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  2. Tree (abstract data type) - Wikipedia

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

    In computer science, a tree is a widely used abstract data type that represents a hierarchical tree structure with a set of connected nodes. Each node in the tree can be connected to many children (depending on the type of tree), but must be connected to exactly one parent, [ 1 ] [ 2 ] except for the root node, which has no parent (i.e., the ...

  3. Abstract syntax tree - Wikipedia

    en.wikipedia.org/wiki/Abstract_syntax_tree

    An abstract syntax tree (AST) is a data structure used in computer science to represent the structure of a program or code snippet. It is a tree representation of the abstract syntactic structure of text (often source code) written in a formal language. Each node of the tree denotes a construct occurring in the text.

  4. 2–3–4 tree - Wikipedia

    en.wikipedia.org/wiki/2–3–4_tree

    In computer science, a 2–3–4 tree (also called a 2–4 tree) is a self-balancing data structure that can be used to implement dictionaries. The numbers mean a tree where every node with children (internal node) has either two, three, or four child nodes: a 2-node has one data element, and if internal has two child nodes;

  5. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    In computer science, tree traversal (also known as tree search and walking the tree) is a form of graph traversal and refers to the process of visiting (e.g. retrieving, updating, or deleting) each node in a tree data structure, exactly once. Such traversals are classified by the order in which the nodes are visited.

  6. Ukkonen's algorithm - Wikipedia

    en.wikipedia.org/wiki/Ukkonen's_algorithm

    Final suffix tree using Ukkonen's algorithm (example). To better illustrate how a suffix tree is constructed using Ukkonen's algorithm, we can consider the string S = xabxac. Start with an empty root node. Construct for S[1] by adding the first character of the string. Rule 2 applies, which creates a new leaf node.

  7. Priority search tree - Wikipedia

    en.wikipedia.org/wiki/Priority_search_tree

    In computer science, a priority search tree is a tree data structure for storing points in two dimensions. It was originally introduced by Edward M. McCreight. [1] It is effectively an extension of the priority queue with the purpose of improving the search time from O(n) to O(s + log n) time, where n is the number of points in the tree and s is the number of points returned by the search.

  8. 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

  9. Zipper (data structure) - Wikipedia

    en.wikipedia.org/wiki/Zipper_(data_structure)

    A layperson's explanation for a tree with zipper would be an ordinary computer filesystem with operations to go to parent (often cd..), and the possibility to go downwards (cd subdirectory). The zipper is the pointer to the current path. Behind the scenes the zippers are efficient when making (functional) changes to a data structure, where a ...