  Cooperative constraint solving is an area of constraint programming that
studies the interaction between constraint solvers with the aim of discovering
the interaction patterns that amplify the positive qualities of individual
solvers. Automatisation and formalisation of such studies is an important issue
of cooperative constraint solving.
  In this paper we present a constraint-based analysis of composite solvers
that integrates reasoning about the individual solvers and the processed data.
The idea is to approximate this reasoning by resolution of set constraints on
the finite sets representing the predicates that express all the necessary
properties. We illustrate application of our analysis to two important
cooperation patterns: deterministic choice and loop.
