Self-adjusting binary search trees
Journal of the ACM (JACM)
Sequential access in splay trees takes linear time
Combinatorica
Skip lists: a probabilistic alternative to balanced trees
Communications of the ACM
On the dynamic finger conjecture for splay trees
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Splaying a search tree in preorder takes linear time
ACM SIGACT News
Journal of Algorithms
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
A Fast Algorithm for Melding Splay Trees
WADS '89 Proceedings of the Workshop on Algorithms and Data Structures
On the Dynamic Finger Conjecture for Splay Trees Part II: The Proof
On the Dynamic Finger Conjecture for Splay Trees Part II: The Proof
On the Dynamic Finger Conjecture for Splay Trees Part I: Splay Sorting log n-Block Sequences
On the Dynamic Finger Conjecture for Splay Trees Part I: Splay Sorting log n-Block Sequences
Data structures for limited oblivious execution of programs while preserving locality of reference
Proceedings of the 2007 ACM workshop on Digital Rights Management
Software—Practice & Experience
Query Responsive Index Structures
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
Reducing splaying by taking advantage of working sets
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
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Splay trees are self-organizing binary search trees that were introduced by Sleator and Tarjan [J. ACM 32 (1985) 652-686]. In this paper we present a randomized variant of these trees. The new algorithm for reorganizing the tree is both simple and easy to implement. We prove that our randomized splaying scheme has the same asymptotic performance as the original deterministic scheme but improves constants in the expected running time. This is interesting in practice because the search time in splay trees is typically higher than the search time in skip lists and AVL-trees. We present a detailed experimental study of our algorithm. On request sequences generated by fixed probability distributions, we can achieve improvements of up to 25% over deterministic splaying. On request sequences that exhibit high locality of reference, the improvements are minor.