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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 ...
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.
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.
A binary tree may thus be also called a bifurcating arborescence, [3] a term which appears in some early programming books [4] before the modern computer science terminology prevailed. It is also possible to interpret a binary tree as an undirected , rather than directed graph , in which case a binary tree is an ordered , rooted tree . [ 5 ]
A simple binary tree of size 9 and height 3, with a root node whose value is 2. The above tree is unbalanced and not sorted. Nodes are often arranged into tree structures. A node represents the information contained in a single data structure. These nodes may contain a value or condition, or possibly serve as another independent data structure.
This is particularly used in the representation of text in computer languages, [2] which are generally stored in a tree structure as an abstract syntax tree. Abstract syntax, which only consists of the structure of data, is contrasted with concrete syntax, which also includes information about the representation. For example, concrete syntax ...
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As a programming technique, it is used most often in the context of lazy programming languages, and can be preferable to recursion when the desired size or precision of a program's output is unknown. In such cases the program requires both a definition for an infinitely large (or infinitely precise) result, and a mechanism for taking a finite ...