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The new data structure is completely rebuilt whenever it grows too large or too small. Let be the number of elements of the total order when it was last rebuilt. The data structure is rebuilt whenever the invariant is violated by an insertion or deletion. Since rebuilding can be done in linear time this does not affect the amortized performance ...
Given a class of input objects, find efficient algorithms and data structures to answer a certain query about a set of input objects each time the input data is modified, i.e., objects are inserted or deleted. Problems in this class have the following measures of complexity: Space – the amount of memory space required to store the data structure;
Static search structures are designed for answering many queries on a fixed database; dynamic structures also allow insertion, deletion, or modification of items between successive queries. In the dynamic case, one must also consider the cost of fixing the search structure to account for the changes in the database.
Operations such as insertion and deletion cause the BST representation to change dynamically. The data structure must be modified in such a way that the properties of BST continue to hold. New nodes are inserted as leaf nodes in the BST. [10]: 294–295 Following is an iterative implementation of the insertion operation. [10]: 294
In computer science, a B-tree is a self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree generalizes the binary search tree , allowing for nodes with more than two children. [ 2 ]
A schematic picture of the skip list data structure. Each box with an arrow represents a pointer and a row is a linked list giving a sparse subsequence; the numbered boxes (in yellow) at the bottom represent the ordered data sequence. Searching proceeds downwards from the sparsest subsequence at the top until consecutive elements bracketing the ...
The deletion procedure for a randomized binary search tree uses the same information per node as the insertion procedure, but unlike the insertion procedure, it only needs on average O(1) random decisions to join the two subtrees descending from the left and right children of the deleted node into a single tree.
Radix trees support insertion, deletion, and searching operations. Insertion adds a new string to the trie while trying to minimize the amount of data stored. Deletion removes a string from the trie. Searching operations include (but are not necessarily limited to) exact lookup, find predecessor, find successor, and find all strings with a prefix.