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Partial-order Reduction For General State Exploring Algorithms

机译:一般状态探索算法的偏序约简

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Partial-order reduction is one of the main techniques used to tackle the combinatorial state explosion problem occurring in explicit-state model checking of concurrent systems. The reduction is performed by exploiting the independence of concurrently executed events, which allows portions of the state space to be pruned. An important condition for the soundness of partial-order-based reduction algorithms is a condition that prevents indefinite ignoring of actions when pruning the state space. This condition is commonly known as the cycle proviso. In this paper, we present a new version of this proviso, which is applicable to a general search algorithm skeleton that we refer to as the general state exploring algorithm (GSEA). GSEA maintains a set of open states from which states are iteratively selected for expansion and moved to a closed set of states. Depending on the data structure used to represent the open set, GSEA can be instantiated as a depth-first, a breadth-first, or a directed search algorithm such as Best-First Search or A*. The proviso is characterized by reference to the open and closed set of states of the search algorithm. As a result, it can be computed in an efficient manner during the search based on local information. We implemented partial-order reduction for GSEA based on our proposed proviso in the tool HSF-SPIN, an extension of the explicit-state model checker SPIN for directed model checking. We evaluate the state space reduction achieved by partial-order reduction using the proposed proviso by comparing it on a set of benchmark problems to the use of other provisos. We also compare the use of breadth-first search (BFS) and A*, two algorithms ensuring that counterexamples of minimal length will be found, together with the proviso that we propose.
机译:偏序还原是解决并发系统显式状态模型检查中出现的组合状态爆炸问题的主要技术之一。通过利用并发执行的事件的独立性来执行减少操作,这可以减少部分状态空间。基于偏序约简算法的健全性的一个重要条件是防止修剪状态空间时不确定地忽略动作的条件。这种情况通常称为循环条件。在本文中,我们提出了此条款的新版本,该条款适用于我们称为通用状态探索算法(GSEA)的通用搜索算法框架。 GSEA维护一组开放状态,从这些状态中反复选择要扩展的状态,然后移至一组封闭状态。根据用于表示开放集的数据结构,可以将GSEA实例化为深度优先,宽度优先或定向搜索算法(例如,最佳优先搜索或A *)。附带条件的特征是参考搜索算法的打开和关闭状态集。结果,可以在搜索期间基于本地信息以有效的方式进行计算。我们基于工具HSF-SPIN中提议的附加条件对GSEA实施了部分顺序缩减,这是显式状态模型检查器SPIN的扩展,用于定向模型检查。我们通过比较一组基准问题与其他条件的使用来比较所提出的条件,来评估通过部分顺序减少而实现的状态空间减少。我们还比较了广度优先搜索(BFS)和A *的使用,这两种算法可确保找到最小长度的反例以及我们建议的附带条件。

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