2001
DOI: 10.1002/rsa.10009
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Asymptotic distribution for the cost of linear probing hashing

Abstract: Abstract. We study moments and asymptotic distributions of the construction cost, measured as the total displacement, for hash tables using linear probing. Four different methods are employed for different ranges of the parameters; together they yield a complete description. This extends earlier results by Flajolet, Poblete and Viola. The average cost of unsuccessful searches is considered too.

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Cited by 36 publications
(55 citation statements)
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References 29 publications
(62 reference statements)
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“…As has been noted earlier, see e.g. [10], the asymptotic behaviour of hashing with linear probing when n and m and tend to ∞ depend on the relative size of m and n. We will in the present paper, for simplicity as well as for lack of time and space, only consider the case n/m → α with 0 < α < 1. (This is also the range of most interest for computer applications.)…”
Section: (T ) Is a Random Distribution And Its Mean E(d(t )|T ) And Vmentioning
confidence: 88%
See 2 more Smart Citations
“…As has been noted earlier, see e.g. [10], the asymptotic behaviour of hashing with linear probing when n and m and tend to ∞ depend on the relative size of m and n. We will in the present paper, for simplicity as well as for lack of time and space, only consider the case n/m → α with 0 < α < 1. (This is also the range of most interest for computer applications.)…”
Section: (T ) Is a Random Distribution And Its Mean E(d(t )|T ) And Vmentioning
confidence: 88%
“…(It can be treated by similar methods, cf. the discussion of the total displacement in [10].) It will be seen below, that in this range, the dependency on T is negligible.…”
Section: (T ) Is a Random Distribution And Its Mean E(d(t )|T ) And Vmentioning
confidence: 94%
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“…This formula for m = 2 was derived in another way by Janson [25,Theorem 7.4]. There the distribution of S 2 (λ) appears as the asymptotic distribution, in a suitable limit regime, of the cost of linear probing hashing.…”
Section: Corollary 16mentioning
confidence: 98%
“…Instances and variants of this model have found applications in the diverse fields of population genetics [17,19], combinatorics [4,48], Bayesian statistics [23], ecology [37,15], statistical physics [11,12,13,53,55], and computer science [25].…”
Section: Introductionmentioning
confidence: 99%