Self-organizing heuristics for implicit data structures
SIAM Journal on Computing
Amortized efficiency of list update and paging rules
Communications of the ACM
Self-adjusting binary search trees
Journal of the ACM (JACM)
Implicit data structures for weighted elements
Information and Control - The MIT Press scientific computation series
Self-adjusting multi-way search trees
Information Processing Letters
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Self-Adjusting k-ary Search Trees
WADS '89 Proceedings of the Workshop on Algorithms and Data Structures
Segmented hash: an efficient hash table implementation for high performance networking subsystems
Proceedings of the 2005 ACM symposium on Architecture for networking and communications systems
B-tries for disk-based string management
The VLDB Journal — The International Journal on Very Large Data Bases
Divide and discriminate: algorithm for deterministic and fast hash lookups
Proceedings of the 5th ACM/IEEE Symposium on Architectures for Networking and Communications Systems
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This paper introduces a general technique for speeding up unsuccessful search using very little extra space (2 bits per key). This technique is applicable to many data structures including linear lists, and search trees. For linear lists we get on-line algorithms for processing a sequence of successful and unsuccessful searches which are competitive with strong off-line algorithms. In a virtual memory environment our self-adjusting algorithm for multi-way search trees is competitive with an optimal static multi-way tree and will often outperform the static tree.