Problem solving using process algebra considered insightful
J.F. Groote and E.P. de Vink

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.