Gravitational Bee Search Algorithm with Fuzzy Logic for Effective Test Suite Minimization and Prioritization

Objectives: Software testing is the significant part of software development and is essential to confirm the quality of the software. The test suites developed for this purpose can be used again and updated repeatedly as the software advances. Subsequently, novel test cases will be added to the test suite and because of that, the size of the test suite will become bigger. Moreover, the test suite becomes redundant. Thus executing/re-executing the large test suite consumes more time and also increases the cost of testing. Therefore, in order to minimize the cost and the time of testing, it is essential to minimize the test suite. Methods/Statistical Analysis: Thus, the focus of this paper is to minimize the test suite by discovering a group of test cases that gives the same or better coverage as the original test suite based on some condition. Finding: In this study, the minimization is achieved by using a Gravitational Bee Search (GBS) algorithm, this algorithm is derived by combining artificial bee colony and gravitational search algorithms. Then, the Fuzzy operation is applied for prioritization to achieve efficient test suite. The algorithm searches for the optimum solution by calculating fitness values using coverage information. The search process is repetitive until a reduced test suite is identified. Application/ Improvement: The proposed algorithm is applied on an online ticket booking system and the results shows that the proposed system is approximately 15% to 20% more efficient than the existing system respective to the number of test cases and execution time.