Automated software testing using a metaheuristic technique based on Tabu search

Abstract

The use of techniques for automating the generation of software test cases is very important as it can reduce the time and cost of this process. The latest methods for automatic generation of tests use metaheuristic search techniques, i.e. Genetic Algorithms and Simulated Annealing. There is a great deal of research into the use of Genetic Algorithms to obtain a specific coverage in software testing but there is none using the metaheuristic Tabu Search technique. In this paper, we explain how we have created an efficient testing technique that combines Tabu Search with Korel's chaining approach. Our technique automatically generates test data in order to obtain branch coverage in software testing.