Searching in Random Partially Ordered Sets
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Searching in random partially ordered sets
Theoretical Computer Science - Latin American theorotical informatics
An efficient search algorithm for partially ordered sets
ACST'06 Proceedings of the 2nd IASTED international conference on Advances in computer science and technology
On searching a table consistent with division poset
Theoretical Computer Science
Finding an optimal tree searching strategy in linear time
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Edge ranking and searching in partial orders
Discrete Applied Mathematics
B-tries for disk-based string management
The VLDB Journal — The International Journal on Very Large Data Bases
On the complexity of searching in trees: average-case minimization
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Quantum search of partially ordered sets
Quantum Information & Computation
Binary identification problems for weighted trees
WADS'11 Proceedings of the 12th international conference on Algorithms and data structures
Searching in dynamic tree-like partial orders
WADS'11 Proceedings of the 12th international conference on Algorithms and data structures
On the complexity of searching in trees and partially ordered structures
Theoretical Computer Science
The binary identification problem for weighted trees
Theoretical Computer Science
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It is well known that the optimal solution for searching in a finite total order set is binary search. In binary search we divide the set into two "halves" by querying the middle element and continue the search on the suitable half. What is the equivalent of binary search when the set P is partially ordered? A query in this case is to a point $x\in P$, with two possible answers: "yes" indicates that the required element is "below" x or "no" if the element is not below x. We show that the problem of computing an optimal strategy for search in posets that are tree-like (or forests) is polynomial in the size of the tree and requires at most O(n4 log3 n) steps. Optimal solutions of such search problems are often needed in program testing and debugging, where a given program is represented as a tree and a bug should be found using a minimal set of queries. This type of search is also applicable in searching classified large tree-like databases (e.g., the Internet).