Model checking performability properties

Haverkort, Boudewijn R.; Cloth, Lucia; Hermanns, Holger; Katoen, Joost-Pieter; Baier, Christel

doi:10.1109/dsn.2002.1028891

Cited by 50 publications

(48 citation statements)

References 24 publications

(26 reference statements)

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“…We write M |= Φ if the initial state of an MDP fulfils the PCTL state formula Φ. The reachability reward formula [10], [11] R m (♦ Φ) states that the expected accumulated reward until a state satisfying Φ is reached should meet the bound m for all schedulers.…”

Section: Probabilistic Ctlmentioning

confidence: 99%

Model Repair for Markov Decision Processes

Chen

Hahn

Han

et al. 2013

2013 International Symposium on Theoretical Aspects of Software Engineering

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Abstract-Markov decision processes (MDPs) are often used for modelling distributed systems with probabilistic failure or randomisation. We consider the problem of model repair for MDPs defined as follows: if the MDP fails to satisfy a property, we aim to find new values for the transition probabilities so that the property is guaranteed to hold, while at the same time the cost of repair is minimised. Because solving the MDP repair problem exactly is infeasible, in this paper we focus on approximate solution methods. We first formulate a region-based approach, which yields an interval in which the minimal repair cost is contained. As an alternative, we also consider samplingbased approaches, which are faster but unable to provide lower bounds on the repair cost. We have integrated both methods into the probabilistic model checker PRISM and demonstrated their usefulness in practice using a computer virus case study.

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Section: Probabilistic Ctlmentioning

confidence: 99%

Model Repair for Markov Decision Processes

Chen

Hahn

Han

et al. 2013

2013 International Symposium on Theoretical Aspects of Software Engineering

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“…Further work can consider an implementation of the proposed method (possibly exploiting existing DSPN tools), and the extension of CSL TA to allow for rewards [12]. We also plan to compare the DTA approach with the automatabased approach of Obal and Sanders [14].…”

Section: Resultsmentioning

confidence: 99%

CSL^TA: an Expressive Logic for Continuous-Time Markov Chains

Osogami

2007

Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)

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“…With regards to CTMCs, a number of extensions of CSL have been proposed in the literature, along with associated model checking algorithms. For example, [35] proposes an action based version of CSL; [31,9] introduce the logics CRL and CSRL which added support for reward-based properties [42]; and [44] augment CSL with random time-bounded until and random expected-time operators, respectively.…”

Section: Discussionmentioning

confidence: 99%

Stochastic Model Checking

Kwiatkowska

Norman

Parker

Lecture Notes in Computer Science

453

353

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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.

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Model checking performability properties

Abstract: Model checking has been introduced as an automated tech-

Cited by 50 publications

References 24 publications

Model Repair for Markov Decision Processes

Model Repair for Markov Decision Processes

CSL^TA: an Expressive Logic for Continuous-Time Markov Chains

Stochastic Model Checking

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