Learning regular sets from queries and counterexamples
Information and Computation
Formal Methods for Protocol Testing: A Detailed Study
IEEE Transactions on Software Engineering
On the learnability of infinitary regular sets
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MAS — an interactive synthesizer to support behavioral modelling in UML
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
FORTE XII / PSTV XIX '99 Proceedings of the IFIP TC6 WG6.1 Joint International Conference on Formal Description Techniques for Distributed Systems and Communication Protocols (FORTE XII) and Protocol Specification, Testing and Verification (PSTV XIX)
Inference of Finite Automata Using Homing Sequences
Machine Learning: From Theory to Applications - Cooperative Research at Siemens and MIT
EXPERIMENTAL EVALUATION OF FSM-BASED TESTING METHODS
SEFM '05 Proceedings of the Third IEEE International Conference on Software Engineering and Formal Methods
Efficient test-based model generation for legacy reactive systems
HLDVT '04 Proceedings of the High-Level Design Validation and Test Workshop, 2004. Ninth IEEE International
Testing Security Properties of Protocol Implementations - a Machine Learning Based Approach
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
FM '09 Proceedings of the 2nd World Congress on Formal Methods
Monitoring architectural properties in dynamic component-based systems
CBSE'07 Proceedings of the 10th international conference on Component-based software engineering
State Machine Inference in Testing Context with Long Counterexamples
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
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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Angluin's algorithm is a well known approach for learning black boxes as minimal deterministic finite automata in polynomial time. In order to infer finite state machines instead of automata, different variants of this algorithm have been proposed. These algorithms rely on two types of queries which can be asked to an oracle: output and equivalence queries. If the black box is not equivalent to the learnt model, the oracle replies with a counterexample. The complexity of these algorithms depends on the length of the counterexamples provided by the oracle. The aim of this paper is to compare the average practical complexity of three of these algorithms in the case of poor oracles, in particular when the counterexamples are constructed with random walks.