多推杆合作系统的后向可达性

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Chris Köcher , Dietrich Kuske
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引用次数: 0

摘要

合作式多图元系统由多个图元组成,这些图元可以将递归程序的执行委托给子图元;一旦所有子图元完成任务,控制权就会返回到调用图元。这就允许了并发执行,因为不相连的子元组可以独立执行它们的任务。由于递归下降到子元组的具体形式,多重下推的内容并不构成任意的字元组,而是可以理解为马祖尔凯维奇跟踪(Mazurkiewicz trace)。对于这种系统,我们证明了后向可达性关系有效地保留了可识别性,这是对 Bouajjani 等人针对单下推系统的结果和证明技术的推广。由此可见,对于合作的多推倒系统,可达性关系是可以在多项式时间内解密的,而且对于可识别的配置集所给出的安全性和有效性等属性也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Backwards-reachability for cooperating multi-pushdown systems
A cooperating multi-pushdown system consists of a tuple of pushdown systems that can delegate the execution of recursive procedures to sub-tuples; control returns to the calling tuple once all sub-tuples finished their task. This allows the concurrent execution since disjoint sub-tuples can perform their task independently. Because of the concrete form of recursive descent into sub-tuples, the content of the multi-pushdown does not form an arbitrary tuple of words, but can be understood as a Mazurkiewicz trace. For such systems, we prove that the backwards reachability relation efficiently preserves recognizability, generalizing a result and proof technique by Bouajjani et al. for single-pushdown systems. It follows that the reachability relation is decidable for cooperating multi-pushdown systems in polynomial time and the same holds, e.g., for safety and liveness properties given by recognizable sets of configurations.
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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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