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Reinhard Kutzelnigg

dblp:85/7529 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 3 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Algorithms and data structures · 70% Combinatorics and discrete mathematics · 23% Graph algorithms and graph theory · 7%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › analysis of algorithms
average-case analysis
0.112012
A precise analysis of Cuckoo hashing · ACM Trans. Algorithms 2012
Algorithms and data structures › data structure design › search structures › hashing › multiple-choice hashing
cuckoo hashing
0.112012
A precise analysis of Cuckoo hashing · ACM Trans. Algorithms 2012
Combinatorics and discrete mathematics
generating functions
0.112012
A precise analysis of Cuckoo hashing · ACM Trans. Algorithms 2012
Algorithms and data structures › data structure design › search structures
hashing
0.112012
A precise analysis of Cuckoo hashing · ACM Trans. Algorithms 2012
Graph algorithms and graph theory
random graphs
0.012012
A precise analysis of Cuckoo hashing · ACM Trans. Algorithms 2012

Methods — techniques the papers use, named apart from their topics

generating functions · 0.1double saddle point method · 0.1asymptotic expansion · 0.1
YearPublicationVenuePosition
2012 A precise analysis of Cuckoo hashing
abstract
Cuckoo hashing was introduced by Pagh and Rodler in 2001. Its main feature is that it provides constant worst-case search time. The aim of this article is to present a precise average case analysis of Cuckoo hashing. In particular, we determine the probability that Cuckoo hashing produces no conflicts and give an upper bound for the construction time, that is linear in the size of the table. The analysis rests on a generating function approach to the so called Cuckoo Graph, a random bipartite graph, and an application of a double saddle point method to obtain asymptotic expansions. Furthermore, we provide some results concerning the structure of these kinds of random graphs. Our results extend the analysis of Devroye and Morin [2003]. Additionally, we provide numerical results confirming the mathematical analysis.
Michael Drmota, Reinhard Kutzelnigg
ACM Trans. Algorithms2
2009 Combinatorial Models for Cooperation Networks
Michael Drmota, Bernhard Gittenberger, Reinhard Kutzelnigg
IWOCA3
2008 An Improved Version of Cuckoo Hashing: Average Case Analysis of Construction Cost and Search Operations
Reinhard Kutzelnigg
IWOCA1