Model Checking

Clarke, Edmund M.; Grumberg, Orna

doi:10.1007/978-3-642-61455-2_16

Cited by 316 publications

(461 citation statements)

References 31 publications

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“…Together with the previous TGTS, we specified a BaVeL model defining a set of properties for the verification of VisMODLE designs using Petri nets. The analysis is performed by calculating the coverability graph of the Petri net resulting from the previous transformation, and then applying model checking [6] on such graph in order to verify the system properties. These properties are expressed using Computational Tree Logic (CTL) [6].…”

Section: Analysis Of Vismodle By Petri Nets: An Example Of Visual Semmentioning

confidence: 99%

“…In this respect, a common approach is the use of hidden formal methods that provide analysis mechanisms for the system dynamic semantics. Formal methods [3,6] are techniques based on mathematics that help in the specification and verification of systems in order to obtain products with higher quality and fewer errors. One of their drawbacks is their difficulty, as they usually require experts in the given verification method.…”

Section: Introductionmentioning

confidence: 99%

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Supporting user-oriented analysis for multi-view domain-specific visual languages

Guerra

Lara

Malizia

et al. 2009

Information and Software Technology

248

149

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Esta es la versión de autor del artículo publicado en: This is an author produced version of a paper published in: AbstractThe integration of usable and flexible analysis support in modelling environments is a key success factor in Model-Driven Development. In this paradigm, models are the core asset from which code is automatically generated, and thus ensuring model correctness is a fundamental quality control activity. For this purpose, a common approach consists on transforming the system models into formal semantic domains for verification. However, if the analysis results are not shown in a proper way to the end-user (e.g. in terms of the original language) they may become useless.In this paper we present a novel DSVL called BaVeL that facilitates the flexible annotation of verification results obtained in semantic domains to different formats, including the context of the original language. BaVeL is used in combination with a consistency framework, providing support for all the verification life cycle: acquisition of additional input data, transformation of the system models into semantic domains, verification, and flexible annotation of analysis results.The approach has been empirically validated by its implementation in the AToM 3 meta-modelling tool, and tested with several DSVLs. In this paper we present a case study for the analysis of a notation in the area of Digital Libraries, where the analysis is performed by transformations into Petri nets and a process algebra.

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Section: Analysis Of Vismodle By Petri Nets: An Example Of Visual Semmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Supporting user-oriented analysis for multi-view domain-specific visual languages

Guerra

Lara

Malizia

et al. 2009

Information and Software Technology

248

149

View full text Add to dashboard Cite

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“…Since the specification logic we will use later in this paper is based on CTL, we give a brief introduction to CTL. More detailed information can be found in the literature [23]. CTL extends propositional logic by six temporal operators which allow to specify the temporal behavior of a system: A, E, X, F, G, U; A and E are path quantifiers that quantify over paths in a Kripke structure, whereas the others are linear-time operators that specify properties along a given path π.…”

Section: Model Checkingmentioning

confidence: 99%

Proactive Detection of Computer Worms Using Model Checking

Kinder

Katzenbeisser

Schallhart

et al. 2010

IEEE Trans. Dependable and Secure Comput.

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Abstract-Although recent estimates are speaking of 200,000 different viruses, worms, and Trojan horses, the majority of them are variants of previously existing malware. As these variants mostly differ in their binary representation rather than their functionality, they can be recognized by analyzing the program behavior, even though they are not covered by the signature databases of current antivirus tools. Proactive malware detectors mitigate this risk by detection procedures which use a single signature to detect whole classes of functionally related malware without signature updates. It is evident that the quality of proactive detection procedures depends on their ability to analyze the semantics of the binary. In this paper, we propose the use of model checking-a well established software verification technique-for proactive malware detection. We describe a tool which extracts an annotated control flow graph from the binary and automatically verifies it against a formal malware specification. To this end, we introduce the new specification language CTPL, which balances the high expressive power needed for malware signatures with efficient model checking algorithms. Our experiments demonstrate that our technique indeed is able to recognize variants of existing malware with a low risk of false positives.

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“…Different representations of ROBDDs (Reduced Order Binary Decision Diagrams) [20] are used to manipulate the state transition relations as diagrams and this allows model checkers to verify larger systems. Still, most model checkers face the state space explosion problems [14] . To be able to apply model checking to larger designs, state reduction techniques are used.…”

Section: Representing Bbds In High Order Logicmentioning

confidence: 99%

“…They are focused mostly on automatic decision procedures for solving the verification problem. Model checking is a state exploration based verification technique developed in the 1980s by Clarke and Emerson [14] and independently by Quielle and Sifakis [15] . In model checking, a state of the system under consideration is a snapshot of the system at certain time, given by the set of the variables values of that system at that time.…”

Section: Formal Verification Techniquesmentioning

confidence: 99%

On The Integration of Decision Diagrams in High Order Logic Based Theorem Provers:a Survey

Abed¹,

Mohamed²,

Sammane³

2007

J. of Computer Science

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This survey discuss approaches that integrate Decision Diagrams inside High Order Logic based Theorem provers. The approaches can be divided in two kinds, one is based on building a translation between model checker and theorem prover, the second is based on embedding the model checker algorithms inside the theorem prover. A comparison between both is discussed in detail. The paper also tries to answer which is the best decision graphs formalization for theorem provers as what is the optimized set of operations to efficiently manipulate the decision graphs inside theorem provers. Then, we contrast between them according to their efficiency, complexity and feasibility.

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Model Checking

Cited by 316 publications

References 31 publications

Supporting user-oriented analysis for multi-view domain-specific visual languages

Supporting user-oriented analysis for multi-view domain-specific visual languages

Proactive Detection of Computer Worms Using Model Checking

On The Integration of Decision Diagrams in High Order Logic Based Theorem Provers:a Survey

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