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  2. Tree (abstract data type) - Wikipedia

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

    The height of a node is the length of the longest downward path to a leaf from that node. The height of the root is the height of the tree. The depth of a node is the length of the path to its root (i.e., its root path). Thus the root node has depth zero, leaf nodes have height zero, and a tree with only a single node (hence both a root and ...

  3. Binary search tree - Wikipedia

    en.wikipedia.org/wiki/Binary_search_tree

    Various height-balanced binary search trees were introduced to confine the tree height, such as AVL trees, Treaps, and red–black trees. [5] The AVL tree was invented by Georgy Adelson-Velsky and Evgenii Landis in 1962 for the efficient organization of information. [6] [7] It was the first self-balancing binary search tree to be invented. [8]

  4. AVL tree - Wikipedia

    en.wikipedia.org/wiki/AVL_tree

    In a binary tree the balance factor of a node X is defined to be the height difference ():= (()) (()) [6]: 459 of its two child sub-trees rooted by node X. A node X with () < is called "left-heavy", one with () > is called "right-heavy", and one with () = is sometimes simply called "balanced".

  5. 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]

  6. Weight-balanced tree - Wikipedia

    en.wikipedia.org/wiki/Weight-balanced_tree

    With the new operations, the implementation of weight-balanced trees can be more efficient and highly-parallelizable. [10] [11] Join: The function Join is on two weight-balanced trees t 1 and t 2 and a key k and will return a tree containing all elements in t 1, t 2 as well as k. It requires k to be greater than all keys in t 1 and smaller than ...

  7. B-tree - Wikipedia

    en.wikipedia.org/wiki/B-tree

    Let h ≥ –1 be the height of the classic B-tree (see Tree (data structure) § Terminology for the tree height definition). Let n ≥ 0 be the number of entries in the tree. Let m be the maximum number of children a node can have. Each node can have at most m−1 keys.

  8. B+ tree - Wikipedia

    en.wikipedia.org/wiki/B+_tree

    B+ tree node format where K=4. (p_i represents the pointers, k_i represents the search keys). As with other trees, B+ trees can be represented as a collection of three types of nodes: root, internal (a.k.a. interior), and leaf. In B+ trees, the following properties are maintained for these nodes:

  9. Self-balancing binary search tree - Wikipedia

    en.wikipedia.org/wiki/Self-balancing_binary...

    For height-balanced binary trees, the height is defined to be logarithmic (⁡) in the number of items. This is the case for many binary search trees, such as AVL trees and red–black trees . Splay trees and treaps are self-balancing but not height-balanced, as their height is not guaranteed to be logarithmic in the number of items.