Learning EFSM Models with Registers in Guards
<|reference_start|>Learning EFSM Models with Registers in Guards: This paper presents an active inference method for Extended Finite State Machines, where inputs and outputs are parametrized, and transitions can be conditioned by guards involving input parameters and internal variables called registers. The method applies to (software) systems that cannot be reset, so it learns an EFSM model of the system on a single trace.<|reference_end|>
@article{vega2024learning,
    title={Learning EFSM Models with Registers in Guards},
    author={Germ'an Vega, Roland Groz, Catherine Oriat, Michael Foster, Neil
  Walkinshaw, Adenilso Sim~ao},
    journal={arXiv preprint arXiv:2406.07040},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.07040},
    primaryClass={cs.FL}
}