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首页> 外文期刊>LIPIcs : Leibniz International Proceedings in Informatics >A Fully Abstract Game Semantics for Countable Nondeterminism
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A Fully Abstract Game Semantics for Countable Nondeterminism

机译:可数不确定性的完全抽象游戏语义学

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The concept of fairness for a concurrent program means that the program must be able to exhibit an unbounded amount of nondeterminism without diverging. Game semantics models of nondeterminism show that this is hard to implement; for example, Harmer and McCusker's model only admits infinite nondeterminism if there is also the possibility of divergence. We solve a long standing problem by giving a fully abstract game semantics for a simple stateful language with a countably infinite nondeterminism primitive. We see that doing so requires us to keep track of infinitary information about strategies, as well as their finite behaviours. The unbounded nondeterminism gives rise to further problems, which can be formalized as a lack of continuity in the language. In order to prove adequacy for our model (which usually requires continuity), we develop a new technique in which we simulate the nondeterminism using a deterministic stateful construction, and then use combinatorial techniques to transfer the result to the nondeterministic language. Lastly, we prove full abstraction for the model; because of the lack of continuity, we cannot deduce this from definability of compact elements in the usual way, and we have to use a stronger universality result instead. We discuss how our techniques yield proofs of adequacy for models of nondeterministic PCF, such as those given by Tsukada and Ong.
机译:并发程序的公平性概念意味着该程序必须能够表现出无限量的不确定性而不会产生分歧。非确定性的游戏语义模型表明这很难实现。例如,Harmer和McCusker的模型仅在存在分歧的可能性时才承认无限的不确定性。我们通过为一种简单的有状态语言提供完全抽象的游戏语义来解决一个长期存在的问题,该语义具有可计数的无限不确定性原语。我们看到这样做需要我们跟踪有关策略及其有限行为的无限信息。无限的不确定性引起了进一步的问题,可以将其形式化为语言缺乏连续性。为了证明模型的正确性(通常需要连续性),我们开发了一种新技术,其中我们使用确定性有状态构造来模拟不确定性,然后使用组合技术将结果转换为不确定性语言。最后,我们证明了该模型的完全抽象;由于缺乏连续性,我们不能以通常的方式从紧凑元素的可定义性推断出这一点,而必须使用更强的通用性结果。我们讨论了我们的技术如何为不确定的PCF模型(例如Tsukada和Ong给出的模型)提供足够的证据。

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