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  2. 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.

  3. Binary tree - Wikipedia

    en.wikipedia.org/wiki/Binary_tree

    A perfect binary tree is a binary tree in which all interior nodes have two children and all leaves have the same depth or same level (the level of a node defined as the number of edges or links from the root node to a node). [18] A perfect binary tree is a full binary tree.

  4. Associative array - Wikipedia

    en.wikipedia.org/wiki/Associative_array

    This is the case for tree-based implementations, one representative being the <map> container of C++. [16] The order of enumeration is key-independent and is instead based on the order of insertion. This is the case for the "ordered dictionary" in .NET Framework, the LinkedHashMap of Java and Python. [17] [18] [19] The latter is more common.

  5. Bitwise trie with bitmap - Wikipedia

    en.wikipedia.org/wiki/Bitwise_trie_with_bitmap

    A trie is a type of search tree where – unlike for example a B-tree – keys are not stored in the nodes but in the path to leaves. The key is distributed across the tree structure. In a "classic" trie, each node with its child-branches represents one symbol of the alphabet of one position (character) of a key.

  6. Trie - Wikipedia

    en.wikipedia.org/wiki/Trie

    In computer science, a trie (/ ˈ t r aɪ /, / ˈ t r iː /), also known as a digital tree or prefix tree, [1] is a specialized search tree data structure used to store and retrieve strings from a dictionary or set. Unlike a binary search tree, nodes in a trie do not store their associated key.

  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. Succinct data structure - Wikipedia

    en.wikipedia.org/wiki/Succinct_data_structure

    Another example is the representation of a binary tree: an arbitrary binary tree on nodes can be represented in + bits while supporting a variety of operations on any node, which includes finding its parent, its left and right child, and returning the size of its subtree, each in constant time.

  9. 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.