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  2. Fenwick tree - Wikipedia

    en.wikipedia.org/wiki/Fenwick_tree

    A Fenwick tree or binary indexed tree (BIT) is a data structure that stores an array of values and can efficiently compute prefix sums of the values and update the values. It also supports an efficient rank-search operation for finding the longest prefix whose sum is no more than a specified value.

  3. Bit array - Wikipedia

    en.wikipedia.org/wiki/Bit_array

    The Boost C++ Libraries provide a dynamic_bitset class [4] whose size is specified at run-time. The D programming language provides bit arrays in its standard library, Phobos, in std.bitmanip. As in C++, the [] operator does not return a reference, since individual bits are not directly addressable on most hardware, but instead returns a bool.

  4. Binary tree - Wikipedia

    en.wikipedia.org/wiki/Binary_tree

    A balanced binary tree is a binary tree structure in which the left and right subtrees of every node differ in height (the number of edges from the top-most node to the farthest node in a subtree) by no more than 1 (or the skew is no greater than 1). [22]

  5. Binary search tree - Wikipedia

    en.wikipedia.org/wiki/Binary_search_tree

    Fig. 1: A binary search tree of size 9 and depth 3, with 8 at the root. In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree.

  6. Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Huffman_coding

    Huffman tree generated from the exact frequencies of the text "this is an example of a huffman tree". Encoding the sentence with this code requires 135 (or 147) bits, as opposed to 288 (or 180) bits if 36 characters of 8 (or 5) bits were used (This assumes that the code tree structure is known to the decoder and thus does not need to be counted as part of the transmitted information).

  7. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    To traverse arbitrary trees (not necessarily binary trees) with depth-first search, perform the following operations at each node: If the current node is empty then return. Visit the current node for pre-order traversal. For each i from 1 to the current node's number of subtrees − 1, or from the latter to the former for reverse traversal, do:

  8. Priority search tree - Wikipedia

    en.wikipedia.org/wiki/Priority_search_tree

    In computer science, a priority search tree is a tree data structure for storing points in two dimensions. It was originally introduced by Edward M. McCreight. [1] It is effectively an extension of the priority queue with the purpose of improving the search time from O(n) to O(s + log n) time, where n is the number of points in the tree and s is the number of points returned by the search.

  9. Tree (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Tree_(abstract_data_type)

    This unsorted tree has non-unique values (e.g., the value 2 existing in different nodes, not in a single node only) and is non-binary (only up to two children nodes per parent node in a binary tree). The root node at the top (with the value 2 here), has no parent as it is the highest in the tree hierarchy.