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A dictionary implementation based on dynamic perfect hashing

Authors: Martin Dietzfelbinger; Martin Hühne; Christoph Weidling;

A dictionary implementation based on dynamic perfect hashing

Abstract

We describe experimental results on an implementation of a dynamic dictionary. The basis of our implementation is “dynamic perfect hashing” as described by Dietzfelbinger et al. ( SIAM J. Computing 23 , 1994, pp. 738--761), an extension of the storage scheme proposed by Fredman et al. ( J. ACM 31, 1984, pp. 538--544). At the top level, a hash function is used to partition the keys to be stored into several sets. On the second level, there is a perfect hash function for each of these sets. This technique guarantees O (1) worst-case time for lookup and expected O (1) amortized time for insertion and deletion, while only linear space is required. We study the practical performance of dynamic perfect hashing and describe improvements of the basic scheme. The focus is on the choice of the hash function (both for integer and string keys), on the efficiency of rehashing, on the handling of small buckets, and on the space requirements of the implementation.

Keywords

dictionaries, data structures, Data structures, Information storage and retrieval of data, hash functions, Analysis of algorithms, dynamic hashing, implementation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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