On the performance of estimation of distribution algorithms applied to software testing

One of the most important issues in software testing is the generation of the input cases used during the test. Due to the expensive cost of this task., its automation has become a key aspect. An alternative to obtain this is evolutionary testing. The aim of evolutionary testing is the creation Of test data by means of combinatorial optimization search methods. A heuristic approach to the automatic generation of test cases is presented. The developed approach makes use of an emerging set of evolutionary algorithms called estimation of distribution If algorithms. The analysis of the experimental results obtained presents this set of optimization techniques (is a promising option for tackling this problem. More precisely, the performance of different estimation of distribution algorithms is evaluated and, a comparison with the results of previous works is carried out.