SCOOP: A Tool for SymboliC Optimisations Of Probabilistic Processes

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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33 Downloads (Pure)

Abstract

This paper presents SCOOP: a tool that symbolically optimises process-algebraic specifications of probabilistic processes. It takes specifications in the prCRL language (combining data and probabilities), which are linearised first to an intermediate format: the LPPE. On this format, optimisations such as dead-variable reduction and confluence reduction are applied automatically by SCOOP. That way, drastic state space reductions are achieved while never having to generate the complete state space, as data variables are unfolded only locally. The optimised state spaces are ready to be analysed by for instance CADP or PRISM.
Original languageUndefined
Title of host publicationProceedings of the 8th International Conference on Quantitative Evaluation of SysTems, QEST 2011
EditorsC. Palamidessi, A. Riska
Place of PublicationLos Alamitos, USA
PublisherIEEE Computer Society
Pages149-150
Number of pages2
ISBN (Print)978-1-4577-0973-9
DOIs
Publication statusPublished - Sep 2011
Event8th International Conference on Quantitative Evaluation of SysTems, QEST 2011 - RWTH Aachen University, Aachen, Germany
Duration: 5 Sep 20118 Sep 2011
Conference number: 8

Publication series

Name
PublisherIEEE Computer Society

Conference

Conference8th International Conference on Quantitative Evaluation of SysTems, QEST 2011
Abbreviated titleQEST
CountryGermany
CityAachen
Period5/09/118/09/11

Keywords

  • METIS-277654
  • IR-77422
  • EC Grant Agreement nr.: FP7/214755
  • EWI-20206
  • EC Grant Agreement nr.: FP7-ICT-2007-1

Cite this

Timmer, M. (2011). SCOOP: A Tool for SymboliC Optimisations Of Probabilistic Processes. In C. Palamidessi, & A. Riska (Eds.), Proceedings of the 8th International Conference on Quantitative Evaluation of SysTems, QEST 2011 (pp. 149-150). Los Alamitos, USA: IEEE Computer Society. https://doi.org/10.1109/QEST.2011.27
Timmer, Mark. / SCOOP: A Tool for SymboliC Optimisations Of Probabilistic Processes. Proceedings of the 8th International Conference on Quantitative Evaluation of SysTems, QEST 2011. editor / C. Palamidessi ; A. Riska. Los Alamitos, USA : IEEE Computer Society, 2011. pp. 149-150
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abstract = "This paper presents SCOOP: a tool that symbolically optimises process-algebraic specifications of probabilistic processes. It takes specifications in the prCRL language (combining data and probabilities), which are linearised first to an intermediate format: the LPPE. On this format, optimisations such as dead-variable reduction and confluence reduction are applied automatically by SCOOP. That way, drastic state space reductions are achieved while never having to generate the complete state space, as data variables are unfolded only locally. The optimised state spaces are ready to be analysed by for instance CADP or PRISM.",
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doi = "10.1109/QEST.2011.27",
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}

Timmer, M 2011, SCOOP: A Tool for SymboliC Optimisations Of Probabilistic Processes. in C Palamidessi & A Riska (eds), Proceedings of the 8th International Conference on Quantitative Evaluation of SysTems, QEST 2011. IEEE Computer Society, Los Alamitos, USA, pp. 149-150, 8th International Conference on Quantitative Evaluation of SysTems, QEST 2011, Aachen, Germany, 5/09/11. https://doi.org/10.1109/QEST.2011.27

SCOOP: A Tool for SymboliC Optimisations Of Probabilistic Processes. / Timmer, Mark.

Proceedings of the 8th International Conference on Quantitative Evaluation of SysTems, QEST 2011. ed. / C. Palamidessi; A. Riska. Los Alamitos, USA : IEEE Computer Society, 2011. p. 149-150.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AB - This paper presents SCOOP: a tool that symbolically optimises process-algebraic specifications of probabilistic processes. It takes specifications in the prCRL language (combining data and probabilities), which are linearised first to an intermediate format: the LPPE. On this format, optimisations such as dead-variable reduction and confluence reduction are applied automatically by SCOOP. That way, drastic state space reductions are achieved while never having to generate the complete state space, as data variables are unfolded only locally. The optimised state spaces are ready to be analysed by for instance CADP or PRISM.

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KW - EWI-20206

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Timmer M. SCOOP: A Tool for SymboliC Optimisations Of Probabilistic Processes. In Palamidessi C, Riska A, editors, Proceedings of the 8th International Conference on Quantitative Evaluation of SysTems, QEST 2011. Los Alamitos, USA: IEEE Computer Society. 2011. p. 149-150 https://doi.org/10.1109/QEST.2011.27