A tabu search algorithm for structural software testing

This paper presents a tabu search metaheuristic algorithm for the automatic generation of structural software tests. It is a novel work since tabu search is applied to the automation of the test generation task, whereas previous works have used other techniques such as genetic algorithms. The developed test generator has a cost function for intensifying the search and another for diversifying the search that is used when the intensification is not successful. It also combines the use of memory with a backtracking process to avoid getting stuck in local minima. Evaluation of the generator was performed using complex programs under test and large ranges for input variables. Results show that the developed generator is both effective and efficient.