Abstract
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.
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Alba, E., Chicano, J.F. (2006). Software Testing with Evolutionary Strategies. In: Guelfi, N., Savidis, A. (eds) Rapid Integration of Software Engineering Techniques. RISE 2005. Lecture Notes in Computer Science, vol 3943. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751113_5
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DOI: https://doi.org/10.1007/11751113_5
Publisher Name: Springer, Berlin, Heidelberg
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