Combining Refinement of Parametric Models with Goal-Oriented Reduction of Dynamics

Stefan Haar 1 Juraj Kolčák 1, 2 Loïc Paulevé 3, 4
1 MEXICO - Modeling and Exploitation of Interaction and Concurrency
LSV - Laboratoire Spécification et Vérification [Cachan], ENS Cachan - École normale supérieure - Cachan, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8643
4 BioInfo - LRI - Bioinformatique (LRI)
LRI - Laboratoire de Recherche en Informatique
Abstract : Parametric models abstract part of the specification of dynamical models by integral parameters. They are for example used in computational systems biology, notably with parametric regulatory networks, which specify the global architecture (interactions) of the networks, while parameterising the precise rules for drawing the possible temporal evolutions of the states of the components. A key challenge is then to identify the discrete parameters corresponding to concrete models with desired dynamical properties. This paper addresses the restriction of the abstract execution of parametric regulatory (discrete) networks by the means of static analysis of reachability properties (goal states). Initially defined at the level of concrete parameterised models, the goal-oriented reduction of dynamics is lifted to parametric networks, and is proven to preserve all the minimal traces to the specified goal states. It results that one can jointly perform the refinement of parametric networks (restriction of domain of parameters) while reducing the necessary transitions to explore and preserving reachability properties of interest.
Type de document :
Communication dans un congrès
VMCAI 2019 - 20th International Conference on Verification, Model Checking, and Abstract Interpretation, Jan 2019, Lisbon, Portugal. 2019, 〈https://popl19.sigplan.org/track/VMCAI-2019〉
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Contributeur : Loïc Paulevé <>
Soumis le : vendredi 30 novembre 2018 - 09:39:52
Dernière modification le : dimanche 2 décembre 2018 - 01:10:18

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  • HAL Id : hal-01940174, version 1
  • ARXIV : 1811.12377

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Stefan Haar, Juraj Kolčák, Loïc Paulevé. Combining Refinement of Parametric Models with Goal-Oriented Reduction of Dynamics. VMCAI 2019 - 20th International Conference on Verification, Model Checking, and Abstract Interpretation, Jan 2019, Lisbon, Portugal. 2019, 〈https://popl19.sigplan.org/track/VMCAI-2019〉. 〈hal-01940174〉

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