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  • Model-to-model transformations for efficient time-domain verification of concurrent models by NuSMV modules

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    Estivill-Castro421195-Published.pdf (835.5Kb)
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    Author(s)
    Carrillo, M
    Estivill-Castro, V
    Rosenblueth, DA
    Griffith University Author(s)
    Estivill-Castro, Vladimir
    Year published
    2020
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    Abstract
    We introduce and describe an algorithmic transformation from the formalism of arrangements of logic-labelled finite-state machines (LLFSMs) into NuSMV modules (and its implementation as a model-to-model ATL transformation from an Ecore meta-model to the NuSMV language). Our transformation benefits from using modules and integers of NuSMV to improve the efficiency in the construction and verification of the model. Moreover, we can handle predicates about time. Thus, we enable verification of LLFSMs in the time domain. Our transformation is a considerable improvement in efficiency. Compared with earlier transformation algorithms ...
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    We introduce and describe an algorithmic transformation from the formalism of arrangements of logic-labelled finite-state machines (LLFSMs) into NuSMV modules (and its implementation as a model-to-model ATL transformation from an Ecore meta-model to the NuSMV language). Our transformation benefits from using modules and integers of NuSMV to improve the efficiency in the construction and verification of the model. Moreover, we can handle predicates about time. Thus, we enable verification of LLFSMs in the time domain. Our transformation is a considerable improvement in efficiency. Compared with earlier transformation algorithms developed by us, the one presented here produces concise NuSMV files (in an example, 130,295 lines were reduced to 418). We thus show that it is possible to automatically translate arrangements of LLFSMs to concise models that can be efficiently and formally verified.
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    Conference Title
    MODELSWARD 2020 - Proceedings of the 8th International Conference on Model-Driven Engineering and Software Development
    DOI
    https://doi.org/10.5220/0008910202870298
    Copyright Statement
    © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International (CC BY-NC-ND 4.0) License, which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
    Subject
    Artificial intelligence
    Computational complexity and computability
    Data structures and algorithms
    Publication URI
    http://hdl.handle.net/10072/399471
    Collection
    • Conference outputs

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