Digital search trees revisited
SIAM Journal on Computing
Some results on V-ary asymmetric tries
Journal of Algorithms
Elements of information theory
Elements of information theory
Improved behaviour of tries by adaptive branching
Information Processing Letters
The analysis of hybrid trie structures
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Extendible hashing—a fast access method for dynamic files
ACM Transactions on Database Systems (TODS)
PATRICIA—Practical Algorithm To Retrieve Information Coded in Alphanumeric
Journal of the ACM (JACM)
File structures using hashing functions
Communications of the ACM
Use of tree structures for processing files
Communications of the ACM
Communications of the ACM
Average Case Analysis of Algorithms on Sequences
Average Case Analysis of Algorithms on Sequences
Random Structures & Algorithms - Special issue on analysis of algorithms dedicated to Don Knuth on the occasion of his (100)8th birthday
Some results on tries with adaptive branching
Theoretical Computer Science
Fast address look-up for internet routers
BC '98 Proceedings of the IFIP TC6/WG6.2 Fourth International Conference on Broadband Communications: The future of telecommunications
Faster Searching in Tries and Quadtrees - An Analysis of Level Compression
ESA '94 Proceedings of the Second Annual European Symposium on Algorithms
On Time-Space Efficiency of Digital Trees with Adaptive Multidigit Branching
Cybernetics and Systems Analysis
Probabilistic behavior of asymmetric level compressed tries
Random Structures & Algorithms
File searching using variable length keys
IRE-AIEE-ACM '59 (Western) Papers presented at the the March 3-5, 1959, western joint computer conference
On the average depth of asymmetric LC-tries
Information Processing Letters
A note on the probabilistic analysis of patricia trees
Random Structures & Algorithms
IP-address lookup using LC-tries
IEEE Journal on Selected Areas in Communications
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We study a class of adaptive multi-digit tries, in which the numbers of digits rn processed by nodes with n incoming strings are such that, in memoryless model (with n → ∞): $r_n \longrightarrow \frac{log n}{\eta} (pr.)$ where η is an algorithm-specific constant. Examples of known data structures from this class include LC-tries (Andersson and Nilsson, 1993), “relaxed” LC-tries (Nilsson and Tikkanen, 1998), tries with logarithmic selection of degrees of nodes, etc. We show, that the average depth Dn of such tries in asymmetric memoryless model has the following asymptotic behavior (with n → ∞): $D_n = \frac{log log n}{-log(1 - h/\eta)}(1 + o(1))$ where n is the number of strings inserted in the trie, and h is the entropy of the source. We use this formula to compare performance of known adaptive trie structures, and to predict properties of other possible implementations of tries in this class.