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  2. AVL tree - Wikipedia

    en.wikipedia.org/wiki/AVL_tree

    With the new operations, the implementation of AVL trees can be more efficient and highly-parallelizable. [13] The function Join on two AVL trees t 1 and t 2 and a key k 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 all keys in t 2.

  3. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    In depth-first search (DFS), the search tree is deepened as much as possible before going to the next sibling. To traverse binary trees with depth-first search, perform the following operations at each node: [3] [4] If the current node is empty then return. Execute the following three operations in a certain order: [5] N: Visit the current node.

  4. Self-balancing binary search tree - Wikipedia

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

    Most operations on a binary search tree (BST) take time directly proportional to the height of the tree, so it is desirable to keep the height small. A binary tree with height h can contain at most 2 0 +2 1 +···+2 h = 2 h+1 −1 nodes. It follows that for any tree with n nodes and height h: + And that implies:

  5. Red–black tree - Wikipedia

    en.wikipedia.org/wiki/Red–black_tree

    The worst-case height of AVL is 0.720 times the worst-case height of red-black trees, so AVL trees are more rigidly balanced. The performance measurements of Ben Pfaff with realistic test cases in 79 runs find AVL to RB ratios between 0.677 and 1.077, median at 0.947, and geometric mean 0.910. [22]

  6. Input enhancement (computer science) - Wikipedia

    en.wikipedia.org/wiki/Input_Enhancement...

    Trees are used throughout computer science and many different types of trees – binary search trees, AVL trees, red–black trees, and 2–3 trees to name just a small few – have been developed to properly store, access, and manipulate data while maintaining their structure. Trees are a principal data structure for dictionary implementation.

  7. Day–Stout–Warren algorithm - Wikipedia

    en.wikipedia.org/wiki/Day–Stout–Warren_algorithm

    The Day–Stout–Warren (DSW) algorithm is a method for efficiently balancing binary search trees – that is, decreasing their height to O(log n) nodes, where n is the total number of nodes. Unlike a self-balancing binary search tree , it does not do this incrementally during each operation, but periodically, so that its cost can be amortized ...

  8. AOL

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    The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web. AOL.

  9. Tree rotation - Wikipedia

    en.wikipedia.org/wiki/Tree_rotation

    AVL tree, red–black tree, and splay tree, kinds of binary search tree data structures that use rotations to maintain balance. Associativity of a binary operation means that performing a tree rotation on it does not change the final result. The Day–Stout–Warren algorithm balances an unbalanced BST.