Flow Unfolding of Multi-clock Nets

Casu, Gianluca; Pinna, G.

doi:10.1007/978-3-319-07734-5_10

Cited by 9 publications

(8 citation statements)

References 21 publications

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“…Since the seminal work by Winskel [27] that shows a tight connection (via a chain of correflections) between (the category of) safe nets and (prime) event structures, a lot of effort has been made to associate different guises of Petri nets with the corresponding class of event structures (e.g., [4], [12], [6], [26] to name a few). Recently, event structures have been extended to account for reversible concurrent systems, namely a class of systems that have lately received lot of attention because of their applications in different fields [1], [16], including programming abstractions for reliable systems [8], [13], [10], program analysis and debugging [11], modelling bio-chemical simulations [9] and quantum computing [19].…”

Section: Introductionmentioning

confidence: 99%

A distributed operational view of Reversible Prime Event Structures

Melgratti

Mezzina

Pinna

2021

2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS)

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Reversible prime event structures extend the wellknown model of prime event structures to represent reversible computational processes. Essentially, they give abstract descriptions of processes capable of undoing computation steps. Since their introduction, event structures have played a pivotal role in connecting operational models (traditionally, Petri nets and process calculi) with denotational ones (algebraic domains). For this reason, there has been a lot of interest in linking different classes of operational models with different kinds of event structures. Hence, it is natural to ask which is the operational counterpart of reversible prime event structures. Such question has been previously addressed for a subclass of reversible prime event structures in which the interplay between causality and reversibility is restricted to the so-called causerespecting reversible structures. In this paper, we present an operational characterisation of the full-fledged model and show that reversible prime event structures correspond to a subclass of contextual Petri nets, called reversible causal nets. The distinctive feature of reversible causal nets is that causality is recovered from inhibitor arcs instead of the usual overlap between post and presets of transitions. In this way, we are able to operationally explain also out-of-causal order reversibility.

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Section: Introductionmentioning

confidence: 99%

A distributed operational view of Reversible Prime Event Structures

Melgratti

Mezzina

Pinna

2021

2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS)

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“…This indicates several directions for improving its computation (including the extraction of maximal configurations) in the particular case of biological interaction networks, such as the use of contextual Petri nets [2], merge processes [15], unravelings [4], and the use of the network topology and static analysis to prune non-necessary transitions and decompose the detection of attractors.…”

Section: Implementation and Experimental Resultsmentioning

confidence: 99%

Characterization of Reachable Attractors Using Petri Net Unfoldings

Chatain

Haar

Jezequel

et al. 2014

Computational Methods in Systems Biology

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Abstract. Attractors of network dynamics represent the long-term behaviours of the modelled system. Their characterization is therefore crucial for understanding the response and differentiation capabilities of a dynamical system. In the scope of qualitative models of interaction networks, the computation of attractors reachable from a given state of the network faces combinatorial issues due to the state space explosion. In this paper, we present a new algorithm that exploits the concurrency between transitions of parallel acting components in order to reduce the search space. The algorithm relies on Petri net unfoldings that can be used to compute a compact representation of the dynamics. We illustrate the applicability of the algorithm with Petri net models of cell signalling and regulation networks, Boolean and multi-valued. The proposed approach aims at being complementary to existing methods for deriving the attractors of Boolean models, while being generic since it applies to any safe Petri net.

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“…0 is (ε, ε), v 1 is (a * b, b), v 2 is (a + bc, b + ε), v 3 is (a * b, bd), v 4 is ((a + bc)(a + bc), bd + b + ε), v 5 is ((a * + bc)b, bdb) and v 6 is ((a + bc)(a + bc)(a + bc), bdbd + bd + b + ε) are those annotating the conditions shown in the Figure 17. For a discussion on how to obtain these annotations we refer to [28].…”

Section: Discussionmentioning

confidence: 99%

Spreading nets: A uniform approach to unfoldings

Pinna

Fabre

2020

Journal of Logical and Algebraic Methods in Programming

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This paper is devoted to the study of the notion of spread net. A spread net is a (safe) Petri nets where each place is annotated with some information, taken from a suitable information domain, about how such place can get marked. Spread nets generalize various kinds of nets used to represent the non sequential behaviours of a safe net, like unfoldings, merged processes or trellis processes. The spreading of a net may allow to produce more compact (partially unfolded) nets representing the non sequential behaviour of a net, depending on the chosen information domain. In particular in a spread net it is possible to merge not only conflicting runs, but also to partially refold time, as spread nets allow loops in time.

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Flow Unfolding of Multi-clock Nets

Cited by 9 publications

References 21 publications

A distributed operational view of Reversible Prime Event Structures

A distributed operational view of Reversible Prime Event Structures

Characterization of Reachable Attractors Using Petri Net Unfoldings

Spreading nets: A uniform approach to unfoldings

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