State Machine Inference in Testing Context with Long Counterexamples

Muhammad Naeem Irfan 1
1 VASCO
LIG - Laboratoire d'Informatique de Grenoble
Abstract : We are working on the techniques which iteratively learn the formal models from black box implementations by testing. The novelty of the approach addressed here is our processing of the long counterexamples. There is a possibility that the counterexamples generated by a counterexample generator include needless sub sequences. We address the techniques which are developed to avoid the impact of such unwanted sequences on the learning process. The gain of the proposed algorithm is confirmed by considering a comprehensive set of experiments on the finite sate machines.
Type de document :
Communication dans un congrès
Third International Conference on Software Testing, Verification and Validation, ICST 2010, 2010, Paris, France. IEEE Computer Society, pp.508-511, 2010, 〈10.1109/ICST.2010.68〉
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https://hal.inria.fr/hal-00953398
Contributeur : Catherine Oriat <>
Soumis le : vendredi 28 février 2014 - 11:46:39
Dernière modification le : jeudi 11 octobre 2018 - 08:48:04

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Muhammad Naeem Irfan. State Machine Inference in Testing Context with Long Counterexamples. Third International Conference on Software Testing, Verification and Validation, ICST 2010, 2010, Paris, France. IEEE Computer Society, pp.508-511, 2010, 〈10.1109/ICST.2010.68〉. 〈hal-00953398〉

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