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  2. AVL tree - Wikipedia

    en.wikipedia.org/wiki/AVL_tree

    To split an AVL tree into two smaller trees, those smaller than key k, and those greater than key k, first draw a path from the root by inserting k into the AVL. After this insertion, all values less than k will be found on the left of the path, and all values greater than k will be found on the right.

  3. List of data structures - Wikipedia

    en.wikipedia.org/wiki/List_of_data_structures

    This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.

  4. Join-based tree algorithms - Wikipedia

    en.wikipedia.org/wiki/Join-based_tree_algorithms

    In 2016, Blelloch et al. formally proposed the join-based algorithms, and formalized the join algorithm for four different balancing schemes: AVL trees, red–black trees, weight-balanced trees and treaps. In the same work they proved that Adams' algorithms on union, intersection and difference are work-optimal on all the four balancing schemes.

  5. WAVL tree - Wikipedia

    en.wikipedia.org/wiki/WAVL_tree

    One advantage of AVL trees over red–black trees is being more balanced: they have height at most ⁡ ⁡ (for a tree with n data items, where is the golden ratio), while red–black trees have larger maximum height, ⁡. If a WAVL tree is created using only insertions, without deletions, then it has the same small height bound that an AVL ...

  6. Self-balancing binary search tree - Wikipedia

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

    For example, if binary tree sort is implemented with a self-balancing BST, we have a very simple-to-describe yet asymptotically optimal (⁡) sorting algorithm. Similarly, many algorithms in computational geometry exploit variations on self-balancing BSTs to solve problems such as the line segment intersection problem and the point location ...

  7. Order statistic tree - Wikipedia

    en.wikipedia.org/wiki/Order_statistic_tree

    To turn a regular search tree into an order statistic tree, the nodes of the tree need to store one additional value, which is the size of the subtree rooted at that node (i.e., the number of nodes below it). All operations that modify the tree must adjust this information to preserve the invariant that size[x] = size[left[x]] + size[right[x]] + 1

  8. Tree (abstract data type) - Wikipedia

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

    Trees are commonly used to represent or manipulate hierarchical data in applications such as: File systems for: Directory structure used to organize subdirectories and files (symbolic links create non-tree graphs, as do multiple hard links to the same file or directory) The mechanism used to allocate and link blocks of data on the storage device

  9. Tree (graph theory) - Wikipedia

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

    The depth of a tree is the maximum depth of any vertex. Depth is commonly needed in the manipulation of the various self-balancing trees, AVL trees in particular. The root has depth zero, leaves have height zero, and a tree with only a single vertex (hence both a root and leaf) has depth and height zero.