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Federation of International Conferences on Software Technologies: Applications and Foundations

STAF 2018: Software Technologies: Applications and Foundations pp 185–200Cite as

FormalMiner: A Formal Framework for Refinement Mining

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Part of the Lecture Notes in Computer Science book series (LNPSE,volume 11176)

Abstract

Refinement mining has been inspired by process mining techniques and aims to refine an abstract non-deterministic model by sifting it using event logs as a sieve until a reasonably concise model is achieved. FormalMiner is a formal framework that implements model mining using Maude, a modelling language based on rewriting logic. Once the final formal model is attained, it can be used, within the same rewriting-logic framework, to predict the future evolution of the behaviour through simulation, to carry out further validation or to analyse properties through model checking. In this paper we focus on the refinement mining capability of FormalMiner and we illustrate it using a case study from ecology.

Keywords

  • Formal methods
  • Model-driven approaches
  • Rewriting logic
  • Maude
  • Process mining
  • Application to ecosystem modelling

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Author information

Authors and Affiliations

  1. Department of Computer Science, Nazarbayev University, Astana, Kazakhstan

    Antonio Cerone

Authors
  1. Antonio Cerone
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Corresponding author

Correspondence to Antonio Cerone .

Editor information

Editors and Affiliations

  1. Innopolis University, Innopolis, Russia

    Prof. Manuel Mazzara

  2. University of Toulouse, Toulouse Cedex 9, France

    Iulian Ober

  3. Grenoble Alpes University, Montbonnot, France

    Gwen Salaün

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Cerone, A. (2018). FormalMiner: A Formal Framework for Refinement Mining. In: Mazzara, M., Ober, I., Salaün, G. (eds) Software Technologies: Applications and Foundations. STAF 2018. Lecture Notes in Computer Science(), vol 11176. Springer, Cham. https://doi.org/10.1007/978-3-030-04771-9_15

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  • DOI: https://doi.org/10.1007/978-3-030-04771-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04770-2

  • Online ISBN: 978-3-030-04771-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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