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Great-Nsolve: A Tool Integration for (Markov Regenerative) Stochastic Petri Nets

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Quantitative Evaluation of Systems (QEST 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11785))

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Abstract

This paper presents Great-Nsolve, the integration of GreatSPN (with its user-friendly graphical interface and its numerous possibilities of stochastic Petri net analysis) and Nsolve (with its very efficient numerical solution methods) aimed at solving large Markov Regenerative Stochastic Petri Nets (MRSPN). The support for general distribution is provided by the alphaFactory library.

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Author information

Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Torino, Torino, Italy

    Elvio Gilberto Amparore & Susanna Donatelli

  2. Department of Computer Science, TU Dortmund, Dortmund, Germany

    Peter Buchholz

Authors
  1. Elvio Gilberto Amparore
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  2. Peter Buchholz
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  3. Susanna Donatelli
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Corresponding authors

Correspondence to Elvio Gilberto Amparore , Peter Buchholz or Susanna Donatelli .

Editor information

Editors and Affiliations

  1. University of Birmingham, Birmingham, UK

    David Parker

  2. Saarland University, Saarbrücken, Germany

    Verena Wolf

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Amparore, E.G., Buchholz, P., Donatelli, S. (2019). Great-Nsolve: A Tool Integration for (Markov Regenerative) Stochastic Petri Nets. In: Parker, D., Wolf, V. (eds) Quantitative Evaluation of Systems. QEST 2019. Lecture Notes in Computer Science(), vol 11785. Springer, Cham. https://doi.org/10.1007/978-3-030-30281-8_21

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  • DOI: https://doi.org/10.1007/978-3-030-30281-8_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30280-1

  • Online ISBN: 978-3-030-30281-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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