Tree ADTs
From
(→Terminology) |
(→Glossary of terms for rooted trees) |
||
Line 20: | Line 20: | ||
The topmost node in a tree is called the '''root node'''. Being the topmost node, the root node will not have parents. It is the node at which operations on the tree commonly begin (although some algorithms begin with the leaf nodes and work up ending at the root). All other nodes can be reached from it by following '''edges''' or '''links'''. (In the formal definition, each such path is also unique). In diagrams, it is typically drawn at the top. In some trees, such as [[heap (data structure)|heap]]s, the root node has special properties. Every node in a tree can be seen as the root node of the subtree rooted at that node. | The topmost node in a tree is called the '''root node'''. Being the topmost node, the root node will not have parents. It is the node at which operations on the tree commonly begin (although some algorithms begin with the leaf nodes and work up ending at the root). All other nodes can be reached from it by following '''edges''' or '''links'''. (In the formal definition, each such path is also unique). In diagrams, it is typically drawn at the top. In some trees, such as [[heap (data structure)|heap]]s, the root node has special properties. Every node in a tree can be seen as the root node of the subtree rooted at that node. | ||
<br/><br/> | <br/><br/> | ||
- | + | Nodes at the bottommost level of the tree are called '''leaf nodes'''. Since they are at the bottommost level, they do not have any children. | |
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | + | ||
- | Nodes at the bottommost level of the tree are called ''' | + | |
They are also referred to as terminal nodes. | They are also referred to as terminal nodes. | ||
<br/><br/> | <br/><br/> | ||
- | An '''internal node''' or '''inner node''' is any | + | An '''internal node''' or '''inner node''' is any node of a tree that has child nodes and is thus not a leaf node. |
<br/><br/> | <br/><br/> | ||
- | A '''subtree''' is a portion of a tree data structure that can be viewed as a complete tree in itself. Any node in a tree ''T'', together with all the nodes below it, comprise a subtree of ''T''. The subtree corresponding to the root node is the entire tree; the subtree corresponding to any other node is called is a '''proper subtree''' (in analogy to the term | + | A '''subtree''' is a portion of a tree data structure that can be viewed as a complete tree in itself. Any node in a tree ''T'', together with all the nodes below it, comprise a subtree of ''T''. The subtree corresponding to the root node is the entire tree; the subtree corresponding to any other node is called is a '''proper subtree''' (in analogy to the term proper subset). |
<br/><br/> | <br/><br/> | ||
Revision as of 06:39, 12 May 2009
Begin | ↑ Contents: CS2 | Binary Trees → |
A tree is a finite set of elements called nodes. The set is either empty, or consists of a node called the root together with any number of successors which are also trees (subtrees in this case), which are disjoint from each other and from the root. The roots of the subtrees are called children of the root, and there is an edge from each node to its children, and a node is said to be the parent of its children. A node that has at least one child is called an internal node, and a node that has no children is called a leaf node.
More formally, in computer science, a tree is an acyclic connected graph where each node has a set of zero or more children nodes, and at most one parent node.
Terminology
A node is a structure which may contain a value or a condition or represent a separate data structure or a tree of its own. Each node in a tree has zero or more child nodes two child for binary tree, which are below it in the tree (by convention, trees grow down, not up as they do in nature). A node that has a child is called the child's parent node (or ancestor node, or superior). A node has at most one parent.
The height of a node is the length of the longest downward path to a leaf from that node. 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 depth of the root is 0. This is commonly needed in the manipulation of the various self balancing trees, AVL Trees in particular. Conventionally, the value -1 corresponds to a subtree with no nodes, whereas zero corresponds to a subtree with one node. The height of the tree is 1 more than the depth of the deepest node. All nodes at depth d are said to be at level d.
The topmost node in a tree is called the root node. Being the topmost node, the root node will not have parents. It is the node at which operations on the tree commonly begin (although some algorithms begin with the leaf nodes and work up ending at the root). All other nodes can be reached from it by following edges or links. (In the formal definition, each such path is also unique). In diagrams, it is typically drawn at the top. In some trees, such as heaps, the root node has special properties. Every node in a tree can be seen as the root node of the subtree rooted at that node.
Nodes at the bottommost level of the tree are called leaf nodes. Since they are at the bottommost level, they do not have any children. They are also referred to as terminal nodes.
An internal node or inner node is any node of a tree that has child nodes and is thus not a leaf node.
A subtree is a portion of a tree data structure that can be viewed as a complete tree in itself. Any node in a tree T, together with all the nodes below it, comprise a subtree of T. The subtree corresponding to the root node is the entire tree; the subtree corresponding to any other node is called is a proper subtree (in analogy to the term proper subset).
Paths
If n1, n2, …, nn is a sequence of nodes in the tree such that ni is the parent of ni+1, then this sequence is called a path. The length of the path is the number of edges, which is one less than the number of node: in this case the length of the path is n-1. If there is a path from a node M to a node N, then N is called a descendent of M and M is called an ancestor of N.
Trees
CS2: Data Structures
Theory of Computation - ADT Preliminaries
Linear ADTs - Tree ADTs - Graph ADTs - Unordered Collection ADTs