Causal consistent reversibility blends causality and reversibility. For a concurrent system, it says that an action can be undone provided that this has no consequences, thereby making it possible to bring the system back to a past consistent state. Time reversibility is instead considered in the performance evaluation field, mostly for efficient analysis purposes. A continuous-time Markov chain is time reversible if its stochastic behavior remains the same when the direction of time is reversed. We study how to bridge these two theories of reversibility by showing the conditions under which both causal consistent reversibility and time reversibility can be ensured by construction. This is done in the setting of a stochastic process calculus, which is then equipped with a notion of stochastic bisimilarity accounting for both forward and backward directions.
翻译:持续可逆性混合了因果关系和可逆性。 对于一个同时存在的系统,它说可以取消一项行动,只要它不产生任何后果,从而有可能使系统回到过去的一致性状态。 时间可逆性在业绩评价领域被考虑,主要是为了进行有效的分析。 连续时间的Markov链在时间方向逆转时其随机性行为保持不变时是可逆的。 我们研究如何通过显示建筑可以确保因果可逆性和时间可逆性的条件来弥合这两种可逆性理论。 这项工作是在设计一个随机过程的计算方法时进行的,该计算方法随后具备了前向和后向两个方向的相异性计算概念。