map-reduce中的DFA最小化

Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond Pub Date : 2016-06-26 DOI:10.1145/2926534.2926537

G. Grahne, Shahab Harrafi, Iraj Hedayati, A. Moallemi

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引用次数: 7

摘要

我们描述了两种最突出的DFA最小化方法的Map-Reduce实现，即摩尔算法和霍普克罗夫特算法。我们的分析表明，基于Hopcroft算法的算法在运行时间和通信成本方面都更加高效。我们对多达217种状态的各种DFA进行了广泛的实验，验证了这一点。结果还表明，这两种算法对倾斜输入都很敏感，Hopcroft算法本质上就是这样。

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DFA minimization in map-reduce

We describe Map-Reduce implementations of two of the most prominent DFA minimization methods, namely Moore's and Hopcroft's algorithms. Our analysis shows that the one based on Hopcroft's algorithm is more efficient, both in terms of running time and communication cost. This is validated by our extensive experiments on various types of DFA's, with up to 217 states. It also turns out that both algorithms are sensitive to skewed input, the Hopcroft's algorithm being intrinsically so.

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Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond

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