FIG: The Finite Improbability Generator

Budde, Carlos E.

doi:10.1007/978-3-030-45190-5_27

Cited by 6 publications

(11 citation statements)

References 28 publications

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“…Storm produces exact results through model checking, requiring the full state-space, and does not support repairs. Other tools for rare event simulation of automata include Plasma Lab [12], where the user must manually parameterise the model, and [2] and modes [3], which implement a res method other than IS, less suited to analyse dfts.…”

Section: Related Workmentioning

confidence: 99%

“…Simulation runs are sampled, in parallel on multi-core systems, until a specified time bound or simulation number is reached, or a desired relative or absolute estimated error is reached. Results are presented as (by default) 95% confidence intervals (cis) 2 . is released under the GPLv3, and is cross-platform due to its implementation in Java, without run-time dependencies.…”

Section: Dftresmentioning

confidence: 99%

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The Dynamic Fault Tree Rare Event Simulator

Budde

Ruijters²,

Stoelinga

2020

Lecture Notes in Computer Science

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The dynamic-fault-tree rare event simulator, DFTRES, is a statistical model checker for dynamic fault trees (DFTs), supporting the analysis of highly dependable systems, e.g. with unavailability or unreliability under 10 −30 . To efficiently estimate such low probabilities, we apply the Path-ZVA algorithm to implement Importance Sampling with minimal user input. Calculation speed is further improved by selective automata composition and bisimulation reduction. DFTRES reads DFTs in the Galileo or JANI textual formats. The tool is written in Java 11 with multi-platform support, and it is released under the GPLv3. In this paper we describe the architecture, setup, and input language of DFTRES, and showcase its accurate estimation of dependability metrics of (resilient) repairable DFTs from the FFORT benchmark suite.

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Section: Related Workmentioning

confidence: 99%

Section: Dftresmentioning

confidence: 99%

The Dynamic Fault Tree Rare Event Simulator

Budde

Ruijters²,

Stoelinga

2020

Lecture Notes in Computer Science

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“…RES has garnered the interest of mathematicians and computer scientists alike. The scientific outcomes range from theoretical studies of a RES technique's limit behaviour and optimality [8,14,16] over experimental validation on Matlab studies or ad-hoc implementations [10,11,19] to application reports using larger case studies [5,12,18] as well as automated tools [4,6,15,18] that accept a loss of optimality in exchange for practicality.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we demonstrate our replication of the results of [19,21], where replication "means that an independent group can obtain the same result using artifacts which they develop completely independently" in the ACM terminology [1]. To this end, we implemented Restart with prolonged retrials (Restart-P) in the FIG rare event simulator [4] and the modes statistical model checker [7] of the Modest Toolset [13]. We recreated the models in the IOSA and Modest languages, and ran experiments following the original setup.…”

Section: Introductionmentioning

confidence: 99%

Replicating $$\textsc {Restart}$$ with Prolonged Retrials: An Experimental Report

Budde

Hartmanns

2021

Tools and Algorithms for the Construction and Analysis of Systems

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Statistical model checking uses Monte Carlo simulation to analyse stochastic formal models. It avoids state space explosion, but requires rare event simulation techniques to efficiently estimate very low probabilities. One such technique is $$\textsc {Restart}$$ R E S T A R T . Villén-Altamirano recently showed—by way of a theoretical study and ad-hoc implementation—that a generalisation of $$\textsc {Restart}$$ R E S T A R T to prolonged retrials offers improved performance. In this paper, we demonstrate our independent replication of the original experimental results. We implemented $$\textsc {Restart}$$ R E S T A R T with prolonged retrials in the and tools, and apply them to the models used originally. To do so, we had to resolve ambiguities in the original work, and refine our setup multiple times. We ultimately confirm the previous results, but our experience also highlights the need for precise documentation of experiments to enable replicability in computer science.

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“…Furthermore, our approach is compositional and guarantees to deliver (weakly) deterministic IOSA models, hence amenable to discrete event simulation. This enables its analysis via the statistical model checker FIG [13] which specialises in rare event simulation. Our results provide the theoretical foundations on which the tool chain from [14] is based, where they were used for efficient dependability analyses of highly reliable systems.…”

Section: Introductionmentioning

confidence: 99%

A compositional semantics for Repairable Fault Trees with general distributions

Monti¹,

Budde²,

D’Argenio³

EPiC Series in Computing

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Fault Tree Analysis (FTA) is a prominent technique in industrial and scientific risk assessment. Repairable Fault Trees (RFT) enhance the classical Fault Tree (FT) model by introducing the possibility to describe complex dependent repairs of system components. Usual frameworks for analyzing FTs such as BDD, SBDD, and Markov chains fail to assess the desired properties over RFT complex models, either because these become too large, or due to cyclic behaviour introduced by dependent repairs. Simulation is another way to carry out this kind of analysis. In this paper we review the RFT model with Repair Boxes as introduced by Daniele Codetta-Raiteri. We present compositional semantics for this model in terms of Input/Output Stochastic Automata, which allows for the modelling of events occurring according to general continuous distribution. Moreover, we prove that the semantics generates (weakly) deterministic models, hence suitable for discrete event simulation, and prominently for rare event simulation using the FIG tool.

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FIG: The Finite Improbability Generator

Cited by 6 publications

References 28 publications

The Dynamic Fault Tree Rare Event Simulator

The Dynamic Fault Tree Rare Event Simulator

Replicating $$\textsc {Restart}$$ with Prolonged Retrials: An Experimental Report

A compositional semantics for Repairable Fault Trees with general distributions

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