### binary search tree insert search and display

Binary Search Tree is a simple data structure which is very often used to solve a lot of different problems based on searching and sorting, and also it is a very popular topic for programming coding challenges and interview questions.
Binary Search Tree is a rooted binary tree. It is basically a collection of nodes which are linked to each other. now, you may ask what is a node? Each element of the binary tree is a node that has mainly 3 fields,

1. data or element field

Each node in the binary tree has the following properties
1. Data of the left node is less than the parent node
2. Data of the right node is greater than the parent node.

Below is an example image for a binary search tree

It can be seen in the image above that the data in the left child node is less than the data of the parent node and data of the right child node is greater than the parent node. For example, let us consider 8 as the parent node, then we can see that all the nodes that are to the left of it have a value less than 8 and all the nodes to the right of parent node have a value greater than 8.

There are a lot of advantages of using the binary search tree data structure, they are related to searching, sorting, using them as priority queues, etc.

This post is an introductory post for Binary search tree so for this post the following operations implemented in the code below.

1. Insertion of an element in a Binary search tree.
2. Searching for an element in BST.
3. Display Binary search tree in Inorder form.
4. Display Binary search tree in Postorder form.
5. Display Binary search tree in Preorder form.

In order to traverse and display a binary tree, there are 3 types of traversals which are as follows,

1. Inorder Traversal: In this type of traversal we print & traverse to the left subtree first, then print the parent node and then print & traverse the right subtree.
2. Preorder Traversal: In this type of traversal we print the parent node and then print & traverse the left and right subtree respectively.
3. Postorder Traversal: In this type of traversal we print & traverse the left and right subtrees first and then print the parent node.

### C++ Program

You might also be interested in

Minimum & Maximum Element in BST

Binary Search Tree in Python
Binary Search Tree in C++
Display Leaf Nodes of BST
Height of Binary Search Tree

### Infix to Prefix conversion using Stack

This post is about conversion of Infix expression to Prefix conversion. For this conversion we take help of stack data structure, we need to push and pop the operators in and out of the stack.

Infix expressions are the expressions that we normally use,eg. 5+6-7; a+b*c etc. Prefix expressions are the expressions in which the 2 operands are preceded by the operator eg. -+567 , +a*bc etc.

This method is very similar to the method that we used to convert Infix to Postfix but the only difference is that here we need to reverse the input string before conversion and then reverse the final output string before displaying it.

NOTE: This changes one thing that is instead of encountering the opening bracket we now first encounter the closing bracket and we make changes accordingly in our code.

So, to convert an infix expression to a prefix expression we follow the below steps
(we have 2 string, 1st is the input infix expression string 2nd is the output string which is empty initially)

We first revers…

Hashing is a technique used for storing , searching and removing elements in almost constant time. Hashing is done with help of a hash function that generates index for a given input, then this index can be used to search the elements, store an element, or remove that element from that index.

A hash function is a function that is used to map the data elements to their position in the data structure used. For example if we use an array to store the integer elements then the hash function will generate position for each element so that searching, storing and removing operation on the array can be done in constant time that is independent of the number of elements in the array. For better look at the example below.

now we face a problem if for 2 numbers same position is generated example consider elements 1 and 14

1 % 13 = 1

14 % 13 = 1

so when we get 1 we store it at the first position, but when we get 14 we see that the position 1 is already taken, this is a case of collision.

Inorder…