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print leaf nodes of binary search tree

Leaf nodes of binary tree are the nodes with no children or no subtrees.
They have both left and right links as null.


In the above image nodes 1,4 ,7 ,13 have no sub-trees hence they are the leaf nodes.

Leaf nodes can be found easily by traversing the tree in inorder way and the printing the nodes that have no left or right subtrees.


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height of binary search tree

Height of the binary search tree is defined as the number of nodes in the longest path from the root node to leaf node.



In the above image one of the longest paths is 8 --> 10 --> 14 --> 13, containing 4 nodes hence the height of the binary search tree is 4. One thing that should be noted is that a tree with only root node has height 1 and not 0.
In the following the height of the left and right subtree is compared and the larger value is returned.

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Singly Linked List
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Binary Search Tree in C++
Insert ,Search and Display Binary Search Tree
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Linked list in Python

Binary search tree in cpp

Binary Search Tree is a rooted binary tree. Its subtrees have certain properties. Each element of the binary tree is a node that has mainly 3 fields,

data or element fieldleft link right linkFor each node in a binary search tree, the data of the left node is less than the parent node and data of the right node is greater than the parent node.



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.
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.
To know more about binary search tree click here.
The following program has the following operations implemented isEmpty() : method that checks if the tree is empty.getRoot() :  method that returns the root element of the binary search tree.insert() : Insertion in Binary search tree.search() : Method for Searching a element in…

binary search tree in python

Binary Search Tree is a rooted binary tree. Its subtrees have certain properties. Each element of the binary tree is a node that has mainly 3 fields,

data or element fieldleft link right link For each node in binary search tree , the data of the left node is less than the parent node and data of the right node is greater than the parent node.



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.
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.
To know more about binary search tree click here.
The following program has the following operations implemented isEmpty() : method that checks if the tree is empty.getRoot() :  method that retuens the root element of the binary search tree.insert() : Insertion in Binary search tree.search() : Method for Searching a el…

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,


data or element fieldleft link right link
Each node in the binary tree has the following properties
Data of the left node is less than the parent nodeData 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 …

gcd using euclids algorithm

GCD stands for greatest common divisor. GCD of two numbers is the greatest number that divides both numbers without leaving a remainder. Euclidean algorithm for finding the gcd is based on the principle that the gcd of two numbers does not change if the larger number is replaced by its difference with the smaller number.
Let us consider the example of 206 and 40, we find that 2 is the gcd of 206 and 40 also according to the above statement the gcd of 166 (206 - 40) and 40 is also 2.

To know more about GCD click here.

In the below program we follow the below steps

Step 1: In each iteration calculate the quotient Step 2: Then subtract the product of quotient and the smaller number from the bigger numberStep 3: Replace the bigger number by the remainder. Step 4: Repeat above steps until the smaller number becomes 0





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Finding factorial of a num…

Singly Linked List

A linked list is a simple linear data structure formed by a collection of data elements called nodes. Each node consists of a data element and link field.





There is a head node that points to the starting of the linked list.
this diagram shows a simple representation of the linked list.






A linked list can be used to implement stacks, queues, list, associative arrays, etc. 
Unlike arrays linked lists are not stored in contagious memory locations rather they are stored at any empty place in memory and the address of the next node is stored in the link field. Also, you don't need to declare the size of the linked list at the time of initialization you can dynamically keep adding elements to the linked list.
Click for complete information on Linked List 
The following implementation of the linked list has the following methods implemented :
Method to add an element at the start of the ListMethod to add an element at the end of the ListMethod to display the Linked List Method to delete an elemen…

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Stack implementation using array

A stack is a data structure it serves as a collection of elements. It has 2 principle operation push and pop. The push operation pushes the element on the top and the pop operation removes the element on the top. This can be seen in the below image.


Stack works on the principle of  Last In First Out or LIFO i.e the element that is entered last is removed first. Stacks can be implemented using arrays as well as linked list. There are a lot of applications of Stacks like RecursionBacktracking Memory management Activation records etcTo know more about Stacks click here 

The following program is to implement a stack using an array with maximum size of 20.


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Linked List in python
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Finding the next Smallest Palindrome
Finding factorial of a number
Bar Graph in C using dda Line generation algorithm

bar graph in c using dda algorithm

DDA line generation algorithm is used to draw lines by finding the points of the line using arithmetic operations on integers and floating point numbers.
The following program is to draw a bar graph using dda line algorithm.


To know all about the algorithm click here

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OUTPUT




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factorial of a number

Factorial of a number is equal to the product of the number and all the positive numbers below it.
Factorial of a number is denoted as n!.
for example Factorial of 7 is denoted as 7!.
7! = 7*6*5*4*3*2*1
7! = 5040

also 0! is 1 according to the convention of empty product.
To know more about factorials click here


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Linked List in PythonLinked List in JavaProgram to find Armstrong NumbersProgram to find next smallest Palindromefinding square root of a number using Babylonian method

Program to find Armstrong numbers

Armstrong numbers are numbers such that if we take sum of all the digits of the number raised to 3 it equal to the original number.
Armstrong numbers can also be called as 3-narcissistic numbers,as we raise all the digits to 3.
Let us take a quick example 


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Singly Linked List
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