Model checking for infinite state systems using data abstraction, assumption-commitment style reasoning and theorem proving

Dingel, Juergen; Filkorn, Thomas

doi:10.1007/3-540-60045-0_40

Cited by 40 publications

(20 citation statements)

References 7 publications

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“…in [5][6][7][8][9][10]. These methods are, like ours, all based on proving the existence of some kind of 'mimicing' relation from concrete system models to abstract ones.…”

Section: Related Workmentioning

confidence: 99%

A proof of burns N-process mutual exclusion algorithm using abstraction

Jensen

Lynch

1998

Tools and Algorithms for the Construction and Analysis of Systems

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Abstract. Within the Input/Output Automata framework, we state and prove a general abstraction theorem giving conditions for preservation of safety properties from one automaton to another. We use our abstraction theorem to verify that Burns distributed mutual exclusion algorithm parameterized in the number of processes n satisfies the mutual exclusion property. The concrete n-process algorithm is abstracted by a simple 2-process algorithm which is property preserving with respect to the mutual exclusion property. The condition for property preservation is proved to be satisfied by use of the LP theorem prover with a minimum of user assistance, and the 2-process abstraction is automatically verified using the SPIN model checker.

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“…in [5][6][7][8][9][10]. These methods are, like ours, all based on proving the existence of some kind of 'mimicing' relation from concrete system models to abstract ones.…”

Section: Related Workmentioning

confidence: 99%

A proof of burns N-process mutual exclusion algorithm using abstraction

Jensen

Lynch

1998

Tools and Algorithms for the Construction and Analysis of Systems

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“…This means that each path starting in any product state 6 (s, q) consists of factor paths starting in q i that run through the factor structures D ϕi i . It follows that also each fair path through…”

Section: Model Checking On Product Structuresmentioning

confidence: 99%

“…CTL [1], LTL [2], and as a superset of both CTL * [3] are convenient means for specifying concurrent systems. In particular, efficient verification tools for CTL have become standard [4,5,6] and are already used in industrial applications to quickly detect design errors. While LTL and CTL * have exponential verification procedures, CTL can be checked in linear time w.r.t.…”

Section: Introductionmentioning

confidence: 99%

Model Checking on Product Structures

Schneider

1998

Formal Methods in Computer-Aided Design

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We present an algorithm for checking CTL formulas in Kripke structures with side conditions, where the side conditions define new variables in terms of path formulas. Given any CTL formula where the defined variables may occur, the presented algorithm will determine the set of states where the CTL * formula holds that is obtained by replacing each new variable defined by a side condition by its definition. The basic idea of our algorithm is to translate each side condition to a Kripke structure that encodes precisely the definition of the new variable. After that, we compute the products of these structures with the given structure and use a generalization of the well-known CTL model checking procedure. The presented model checking procedure can still be implemented as a symbolic model checking procedure (e.g. with BDDs). We moreover show how each CTL * model checking problem can be translated efficiently to a CTL model checking problem with side conditions, and hence show that the method can be used to construct efficient CTL * and LTL model checking procedures. Moreover, it is shown that for LTL model checking, we can still use standard CTL model checking procedures instead of our generalized version.

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“…As the state explosion problem is a major limitation for the applicability of model checking in real problems (due to their complexity and size), several techniques have been developed to cope with this issue. In particular, symbolic model checking [19,10] and abstraction [12,8] are the most used ones.…”

Section: Introductionmentioning

confidence: 99%

Model Checking RAISE Applicative Specifications

Perna

George²

2007

Fifth IEEE International Conference on Software Engineering and Formal Methods (SEFM 2007)

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Ensuring the correctness of a given software component has become a crucial aspect in Software Engineering and the Model Checking technique provides a fully automated way to achieve this goal. In particular, the usage of Model Checking in formal languages has been reinforced in the last decades given the fact that specifications provide an abstraction of the problem under study, supplying a model of the system of tractable size given the state explosion problem faced by the Model Checking technique.In this paper we focus on the main issues for adding Model Checking functionalities to the RAISE specification language and present the semantic foundations of our current approach for doing so. An outline of the main problems faced in the process and of the solutions to solve them are also presented.

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Model checking for infinite state systems using data abstraction, assumption-commitment style reasoning and theorem proving

Cited by 40 publications

References 7 publications

A proof of burns N-process mutual exclusion algorithm using abstraction

A proof of burns N-process mutual exclusion algorithm using abstraction

Model Checking on Product Structures

Model Checking RAISE Applicative Specifications

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