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Degeneralization Algorithm for Generation of Büchi Automata Based on Contented Situation

机译:基于满足局面的Büchi自动机的成熟化算法

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摘要

We present on-the-fly degeneralization algorithm used to transform generalized Büchi automata (GBA) into Büchi Automata (BA) different from the standard degeneralization algorithm. Contented situation, which is used to record what acceptance conditions are satisfiable during expanding LTL formulae, is attached to the states and transitions in the BA. In order to get the deterministic BA, the Shannon expansion is used recursively when we expand LTL formulae by applying the tableau rules. On-the-fly degeneralization algorithm is carried out in each step of the expansion of LTL formulae. Ordered binary decision diagrams are used to represent the BA and simplify LTL formulae. The temporary automata are stored as syntax directed acyclic graph in order to save storage space. These ideas are implemented in a conversion algorithm used to build a property automaton corresponding to the given LTL formulae. We compare our method to previous work and show that it is more efficient for four sets of random formulae generated by LBTT.
机译:我们展示了用于将广义Büchi自动机(GBA)转换为与标准张结构算法不同的Büchi自动机(BA)的逐渐变识别算法。满足局面的情况,用于记录在扩展LTL公式期间在扩展LTL公式期间符合什么验收条件,附加到州和BA中的转换。为了获得确定性的BA,当我们通过应用Tableau规则延长LTL公式时,Shannon扩展将递归使用。在膨胀LTL公式的每个步骤中进行了逐渐变成算法。订购的二进制判定图用于表示BA并简化LTL公式。临时自动机存储为语法定向非循环图,以便保存存储空间。这些想法是以转换算法实现的,用于构建对应于给定的LTL公式的属性自动机。我们将方法与以前的工作进行比较,并表明它对于LBTT生成的四组随机公式更有效。

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