Abstract
The problem of computing Unique Input/Ouput sequences (UIOs) is NP-hard. Genetic algorithms (GAs) have been proven to be effective in providing good solutions for some NP-hard problems. In this work, we investigated the construction of UIOs using GAs. We defined a fitness function to guide the search of potential UIOs and introduce a DO NOT CARE character to improve the GA’s diversity. Experimental results suggest that, in a small system, the performance of the GA based approaches is no worse than that of random search while, in a more complex system, the GA based approaches outperform random search.
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© 2004 Springer-Verlag Berlin Heidelberg
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Guo, Q., Hierons, R.M., Harman, M., Derderian, K. (2004). Computing Unique Input/Output Sequences Using Genetic Algorithms. In: Petrenko, A., Ulrich, A. (eds) Formal Approaches to Software Testing. FATES 2003. Lecture Notes in Computer Science, vol 2931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24617-6_12
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DOI: https://doi.org/10.1007/978-3-540-24617-6_12
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