Architecting Dependable Systems V
From ZULU to RERS: lessons learned in the ZULU challenge
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
Automata learning with automated alphabet abstraction refinement
VMCAI'11 Proceedings of the 12th international conference on Verification, model checking, and abstract interpretation
Automated inference of models for black box systems based on interface descriptions
ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: technologies for mastering change - Volume Part I
LearnLib tutorial: from finite automata to register interface programs
ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: technologies for mastering change - Volume Part I
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Although many of the software engineering activities can now be model-supported, the model is often missing in software development. We are interested in retrieving statemachine models from black-box software components. We assume that the details of the development process of such components (third-party software or COTS) are not available. To adequately support software engineering activities, we need to learn more complex models than simple automata. Our model is an extension of finite state machines that incorporates the notions of predicates and parameters on transitions. We argue that such a model can offer a suitable trade-off between expressivity of the model and complexity of model learning. We have been able to extend polynomial learning algorithms to extract such models in an incremental testing approach. In turn, the models can be used to derive tests or for component documentation.