Abstract
We present a testing methodology to find suitable test suites in environments where the application of each test to the implementation under test (IUT) might be very expensive in terms of cost or time. The method is general in the sense that it keeps very low the dependence on the underlying model (e.g. finite state machines, timed automata, Java programs, etc). A genetic algorithm (GA) is used to find optimal test suites according to cost and distinguishability criteria.
Work partially supported by project TIN2009-14312-C02-01.
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Alonso, L.M., Rabanal, P., Rodríguez, I. (2011). A Preliminary General Testing Method Based on Genetic Algorithms. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_45
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DOI: https://doi.org/10.1007/978-3-642-21498-1_45
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