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  2. Leftist tree - Wikipedia

    en.wikipedia.org/wiki/Leftist_tree

    In addition to the heap property, leftist trees are maintained so the right descendant of each node has the lower s-value. The height-biased leftist tree was invented by Clark Allan Crane. [2] The name comes from the fact that the left subtree is usually taller than the right subtree. A leftist tree is a mergeable heap. When inserting a new ...

  3. Tree (abstract data type) - Wikipedia

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

    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 leaf) has depth and height zero.

  4. File:Height Balanced Binary Tree.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Height_Balanced...

    English: Analysis of data structures, tree compared to hash and array based structures, height balanced tree compared to more perfectly balanced trees, a simple height balanced tree class with test code, comparable statistics for tree performance, statistics of worst case strictly-AVL-balanced trees versus perfect full binary trees.

  5. Skew heap - Wikipedia

    en.wikipedia.org/wiki/Skew_heap

    A skew heap (or self-adjusting heap) is a heap data structure implemented as a binary tree. Skew heaps are advantageous because of their ability to merge more quickly than binary heaps. In contrast with binary heaps, there are no structural constraints, so there is no guarantee that the height of the tree is logarithmic. Only two conditions ...

  6. Predecessor problem - Wikipedia

    en.wikipedia.org/wiki/Predecessor_problem

    In computer science, the predecessor problem involves maintaining a set of items to, given an element, efficiently query which element precedes or succeeds that element in an order. Data structures used to solve the problem include balanced binary search trees, van Emde Boas trees, and fusion trees.

  7. Level ancestor problem - Wikipedia

    en.wikipedia.org/wiki/Level_ancestor_problem

    In graph theory and theoretical computer science, the level ancestor problem is the problem of preprocessing a given rooted tree T into a data structure that can determine the ancestor of a given node at a given distance from the root of the tree. More precisely, let T be a rooted tree with n nodes, and let v be an arbitrary node of T.

  8. Higher-order abstract syntax - Wikipedia

    en.wikipedia.org/wiki/Higher-order_abstract_syntax

    An abstract syntax is abstract because it is represented by mathematical objects that have certain structure by their very nature. For instance, in first-order abstract syntax (FOAS) trees, as commonly used in compilers, the tree structure implies the subexpression relation, meaning that no parentheses are required to disambiguate programs (as they are, in the concrete syntax).

  9. Weight-balanced tree - Wikipedia

    en.wikipedia.org/wiki/Weight-balanced_tree

    A weight-balanced tree is a binary search tree that stores the sizes of subtrees in the nodes. That is, a node has fields key, of any ordered type; value (optional, only for mappings) left, right, pointer to node; size, of type integer. By definition, the size of a leaf (typically represented by a nil pointer) is zero.

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