A CTL* Model Checker for Petri Nets

Amparore, Elvio Gilberto; Donatelli, Susanna; Gallà, Francesco

doi:10.1007/978-3-030-51831-8_21

Cited by 5 publications

(4 citation statements)

References 23 publications

(21 reference statements)

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“…The tool accepts a CTL syntax ( Amparore, Donatelli & Gallà, 2020b ) that is more expressive than the minimal one in Definition 1, as it includes more boolean connectors, and the path operators (in the Future, for some state in the path) and (globally, for all states in the path). Since CTL formulae are written in textual mode in the tool, the symbols: &&, ||, !, ,>=, <=, == are used for ∧, ∨, ⫬ , ≥, ≤, =, leading to:…”

Section: Starmc: the Outer Viewmentioning

confidence: 99%

“…CTL properties are of practical interest, and CTL model checking has been extensively studied in the past. However, as pointed out in Amparore, Donatelli & Gallà (2020b) , very few CTL model checkers exist today, despite its usefulness in specifying both recurrent behaviours and possibility in the same property (something happening infinitely often and for all behaviour, a certain event/state is reachable), or to explicitly express fairness constraints. LTL can express both fairness constraints and recurrent behaviours, but this is not possible in CTL.…”

Section: Introductionmentioning

confidence: 99%

“…The tool basic principles and structure were first presented in a (demo) paper ( Amparore, Donatelli & Gallà, 2020b ): here we take a deeper, and at the same time broader, view on CTL model-checking and on its implementation in . We provide distinct logical and implementation views of the model-checker, thus separating the algorithms from their fully symbolic implementation.…”

Section: Introductionmentioning

confidence: 99%

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starMC: an automata based CTL* model checker

Amparore¹,

Donatelli²,

Gallà³

2022

PeerJ Computer Science

Self Cite

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Model-checking of temporal logic formulae is a widely used technique for the verification of systems. CTL$^*$ is a temporal logic that allows to consider an intermix of both branching behaviours (like in CTL) and linear behaviours (LTL), overcoming the limitations of LTL (that cannot express “possibility”) and CTL (cannot fully express fairness). Nevertheless CTL$^*$ model-checkers are uncommon. This paper presents (1) the algorithms for a fully symbolic automata-based approach for CTL$^*$, and (2) their implementation in the open-source tool starMC, a CTL$^*$ model checker for systems specified as Petri nets. Testing has been conducted on thousands of formulas over almost a hundred models. The experiments show that the fully symbolic automata-based approach of starMC can compute the set of states that satisfy a CTL$^*$ formula for very large models (non trivial formulas for state spaces larger than 10480 states are evaluated in less than a minute).

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Section: Starmc: the Outer Viewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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starMC: an automata based CTL* model checker

Amparore¹,

Donatelli²,

Gallà³

2022

PeerJ Computer Science

Self Cite

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show abstract

“…BDDs have especially found use in model checking, since they can efficiently represent both the set of states and the state-transition function [11]. Examples are the symbolic model checkers NuSMV [14,13], MCK [17], LTSmin [20], and MCMAS [26] and the recently envisioned symbolic model checking algorithms for CTL* in [2] and for CTLK in [19]. Hence, continuous research effort is devoted to improve the performance of this data structure.…”

Section: Introductionmentioning

confidence: 99%

Efficient Binary Decision Diagram Manipulation in External Memory

Sølvsten¹,

Pol²,

Jakobsen³

et al. 2021

Preprint

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We follow up on the idea of Lars Arge to rephrase the Reduce and Apply algorithms of Binary Decision Diagrams (BDDs) as iterative I/Oefficient algorithms. We identify multiple avenues to improve the performance of his proposed algorithms and extend the technique to other basic BDD algorithms.These algorithms are implemented in a new BDD library, named Adiar. We see very promising results when comparing the performance of Adiar with conventional BDD libraries that use recursive depth-first algorithms. For instances of about 50 GiB, our algorithms, using external memory, are only up to 3.9 times slower compared to Sylvan, exclusively using internal memory. Yet, our proposed techniques are able to obtain this performance at a fraction of the internal memory needed by Sylvan to function. Furthermore, with Adiar we are able to manipulate BDDs that outgrow main memory and so surpass the limits of the other BDD libraries.

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Adiar Binary Decision Diagrams in External Memory

Sølvsten

Pol

Jakobsen

et al. 2022

Tools and Algorithms for the Construction and Analysis of Systems

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We follow up on the idea of Lars Arge to rephrase the Reduce and Apply operations of Binary Decision Diagrams (BDDs) as iterative I/O-efficient algorithms. We identify multiple avenues to simplify and improve the performance of his proposed algorithms. Furthermore, we extend the technique to other common BDD operations, many of which are not derivable using Apply operations alone. We provide asymptotic improvements to the few procedures that can be derived using Apply.Our work has culminated in a BDD package named Adiar that is able to efficiently manipulate BDDs that outgrow main memory. This makes Adiar surpass the limits of conventional BDD packages that use recursive depth-first algorithms. It is able to do so while still achieving a satisfactory performance compared to other BDD packages: Adiar, in parts using the disk, is on instances larger than 9.5 GiB only 1.47 to 3.69 times slower compared to CUDD and Sylvan, exclusively using main memory. Yet, Adiar is able to obtain this performance at a fraction of the main memory needed by conventional BDD packages to function.

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A CTL* Model Checker for Petri Nets

Cited by 5 publications

References 23 publications

starMC: an automata based CTL* model checker

starMC: an automata based CTL* model checker

Efficient Binary Decision Diagram Manipulation in External Memory

Adiar Binary Decision Diagrams in External Memory

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