Exploring the Scope for Partial Order Reduction
Partial order reduction methods combat state explosion by exploring only a part of the full state space. In each state a subset of enabled transitions is selected using well-established criteria. Typically such criteria are based on an upper approximation of dependencies between transitions. An additional heuristic is needed to ensure that currently disabled transitions stay disabled in the discarded execution paths. Usually rather coarse approximations and heuristics have been used, together with fast, simple algorithms that do not fully exploit the information available. More powerful approximations, heuristics, and algorithms had been suggested early on, but little is known whether their use pays off. We approach this question, not by trying alternative methods, but by investigating how much room the popular methods leave for better reduction. We do this via a series of experiments that mimic the ultimate reduction obtainable under certain conditions.
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