In graph theory, an m-ary tree (for nonnegative integers m) (also known as n-ary, k-ary or k-way tree) is an arborescence (or, for some authors, an ordered tree) in which each node has no more than m children. A binary tree is the special case where m = 2, and a ternary tree is another case with m = 3 that limits its children to three.
A full m-ary tree is an m-ary tree where within each level every node has 0 or m children.
A complete m-ary tree (or, less commonly, a perfect m-ary tree) is a full m-ary tree in which all leaf nodes are at the same depth.
For an m-ary tree with height h, the upper bound for the maximum number of leaves is .
The height h of an m-ary tree does not include the root node, with a tree containing only a root node having a height of 0.
The height of a tree is equal to the maximum depth D of any node in the tree.
The total number of nodes in a perfect m-ary tree is , while the height h is
By the definition of Big-Ω, the maximum depth
The height of a complete m-ary tree with n nodes is .
The total number of possible m-ary tree with n nodes is (which is a Catalan number).
tree traversal
Traversing a m-ary tree is very similar to traversing a binary tree. The pre-order traversal goes to parent, left subtree and the right subtree, and for traversing post-order it goes by left subtree, right subtree, and parent node. For traversing in-order, since there are more than two children per node for m > 2, one must define the notion of left and right subtrees. One common method to establish left/right subtrees is to divide the list of children nodes into two groups. By defining an order on the m children of a node, the first nodes would constitute the left subtree and nodes would constitute the right subtree.
Using an array for representing a m-ary tree is inefficient, because most of the nodes in practical applications contain less than m children. As a result, this fact leads to a sparse array with large unused space in the memory.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
The students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing algorithms, elementary data structures, ma
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.
Given a large collection of tree-structured objects (e.g., XML documents), the similarity join finds the pairs of objects that are similar to each other, based on a similarity threshold and a tree edit distance measure. The state-of-the-art similarity join ...
Assoc Computing Machinery2015
, ,
Phasor measurement units (PMUs) deployed to monitor the state of an electrical grid need to be patched from time to time to prevent attacks that exploit vulnerabilities in the software. Applying some of these patches requires a PMU reboot, which takes the ...
2017
We introduce the first binary search tree algorithm designed for speculative executions. Prior to this work, tree structures were mainly designed for their pessimistic (non-speculative) accesses to have a bounded complexity. Researchers tried to evaluate t ...