Decomposing Monolithic Processes in a Process Algebra with Multi-actions

TL;DR

This paper introduces a technique to decompose complex monolithic processes into smaller, manageable components, enabling more efficient state space analysis and verification in process algebra models.

Contribution

It presents a novel decomposition method for monolithic processes into parameter-specific subprocesses, improving analysis efficiency and state space reduction.

Findings

Decomposition yields smaller state spaces compared to monolithic exploration.

Applying minimization before composition further reduces complexity.

State invariants enhance the effectiveness of the decomposition technique.

Abstract

A monolithic process is a single recursive equation with data parameters, which only uses non-determinism, action prefixing, and recursion. We present a technique that decomposes such a monolithic process into multiple processes where each process defines behaviour for a subset of the parameters of the monolithic process. For this decomposition we can show that a composition of these processes is strongly bisimilar to the monolithic process under a suitable synchronisation context. Minimising the resulting processes before determining their composition can be used to derive a state space that is smaller than the one obtained by a monolithic exploration. We apply the decomposition technique to several specifications to show that this works in practice. Finally, we prove that state invariants can be used to further improve the effectiveness of this decomposition technique.