# Field in Tree Data Structure

A field in a tree data structure is a section of the tree that contains data. Fields are usually arranged in a hierarchical structure, with each field containing the data pertaining to a particular branch of the tree.

A field can contain any type of data, including integers, strings, floating-point numbers, and other data structures. Fields are often associated with different nodes in the tree.

For instance, a field in a binary tree might contain the value of a node, while a field in a B-tree might contain the address of a node. Fields can also be used to store data that is related to the structure of the tree.

For instance, a field might contain the height of a tree, the total number of nodes, or the number of children a node has. Fields are typically accessed using pointers or references.

This allows the data stored in the field to be quickly accessed and manipulated. For instance, a field might be used to store a pointer to a node in the tree, allowing the data associated with that node to be quickly found.

Fields are typically accessed using pointers or references. This allows the data stored in the field to be quickly accessed and manipulated. For instance, a field might be used to store a pointer to a node in the tree, allowing the data associated with that node to be quickly found.

Fields are commonly used in tree data structures to store data associated with the structure of the tree. By using fields, trees can be quickly searched and traversed without having to perform expensive traversal operations. Fields can also be used to store data associated with specific nodes, allowing for fast access to the data stored in those nodes.

Fields are also useful for organizing data in a tree structure. By using fields, data can be logically grouped together, making it easier to find and manipulate specific data. By using fields, data can also be easily sorted and searched, enabling the data to be quickly located and manipulated. Fields can also be used to store custom information, such as metadata, associated with the tree structure, making it easier to find and manipulate specific data.

Overall, fields are an important part of tree data structures, as they allow for the storage and manipulation of data associated with the structure of the tree. Fields are also useful for organizing data, enabling the data to be quickly found and manipulated. Finally, fields can also be used to store custom information, such as metadata, associated with the tree structure, making it easier to find and manipulate specific data.

Fields are an essential component of tree data structures, as they enable data to be quickly accessed and manipulated. By using fields, data can be logically grouped together and quickly searched, enabling the data to be quickly located and manipulated. Additionally, fields can also be used to store custom information, such as metadata, associated with the tree structure, making it easier to find and manipulate specific data.

Java Program for the implementation of the Binary Tree Data Structure having Fields.

```
public class BinarySearchTree {
// A Node of the Binary Tree is represented.
public static class Node {
int data;
Node left;
Node right;
public Node (int data) {
// Data should be assigned to the new node, and the left and right children should be set to null.
this. data = data;
this. left = null;
this. right = null;
}
}
// Symbolize the binary tree's root
public Node root;
public BinarySearchTree ( ) {
root = null;
}
// Given a number, factorial () will determine its factorial.
public int factorial (int num) {
int fact = 1;
if (num == 0)
return 1;
else {
while (num > 1) {
fact = fact * num;
num --;
}
return fact;
}
}
// By computing the Catalan Number for the specified key, numberOfBST () will determine the total number of feasible BST.
public int numberOfBST (int key) {
int cNumber = factorial (2 * key) / (factorial (key + 1) * factorial (key));
return cNumber;
}
public static void main (String [ ] args) {
BinarySearchTree b1 = new BinarySearchTree ( );
// Show the total number of binary search trees that can be used with the key
System.out.println("Total number of possible Binary Search Trees with given key: " + bt. numberOfBST (5));
}
}
```

In the above program of the Binary Search Tree, the fields of the Binary Search Tree is the b1 node.

Another java program using Trees which has fields of the tree data structure.

```
import java. util. LinkedList;
import java. util. Queue;
public class DeleteNode
{
// A node in a binary tree has a key, a pointer to its left child, and a pointer to its right child.
static class Node
{
int key;
Node left, right;
// Constructor
Node (int key)
{
this. key = key;
left = null;
right = null;
}
}
static Node root;
static Node temp = root;
// The below method shows the implementation of the inorder traversal of the tree data structure in the recursive way.
static void inorderTraversal (Node temp)
{
if (temp == null)
return;
inorderTraversal (temp. left);
System. out. print (temp. key + " ");
inorderTraversal (temp. right);
}
// To delete the deepest entry in a binary tree using this function
static void deleteDeepestNode (Node root, Node delNode)
{
Queue < Node > q1 = new LinkedList < Node > ( );
q1. add (root);
Node temp = null;
// until the final node, perform level order traverse.
while (! q1. isEmpty ( ))
{
temp = q1. peek ( );
q1. remove ( );
if (temp == delNode)
{
temp = null;
return;
}
if (temp. right != null)
{
if (temp. right == delNode)
{
temp. right = null;
return;
}
else
q1. add (temp. right);
}
if (temp. left != null)
{
if (temp. left == delNode)
{
temp. left = null;
return;
}
else
q1. add (temp. left);
}
}
}
// Function to remove a given binary tree member
static void delete (Node root, int key)
{
if (root == null)
return;
if (root. left == null &&
root. right == null)
{
if (root. key == key)
{
root = null;
return;
}
else
return;
}
Queue < Node > q1 = new LinkedList < Node > ( );
q1. add (root);
Node tempNd = null, keyNode = null;
// until the key and last node are found, perform level order traverse.
while (! q2. isEmpty ( ))
{
temp = q2. peek ();
q2. remove ();
if (temp. key == key)
keyNode = temp;
if (temp. left != null)
q. add (temp. left);
if (temp. right != null)
q. add (temp. right);
}
if (keyNode != null)
{
int x = temp. key;
deleteDeepestNode (root, temp);
keyNode. key = x;
}
}
// Driver code
public static void main (String args [ ])
{
root = new Node (10);
root.left = new Node(11);
root.left.left = new Node(7);
root.left.right = new Node(12);
root.right = new Node(9);
root.right.left = new Node(15);
root.right.right = new Node(8);
System.out.print("Inorder traversal before deletion: ");
inorder(root);
//node to delete
int key = 7;
delete(root, key);
System.out.print("\nInorder traversal after deletion: ");
inorder(root);
}
}
```