Binary tree in the context of Child node


Binary tree in the context of Child node

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⭐ Core Definition: Binary tree

In computer science, a binary tree is a tree data structure in which each node has at most two children, referred to as the left child and the right child. That is, it is a k-ary tree where k = 2. A recursive definition using set theory is that a binary tree is a triple (L, S, R), where L and R are binary trees or the empty set and S is a singleton (a single–element set) containing the root.

From a graph theory perspective, binary trees as defined here are arborescences. A binary tree may thus be also called a bifurcating arborescence, a term which appears in some early programming books 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. Some authors use rooted binary tree instead of binary tree to emphasize the fact that the tree is rooted, but as defined above, a binary tree is always rooted.

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Binary tree in the context of Tree (data structure)

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, except for the root node, which has no parent (i.e., the root node as the top-most node in the tree hierarchy). These constraints mean there are no cycles or "loops" (no node can be its own ancestor), and also that each child can be treated like the root node of its own subtree, making recursion a useful technique for tree traversal. In contrast to linear data structures, many trees cannot be represented by relationships between neighboring nodes (parent and children nodes of a node under consideration, if they exist) in a single straight line (called edge or link between two adjacent nodes).

Binary trees are a commonly used type, which constrain the number of children for each parent to at most two. When the order of the children is specified, this data structure corresponds to an ordered tree in graph theory. A value or pointer to other data may be associated with every node in the tree, or sometimes only with the leaf nodes, which have no children nodes.

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Binary tree in the context of Ahnentafel

An ahnentafel (German for "ancestor table"; German: [ˈʔaːnənˌtaːfəl]) or ahnenreihe ("ancestor series"; German: [ˈʔaːnənˌʁaɪə]) is a genealogical numbering system for listing a person's direct ancestors in a fixed sequence of ascent. The subject (or proband) of the ahnentafel is listed as No. 1, the subject's father as No. 2 and the mother as No. 3, the paternal grandparents as No. 4 and No. 5 and the maternal grandparents as No. 6 and No. 7, and so on, back through the generations. Apart from No. 1, who can be male or female, all even-numbered persons are male, and all odd-numbered persons are female. In this schema, the number of any person's father is double the person's number, and a person's mother is double the person's number plus one. Using this definition of numeration, one can derive some basic information about individuals who are listed without additional research.

This construct displays a person's genealogy compactly, without the need for a diagram such as a family tree. It is particularly useful in situations where one may be restricted to presenting a genealogy in plain text, for example, in emails or newsgroup articles. In effect, an ahnentafel is a method for storing a binary tree in an array by listing the nodes (individuals) in level-order (in generation order).

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Binary tree in the context of 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. The following algorithms are described for a binary tree, but they may be generalized to other trees as well.

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