Problem solving using process algebra considered insightful.

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

4 Citations (Scopus)

Abstract

Process algebras with data, such as LOTOS, PSF, FDR, and mCRL2, are very suitable to model and analyse combinatorial problems. Contrary to more traditional mathematics, many of these problems can very directly be formulated in process algebra. Using a wide range of techniques, such as behavioural reductions, model checking, and visualisation, the problems can subsequently be easily solved. With the advent of probabilistic process algebras this also extends to problems where probabilities play a role. In this paper we model and analyse a number of very well-known – yet tricky – problems and show the elegance of behavioural analysis.
Original languageEnglish
Title of host publicationModelEd, TestEd, TrustEd
Subtitle of host publicationEssays Dedicated to Ed Brinksma on the Occasion of His 60th Birthday
EditorsJoost-Pieter Katoen, Rom Langerak, Arend Rensink
Place of PublicationCham
PublisherSpringer
Chapter3
Pages48-63
Number of pages16
ISBN (Electronic)978-3-319-68270-9
ISBN (Print)978-3-319-68269-3
DOIs
Publication statusPublished - 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10500 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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    Groote, J. F., & de Vink, E. P. (2017). Problem solving using process algebra considered insightful. In J-P. Katoen, R. Langerak, & A. Rensink (Eds.), ModelEd, TestEd, TrustEd: Essays Dedicated to Ed Brinksma on the Occasion of His 60th Birthday (pp. 48-63). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10500 LNCS). Springer. https://doi.org/10.1007/978-3-319-68270-9_3