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Minimal Coverability Tree Construction Made Complete and Efficient

机译:最小的可覆盖性树构建完整而高效

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Downward closures of Petri net reachability sets can be finitely represented by their set of maximal elements called the minimal cover-ability set or Clover. Many properties (coverability, boundedness, ...) can be decided using Clover, in a time proportional to the size of Clover. So it is crucial to design algorithms that compute it efficiently. We present a simple modification of the original but incomplete Minimal Coverability Tree algorithm (MCT), computing Clover, which makes it complete: it memorizes accelerations and fires them as ordinary transitions. Contrary to the other alternative algorithms for which no bound on the size of the required additional memory is known, we establish that the additional space of our algorithm is at most doubly exponential. Furthermore we have implemented a prototype MinCov which is already very competitive: on benchmarks it uses less space than all the other tools and its execution time is close to the one of the fastest tool.
机译:Petri网可达性集的向下闭合可以用称为最小覆盖能力集或Clover的最大元素集来有限表示。可以使用四叶草在与四叶草的大小成比例的时间内确定许多属性(可覆盖性,有界性,...)。因此,设计有效计算算法的至关重要。我们对原始但不完整的最小覆盖率树算法(MCT)进行了简单的修改,即计算三叶草,使其变得完整:它记住加速度并将其作为普通转换触发。与其他可选算法(所需的额外内存的大小不受限制)相反,我们确定该算法的额外空间最多为双指数。此外,我们已经实现了MinCov原型,该原型已经非常具有竞争力:在基准测试中,它使用的空间比所有其他工具都要少,并且其执行时间接近最快的工具之一。

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