where software is released in cycles, each cycle fulfilling the requirements of the customer on a priority basis. This evolutionary development of software also demands high maintenance in the form of retesting. This re-testing is called regression testing and literature reveals that it is a proven N-P hard problem that attracts the application of approximation algorithms such as meta-heuristics. In this paper, the authors explore and applied Crow Search Algorithm to solve the Test Suite Optimization problem by formulating it as Regression Test Case Selection problem to minimize the maintenance cost. The author's objective is to optimize the no. of test cases to re-execute to reduce the execution efforts & time. The performance of the proposed approach is compared with other adopted approaches with the help of statistical tests.