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  2. Binary tree - Wikipedia

    en.wikipedia.org/wiki/Binary_tree

    Tree rotations are very common internal operations on self-balancing binary trees. There are a variety of different operations that can be performed on binary trees. Some are mutator operations, while others simply return useful information about the tree.

  3. Treap - Wikipedia

    en.wikipedia.org/wiki/Treap

    Treaps support the following basic operations: To search for a given key value, apply a standard binary search algorithm in a binary search tree, ignoring the priorities. To insert a new key x into the treap, generate a random priority y for x.

  4. Binary search tree - Wikipedia

    en.wikipedia.org/wiki/Binary_search_tree

    The performance of a binary search tree is dependent on the order of insertion of the nodes into the tree since arbitrary insertions may lead to degeneracy; several variations of the binary search tree can be built with guaranteed worst-case performance. The basic operations include: search, traversal, insert and delete.

  5. 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.

  6. 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:

  7. 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:

  8. B-tree - Wikipedia

    en.wikipedia.org/wiki/B-tree

    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]

  9. Tree rotation - Wikipedia

    en.wikipedia.org/wiki/Tree_rotation

    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. Tamari lattice, a partially ordered set in which the elements can be defined as binary trees and the ordering between elements is defined by tree rotation.