The composition of Event-B models

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Description/Abstract

The transition from classical B \cite{Abr:96} to the Event-B language and method \cite{ABH:06} has seen the removal of some forms of model structuring and composition, with the intention of reinventing them in future. This work contributes to that reinvention. Inspired by a proposed method for state-based decomposition and refinement \cite{AH:06} of an Event-B model, we propose a familiar parallel event composition (over disjoint state variable lists), and the less familiar event fusion (over intersecting state variable lists). A brief motivation is provided for these and other forms of composition of models, in terms of feature-based modelling. We show that model consistency is preserved under such compositions. More significantly we show that model composition preserves refinement.