Saturday, 1 June 2013

Binary Tree Java Program

Introduction

We extend the concept of linked data structures to structure containing nodes with more than one self-referenced field. A binary tree is made of nodes, where each node contains a "left" reference, a "right" reference, and a data element. The topmost node in the tree is called the root.
Every node (excluding a root) in a tree is connected by a directed edge from exactly one other node. This node is called a parent. On the other hand, each node can be connected to arbitrary number of nodes, called children. Nodes with no children are called leaves, or external nodes. Nodes which are not leaves are called internal nodes. Nodes with the same parent are called siblings.
  
More tree terminology:
  • The depth of a node is the number of edges from the root to the node.
  • The height of a node is the number of edges from the node to the deepest leaf.
  • The height of a tree is a height of the root.
  • A full binary tree.is a binary tree in which each node has exactly zero or two children.
  • A complete binary tree is a binary tree, which is completely filled, with the possible exception of the bottom level, which is filled from left to right.
A complete binary tree is very special tree, it provides the best possible ratio between the number of nodes and the height. The height h of a complete binary tree with N nodes is at most O(log N). We can easily prove this by counting nodes on each level, starting with the root, assuming that each level has the maximum number of nodes:
n = 1 + 2 + 4 + ... + 2h-1 + 2h = 2h+1 - 1
Solving this with respect to h, we obtain
h = O(log n)
where the big-O notation hides some superfluous details.

Advantages of trees

Trees are so useful and frequently used, because they have some very serious advantages:
  • Trees reflect structural relationships in the data
  • Trees are used to represent hierarchies
  • Trees provide an efficient insertion and searching
  • Trees are very flexible data, allowing to move subtrees around with minumum effort

Traversals

A traversal is a process that visits all the nodes in the tree. Since a tree is a nonlinear data structure, there is no unique traversal. We will consider several traversal algorithms with we group in the following two kinds
  • depth-first traversal
  • breadth-first traversal
There are three different types of depth-first traversals, :
  • PreOrder traversal - visit the parent first and then left and right children;
  • InOrder traversal - visit the left child, then the parent and the right child;
  • PostOrder traversal - visit left child, then the right child and then 

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