A method for rigorous design of reconfigurable systems

Madeira, Alexandre; Neves, Renato; Barbosa, Lu­ís Soares; Martins, Manuel A.

doi:10.1016/j.scico.2016.05.001

Cited by 10 publications

(5 citation statements)

References 83 publications

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“…Moreover, although M, w 3 ♦q, we can verify that M, w 1 ♦♦q since M, w 2 ♦q. Finally, we point out that the formula (p ∧ ¬p) is false in every world but M, w 4 (p ∧ ¬p). This holds because, by definition, (p ∧ ¬p) holds at w 4 if p ∧ ¬p is valid on each successor state of w 4 .…”

Section: Modal Logicmentioning

confidence: 75%

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Applying differential dynamic logic to reconfigurable biological networks

Figueiredo

Martins

Chaves

2017

Mathematical Biosciences

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. Applying differential dynamic logic to reconfigurable biological networks. Mathematical Biosciences, Elsevier, 2017Elsevier, , 291, pp.10 -20. 10.1016Elsevier, /j.mbs.2017 AbstractQualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system's global dynamics and the latter providing more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS).In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is Differential Dynamic Logic (dL), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how dL can be used as an alternative, or also as a complement to methods already used.

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Section: Modal Logicmentioning

confidence: 75%

“…This holds because, by definition, (p ∧ ¬p) holds at w 4 if p ∧ ¬p is valid on each successor state of w 4 . Since there is no sucessor state of w 4 , M, w 4 (p ∧ ¬p).…”

Section: Modal Logicmentioning

confidence: 99%

Applying differential dynamic logic to reconfigurable biological networks

Figueiredo

Martins

Chaves

2017

Mathematical Biosciences

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“…Dynamic networks of interactions similar to the ones arising in membrane budding are essentially discrete reconfigurable systems; hence, it is natural to formalize them as Kripke structures whose states/worlds correspond to network configurations (specific arrangements of organelles, proteins, cargo molecules, etc., at a given time) and whose transitions capture reconfigurations (like those occurring during budding or fission). This opens the possibility to use standard modal-logic formalisms as in [7,21,11,18,30], among other, to specify and reason about reconfigurations.…”

Section: Initiation Budding Fission Uncoating Fusionmentioning

confidence: 99%

“…The topic is duly receiving growing attention in the formal-methods literature, notably through new mathematical models as well as specification and reasoning tools based on modal and hybrid(ized) logics that explore the intrinsic connection between reconfigurability and Kripke structures (e.g., [21,18,8,10]). In their most basic form, hybrid logics enrich ordinary modal logics with nominalsdesignating states in Kripke structures -and a local-satisfaction operator that enables a change of perspective from the state under consideration to another state that is named (e.g., [1,4]).…”

Section: Introductionmentioning

confidence: 99%

Dynamic Reconfiguration via Typed Modalities

Ţuţu

Chiriţă²,

Fiadeiro

2021

Formal Methods

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Modern software systems are increasingly exhibiting dynamicreconfiguration features analogous to naturally occurring phenomena where the architecture of a complex changes dynamically, at run time, on account of interactions between its components. This has led to a renewed interest in modal logics for formal system development, building on the intuitive idea that system configurations can be regarded as local models of a Kripke structure, while reconfigurations are captured by accessibility relations. We contribute to this line of research by advancing a modal logic with varying quantification domains that employs typed modalities and dedicated modal operators to specify and reason about a new generation of Kripke structures, called dynamic networks of interactions, that account for the context of a system's dynamics, identifying which actants have triggered a reconfiguration and what are its outcomes. To illustrate the expressiveness of the formalism, we provide a specification of the biological process of membrane budding, which we then analyse using a sound and complete proof-by-translation method that links dynamic networks of interactions with partial first-order logic.

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“…Finally, it is worth noting that this work is framed in our long term research on demand driven generation of specification logics, parametric to the specificities of some classes of complex systems (e.g. [2,20,21]).…”

Section: Lemma 11 (Truth Lemma)mentioning

confidence: 99%

Adding Proof Calculi to Epistemic Logics with Structured Knowledge

Benevides

Madeira

Martins

2021

Fundamentals of Software Engineering

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Dynamic Epistemic Logic (DEL) is used in the analysis of a wide class of application scenarios involving multi-agents systems with local perceptions of information and knowledge. In its classical form, the knowledge of epistemic states is represented by sets of propositions. However, the complexity of the current systems, requires other richer structures, than sets of propositions, to represent knowledge on their epistemic states. Algebras, graphs or distributions are examples of useful structures for this end. Based on this observation, we introduced a parametric method to build dynamic epistemic logics on-demand, taking as parameter the specific knowledge representation framework (e.g., propositional, equational or even a modal logic) that better fits the problems in hand. In order to use the built logics in practices, tools support is needed. Based on this, we extended our previous method with a parametric construction of complete proof calculi. The complexity of the model checking and satisfiability problems for the achieved logics are provided.

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A method for rigorous design of reconfigurable systems

Cited by 10 publications

References 83 publications

Applying differential dynamic logic to reconfigurable biological networks

Applying differential dynamic logic to reconfigurable biological networks

Dynamic Reconfiguration via Typed Modalities

Adding Proof Calculi to Epistemic Logics with Structured Knowledge

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