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31
On probabilistic model checking
, 1996
"... Abstract. This tutorial presents an overview of model checking for both discrete and continuous-time Markov chains (DTMCs and CTMCs). Model checking algorithms are given for verifying DTMCs and CTMCs against specifications written in probabilistic extensions of temporal logic, including quantitative ..."
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Cited by 107 (25 self)
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Abstract. This tutorial presents an overview of model checking for both discrete and continuous-time Markov chains (DTMCs and CTMCs). Model checking algorithms are given for verifying DTMCs and CTMCs against specifications written in probabilistic extensions of temporal logic, including quantitative properties with rewards. Example properties include the probability that a fault occurs and the expected number of faults in a given time period. We also describe the practical application of stochastic model checking with the probabilistic model checker PRISM by outlining the main features supported by PRISM and three real-world case studies: a probabilistic security protocol, dynamic power management and a biological pathway. 1
Probabilistic model checking of complex biological pathways
, 2006
"... Abstract. Probabilistic model checking is a formal verification technique that has been successfully applied to the analysis of systems from a broad range of domains, including security and communication protocols, distributed algorithms and power management. In this paper we illustrate its applicab ..."
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Cited by 94 (18 self)
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Abstract. Probabilistic model checking is a formal verification technique that has been successfully applied to the analysis of systems from a broad range of domains, including security and communication protocols, distributed algorithms and power management. In this paper we illustrate its applicability to a complex biological system: the FGF (Fibroblast Growth Factor) signalling pathway. We give a detailed description of how this case study can be modelled in the probabilistic model checker PRISM, discussing some of the issues that arise in doing so, and show how we can thus examine a rich selection of quantitative properties of this model. We present experimental results for the case study under several different scenarios and provide a detailed analysis, illustrating how this approach can be used to yield a better understanding of the dynamics of the pathway. 1
D.: Symmetry reduction for probabilistic model checking
- International Organization for Standardization. ISO Information Processing Systems - Data Communication High-Level Data Link Control Procedure - Frame Structure. IS 3309
, 2006
"... Abstract. We present an approach for applying symmetry reduction techniques to probabilistic model checking, a formal verification method for the quantitative analysis of systems with stochastic characteristics. We target systems with a set of non-trivial, but interchangeable, components such as tho ..."
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Cited by 45 (13 self)
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Abstract. We present an approach for applying symmetry reduction techniques to probabilistic model checking, a formal verification method for the quantitative analysis of systems with stochastic characteristics. We target systems with a set of non-trivial, but interchangeable, components such as those which commonly arise in randomised distributed algorithms or probabilistic communication protocols. We show, for three types of probabilistic models, that symmetry reduction, similarly to the non-probabilistic case, allows verification to instead be performed on a bisimilar quotient model which may be up to factorially smaller. We then propose an efficient algorithm for the construction of the quotient model using a symbolic implementation based on multi-terminal binary decision diagrams (MTBDDs) and, using four large case studies, demonstrate that this approach offers not only a dramatic increase in the size of probabilistic model which can be quantitatively analysed but also a significant decrease in the corresponding run-times. 1
Quantitative Verification: Models, Techniques and Tools
, 2007
"... Automated verification is a technique for establishing if certain properties, usually expressed in temporal logic, hold for a system model. The model can be defined using a high-level formalism or extracted directly from software using methods such as abstract interpretation. The verification procee ..."
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Cited by 35 (15 self)
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Automated verification is a technique for establishing if certain properties, usually expressed in temporal logic, hold for a system model. The model can be defined using a high-level formalism or extracted directly from software using methods such as abstract interpretation. The verification proceeds through exhaustive exploration of the state-transition graph of the model and is therefore more powerful than testing. Quantitative verification is an analogous technique for establishing quantitative properties of a system model, such as the probability of battery power dropping below minimum, the expected time for message delivery and the expected number of messages lost before protocol termination. Models analysed through this method are typically variants of Markov chains, annotated with costs and rewards that describe resources and their usage during execution. Properties are expressed in temporal logic extended with probabilistic and reward operators. Quantitative verification involves a combination of a traversal of the state-transition graph of the model and numerical computation. This paper gives a brief overview of current research in quantitative verification, concentrating on the potential of the method and outlining future challenges. The modelling approach is described and the usefulness of the methodology illustrated with an example of a real-world protocol standard – Bluetooth device discovery – that has been analysed using the PRISM model checker (www.prismmodelchecker.org).
Using Probabilistic Model Checking in Systems Biology
"... Probabilistic model checking is a formal verification frame-work for systems which exhibit stochastic behaviour. It has been successfully applied to a wide range of domains, includ-ing security and communication protocols, distributed algo-rithms and power management. In this paper we demon-strate i ..."
