面向因果模糊并发系统的动作细化

Jinzhao Wu, Houguang Yue
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引用次数: 2

摘要

动作细化是并发系统分层设计方法中的核心操作。本文提出了一种基于因果模糊概念的并发系统动作细化方法,这种方法在实际应用中经常出现。这些系统是根据具有因果歧义的事件结构来建模的。我们证明了低级系统的行为本身是从高级系统的行为派生出来的:在一定的偏序语义下,精炼系统的行为可以从原始系统的行为和用于用显式表示的起点代替动作的系统的行为组合地推断出来。此外,在此改进下,线性时间等价的一种变体pomset迹等价和基于偏序语义的分支时间等价的一种变体历史保持双模拟等价都是同余的。因此,细化操作表现良好,并满足通常期望的属性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards action refinement for concurrent systems with causal ambiguity
Action refinement is a core operation in the hierarchical design methodology for concurrent systems. In this paper we develop an action refinement approach for concurrent systems with the notion of causal ambiguity, which often exists and appears in real application areas. The systems are modelled in terms of event structures with causal ambiguity. We demonstrate that the behavior of the lower-level system is itself derived from the behavior of the high-level system : Under a certain partial order semantics, the behavior of the refined system can be inferred compositionally from the behavior of the original system and from the behavior of the systems used to substitute actions with explicitly represented start points. Furthermore, a variant of a linear-time equivalence termed pomset trace equivalence and a variant of a branching-time equivalence termed history preserving bisimulation equivalence based on the partial order semantics are both congruences under the refinement. The refinement operation behaves thus well and meets the commonly expected properties.
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