Automated Software Test Data Generation
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This paper applies the Evolutionary Strategy (ES) metaheuristic to the automatic test data generation problem. The problem consists in creating automatically a set of input data to test a program. This is a required step in software development and a time consuming task in all software companies. We describe our proposal and study the influence of some parameters of the algorithm in the results. We use a benchmark of eleven programs that includes fundamental algorithms in computer science. Finally, we compare our ES with a Genetic Algorithm (GA), a well-known algorithm in this domain. The results show that the ES obtains in general better results than the GA for the benchmark used.