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| Paper IPM / Computer Science / 10875 |
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Constraint automata are a semantic model for Reo modeling language. Testing correctness of mapping black-box components in Reo to constraint automata is an important problem in analyzing the semantic model of Reo. This testing requires a suite of test cases that cover the automaton states and transitions and also examine different paths. In this paper, Genetic Algorithm (GA) is employed to generate such suite of test cases. This test data generation is improved by Genetic Symbiosis Algorithm (GSA). The results show that GSA approach brings us a suite of test cases with full coverage of automata states and transitions and also diversity of examined paths.
Keywords: Constraint automata, finite-state machine testing, automatic test data generation, genetic algorithms, symbiotic evolutionary algorithms.
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