MultiVeStA: Statistical Model Checking for Discrete Event Simulators

Sebastio, Stefano; Vandin, Andrea

doi:10.4108/icst.valuetools.2013.254377

Cited by 21 publications

(9 citation statements)

References 22 publications

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“…For example, we plan to extend ERODE, and in particular its stochastic simulator, with statistical model checking [45] capabilities. This can be obtained upon integration with the statistical analyser MultiVeStA [55], which has already proven useful in the analysis of a wide range of scenarios, including software product lines [6,7], crowd-steering [53], public transportation systems [33], and swarm robotics [8].…”

Section: Discussionmentioning

confidence: 99%

Language-based Abstractions for Dynamical Systems

Vandin

2017

Electron. Proc. Theor. Comput. Sci.

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Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of effectively performing analyses. This has motivated a large body of research, across many disciplines, into abstraction techniques that provide smaller ODE systems while preserving the original dynamics in some appropriate sense. In this paper we give an overview of a recently proposed computer-science perspective to this problem, where ODE reduction is recast to finding an appropriate equivalence relation over ODE variables, akin to classical models of computation based on labelled transition systems.

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Section: Discussionmentioning

confidence: 99%

Language-based Abstractions for Dynamical Systems

Vandin

2017

Electron. Proc. Theor. Comput. Sci.

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“…A closely related research line which we have started recently is the combination of statistical modelchecking [25,33] with spatio-temporal model-checking. An example of application of the combined technique to the analysis of a bike-sharing system of the size of the London one is presented in [15].…”

Section: Discussionmentioning

confidence: 99%

On Formal Methods for Collective Adaptive System Engineering. Scalable Approximated, Spatial Analysis Techniques. Extended Abstract.

Latella

2016

Electron. Proc. Theor. Comput. Sci.

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In this extended abstract a view on the role of Formal Methods in System Engineering is briefly presented. Then two examples of useful analysis techniques based on solid mathematical theories are discussed as well as the software tools which have been built for supporting such techniques. The first technique is Scalable Approximated Population DTMC Model-checking. The second one is Spatial Model-checking for Closure Spaces. Both techniques have been developed in the context of the EU funded project QUANTICOL. * Work partially funded by the EU projects QUANTICOL (nr. 600708) and ASCENS (nr. 257414).

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“…The simulator has been enriched with the distributed statistical analysis functionalities provided by MULTIVESTA [30], [31]. MULTIVESTA allows to express the system properties of interest in a compact way through a PCTL (Probabilistic Computation Tree Logic) language.…”

Section: A Simulation Toolsmentioning

confidence: 99%

A Workload-Based Approach to Partition the Volunteer Cloud

Sebastio

Scala

2015

2015 IEEE Conference on Collaboration and Internet Computing (CIC)

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The growing demand of computational resources has shifted users towards the adoption of cloud computing technologies. Cloud allows users to transparently access to remote computing capabilities as an utility. The volunteer computing paradigm, another ICT trend of the last years, can be considered a companion force to enhance the cloud in fulfilling specific domain requirements, such as computational intensive requests. Combining the spared resources provided by volunteer nodes with few data centers is possible to obtain a robust and scalable cloud platform. The price for such benefits relies in increased challenges to design and manage a dynamic complex system composed by heterogeneous nodes. Task execution requests submitted in the volunteer cloud are usually associated with Quality of Service requirements e.g., specified through an execution deadline. In this paper, we present a preliminary evaluation of a cloud partitioning approach to distribute task execution requests in volunteer cloud, that has been validated through a simulation-based statistical analysis using the Google workload data trace.

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MultiVeStA: Statistical Model Checking for Discrete Event Simulators

Cited by 21 publications

References 22 publications

Language-based Abstractions for Dynamical Systems

Language-based Abstractions for Dynamical Systems

On Formal Methods for Collective Adaptive System Engineering. Scalable Approximated, Spatial Analysis Techniques. Extended Abstract.

A Workload-Based Approach to Partition the Volunteer Cloud

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