Self-adjusting binary search trees
Journal of the ACM (JACM)
Rotation distance, triangulations, and hyperbolic geometry
STOC '86 Proceedings of the eighteenth annual ACM symposium on Theory of computing
Self-Organizing Binary Search Trees
Journal of the ACM (JACM)
Alternatives to splay trees with O(log n) worst-case access times
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
On the Dynamic Finger Conjecture for Splay Trees. Part I: Splay Sorting log n-Block Sequences
SIAM Journal on Computing
On the Dynamic Finger Conjecture for Splay Trees. Part II: The Proof
SIAM Journal on Computing
Improved Upper Bounds for Pairing Heaps
SWAT '00 Proceedings of the 7th Scandinavian Workshop on Algorithm Theory
O(log log n)-competitive dynamic binary search trees
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
SIAM Journal on Computing
Skip-Splay: Toward Achieving the Unified Bound in the BST Model
WADS '09 Proceedings of the 11th International Symposium on Algorithms and Data Structures
Confluently Persistent Tries for Efficient Version Control
Algorithmica - Special Issue: Scandinavian Workshop on Algorithm Theory; Guest Editor: Joachim Gudmundsson
Algorithmica
De-amortizing binary search trees
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part I
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We present a general transformation for combining a constant number of binary search tree data structures (BSTs) into a single BST whose running time is within a constant factor of the minimum of any "well-behaved" bound on the running time of the given BSTs, for any online access sequence. (A BST has a well-behaved bound with f(n) overhead if it spends at most $\mathcal{O}(f(n))$ time per access and its bound satisfies a weak sense of closure under subsequences.) In particular, we obtain a BST data structure that is $\mathcal{O}(\log\log n)$ competitive, satisfies the working set bound (and thus satisfies the static finger bound and the static optimality bound), satisfies the dynamic finger bound, satisfies the unified bound with an additive $\mathcal{O}(\log\log n)$ factor, and performs each access in worst-case $\mathcal{O}(\log n)$ time.