Using Adaptive Sequences for Learning Non-Resettable FSMs

Roland Groz, Nicolas Bremond, Adenilso Simao
Proceedings of The 14th International Conference on Grammatical Inference 2018, PMLR 93:30-43, 2019.

Abstract

This paper proposes a new method to infer non-resettable Mealy machines based on the notions of adaptive homing and characterizing used in FSM testing. This method does not require any knowledge on the system inferred apart from its input set. It progressively extends an output query, and also avoids almost all equivalence queries. It is fast, and scales to machines that have hundreds of states. It outperforms in most respect previous algorithms, and can even compete with algorithms that assume a reset.

Cite this Paper

BibTeX
@InProceedings{pmlr-v93-groz19a, title = {Using Adaptive Sequences for Learning Non-Resettable FSMs}, author = {Groz, Roland and Bremond, Nicolas and Simao, Adenilso}, booktitle = {Proceedings of The 14th International Conference on Grammatical Inference 2018}, pages = {30--43}, year = {2019}, editor = {Unold, Olgierd and Dyrka, Witold and Wieczorek, Wojciech}, volume = {93}, series = {Proceedings of Machine Learning Research}, month = {feb}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v93/groz19a/groz19a.pdf}, url = {https://proceedings.mlr.press/v93/groz19a.html}, abstract = {This paper proposes a new method to infer non-resettable Mealy machines based on the notions of adaptive homing and characterizing used in FSM testing. This method does not require any knowledge on the system inferred apart from its input set. It progressively extends an output query, and also avoids almost all equivalence queries. It is fast, and scales to machines that have hundreds of states. It outperforms in most respect previous algorithms, and can even compete with algorithms that assume a reset.} }
Endnote
%0 Conference Paper %T Using Adaptive Sequences for Learning Non-Resettable FSMs %A Roland Groz %A Nicolas Bremond %A Adenilso Simao %B Proceedings of The 14th International Conference on Grammatical Inference 2018 %C Proceedings of Machine Learning Research %D 2019 %E Olgierd Unold %E Witold Dyrka %E Wojciech Wieczorek %F pmlr-v93-groz19a %I PMLR %P 30--43 %U https://proceedings.mlr.press/v93/groz19a.html %V 93 %X This paper proposes a new method to infer non-resettable Mealy machines based on the notions of adaptive homing and characterizing used in FSM testing. This method does not require any knowledge on the system inferred apart from its input set. It progressively extends an output query, and also avoids almost all equivalence queries. It is fast, and scales to machines that have hundreds of states. It outperforms in most respect previous algorithms, and can even compete with algorithms that assume a reset.
APA
Groz, R., Bremond, N. & Simao, A.. (2019). Using Adaptive Sequences for Learning Non-Resettable FSMs. Proceedings of The 14th International Conference on Grammatical Inference 2018, in Proceedings of Machine Learning Research 93:30-43 Available from https://proceedings.mlr.press/v93/groz19a.html.

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