在线拓扑排序的平均-实例分析
Average-Case Analysis of Online Topological Ordering
摘要:
指针分析和增量编译等应用需要在动态更新下维护有向无环图(DAG)节点的拓扑顺序。这个问题的所有已知算法要么只分析最坏情况下的插入序列,要么只在随机DAG上进行实验评估。我们提出了第一个平均情况下分析在线拓扑排序算法。对于Alpern等人(SODA,1990),Katriel和Bodlaender(TALG,2006)以及Pearce和Kelly(JEA,2006)的算法,我们证明了在以随机顺序插入完整DAG的边的情况下的预期运行时间为O(n^2 polylog(n))。这比这个问题最著名的最坏情况下的界限O(n^{2.75})要小得多。
英文摘要:
Many applications like pointer analysis and incremental compilation require maintaining a topological ordering of the nodes of a directed acyclic graph (DAG) under dynamic updates. All known algorithms for this problem are either only analyzed for worst-case insertion sequences or only evaluated experimentally on random DAGs. We present the first average-case analysis of online topological ordering algorithms. We prove an expected runtime of O(n^2 polylog(n)) under insertion of the edges of a complete DAG in a random order for the algorithms of Alpern et al. (SODA, 1990), Katriel and Bodlaender (TALG, 2006), and Pearce and Kelly (JEA, 2006). This is much less than the best known worst-case bound O(n^{2.75}) for this problem.
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