@article{Cassel:2016vg,
    Abstract = {We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.},
    Author = {Cassel, Sofia and Howar, Falk and Jonsson, Bengt and Steffen, Bernhard},
    File = {Active learning for extended finite state machines - 2016\_Article\_.pdf},
    ISBN = {1433-299X},
    Journal = {Formal Aspects of Computing},
    Number = {2},
    Pages = {233--263},
    Title = {Active learning for extended finite state machines},
    URL = {https://doi.org/10.1007/s00165-016-0355-5},
    Volume = {28},
    Year = {2016},
    bdsk-url-1 = {https://doi.org/10.1007/s00165-016-0355-5},
    da = {2016/04/01},
    date-added = {2021-04-06 15:16:32 +0200},
    date-modified = {2021-04-06 15:16:32 +0200},
    id = {Cassel2016},
    ty = {JOUR},
    doi = {10.1007/s00165-016-0355-5}
}

@article{Cassel:2016vg, Abstract = {We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.}, Author = {Cassel, Sofia and Howar, Falk and Jonsson, Bengt and Steffen, Bernhard}, File = {Active learning for extended finite state machines - 2016_Article_.pdf}, ISBN = {1433-299X}, Journal = {Formal Aspects of Computing}, Number = {2}, Pages = {233--263}, Title = {Active learning for extended finite state machines}, URL = {https://doi.org/10.1007/s00165-016-0355-5}, Volume = {28}, Year = {2016}, bdsk-url-1 = {https://doi.org/10.1007/s00165-016-0355-5}, da = {2016/04/01}, date-added = {2021-04-06 15:16:32 +0200}, date-modified = {2021-04-06 15:16:32 +0200}, id = {Cassel2016}, ty = {JOUR}, doi = {10.1007/s00165-016-0355-5} }