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Cited by 25 (0 self)
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Probabilistic model checking is a formal verification frame-work for systems which exhibit stochastic behaviour. It has been successfully applied to a wide range of domains, includ-ing security and communication protocols, distributed algo-rithms and power management. In this paper we demon-strate its applicability to the analysis of biological pathways and show how it can yield a better understanding of the dynamics of these systems. Through a case study of the MAP (Mitogen-Activated Protein) Kinase cascade, we ex-plain how biological pathways can be modelled in the prob-abilistic model checker PRISM and how this enables the analysis of a rich selection of quantitative properties. 1.
Probabilistic model checking of contention resolution in the IEEE 802.15.4 lowrate wireless personal area network protocol
- In Proc. 2nd Int. Symposium on Leveraging Applications of Formal Methods (IsoLA’06
, 2006
"... Abstract—The international standard IEEE 802.15.4 defines low-rate wireless personal area networks, a central communi-cation infrastructure of pervasive computing. In order to avoid conflicts caused by multiple devices transmitting at the same time, it uses a contention resolution algorithm based on ..."
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Cited by 13 (2 self)
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Abstract—The international standard IEEE 802.15.4 defines low-rate wireless personal area networks, a central communi-cation infrastructure of pervasive computing. In order to avoid conflicts caused by multiple devices transmitting at the same time, it uses a contention resolution algorithm based on randomised exponential backoff that is similar to the ones used in IEEE 802.3 for Ethernet and IEEE 802.11 for Wireless LAN. We model the protocol using probabilistic timed automata, a formalism in which both nondeterministic and probabilistic choice can be represented. The probabilistic timed automaton is transformed into a finite-state Markov decision process via a property-preserving integral-time semantics. Using the proba-bilistic model checker PRISM, we verify correctness properties, compare different operation modes of the protocol, and analyse performance and accuracy of different model abstractions. I.
Model Checking Meets Performance Evaluation
"... Markov chains are one of the most popular models for the evaluation of performance and dependability of information processing systems. To obtain performance measures, typically long-run or transient state probabilities of Markov chains are determined. Sometimes the Markov chain at hand is equipped ..."
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Cited by 7 (1 self)
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Markov chains are one of the most popular models for the evaluation of performance and dependability of information processing systems. To obtain performance measures, typically long-run or transient state probabilities of Markov chains are determined. Sometimes the Markov chain at hand is equipped with rewards and computations involve determining long-run or instantaneous reward probabilities.
Software Engineering Techniques for the Development of Systems of Systems
- In Foundations of Computer Software. Future Trends and Techniques for Development, volume 6028 of Lecture Notes in Computer Science
, 2010
"... Abstract. This paper investigates how existing software engineering techniques can be employed, adapted and integrated for the development of systems of systems. Starting from existing system-of-systems (SoS) studies, we identify computing paradigms and techniques that have the potential to help add ..."
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Cited by 6 (1 self)
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Abstract. This paper investigates how existing software engineering techniques can be employed, adapted and integrated for the development of systems of systems. Starting from existing system-of-systems (SoS) studies, we identify computing paradigms and techniques that have the potential to help address the challenges associated with SoS development, and propose an SoS development framework that combines these techniques in a novel way. This framework addresses the development of a class of IT systems of systems characterised by high variability in the types of interactions between their component systems, and by relatively small numbers of such interactions. We describe how the framework supports the dynamic, automated generation of the system interfaces required to achieve these interactions, and present a case study illustrating the development of a data-centre SoS using the new framework. 1
Exogenous Probabilistic Computation Tree Logic
"... Replace this file with prentcsmacro.sty for your meeting, or with entcsmacro.sty for your meeting. Both can be ..."
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Cited by 5 (1 self)
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Replace this file with prentcsmacro.sty for your meeting, or with entcsmacro.sty for your meeting. Both can be
Temporalization of probabilistic propositional logic
, 2008
"... In this paper we study several properties of the Exogenous Probabilistic Propositional Logic (EPPL), a logic for reasoning about probabilities, with the purpose of introducing a temporal version- Exogenous Probabilistic Linear Temporal Logic (EPLTL). In detail, we give a small model theorem for EPPL ..."
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Cited by 3 (2 self)
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In this paper we study several properties of the Exogenous Probabilistic Propositional Logic (EPPL), a logic for reasoning about probabilities, with the purpose of introducing a temporal version- Exogenous Probabilistic Linear Temporal Logic (EPLTL). In detail, we give a small model theorem for EPPL and introduce a satisfaction and a model checking algorithm for both EPPL and EPLTL. We are also able to provide a (weakly) complete calculus for EPLTL. Finally, we conclude by pointing out some future work. 1
