Abstract
Generating test data is computationally expensive. This paper improves a framework that addresses this issue by representing the test data generation problem as an optimisation problem and uses heuristics to help generate test cases. The paper considers the temporal constraints and behaviour of a certain class of (timed) finite state machines. A very simple fitness function is defined that can be used with several evolutionary search techniques and automated test case generation tools.
An extended version of this paper, including a case study, can be found in [1]. Research supported by the Spanish projects WEST/FAST (TIN2006-15578-C02-01) and MATES (CCG08-UCM/TIC-4124).
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Derderian, K., Merayo, M.G., Hierons, R.M., Núñez, M.: Aiding test case generation in temporally constrained state based systems using genetic algorithms (2009), http://kimba.mat.ucm.es/manolo/papers/aiding-extended.pdf
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© 2009 Springer-Verlag Berlin Heidelberg
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Derderian, K., Merayo, M.G., Hierons, R.M., Núñez, M. (2009). Aiding Test Case Generation in Temporally Constrained State Based Systems Using Genetic Algorithms. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_41
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DOI: https://doi.org/10.1007/978-3-642-02478-8_41
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-02478-8
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