Tutorial Playlist

Data Structure Tutorial


Arrays in Data Structures: A Guide With Examples

Lesson - 1

All You Need to Know About Two-Dimensional Arrays

Lesson - 2

All You Need to Know About a Linked List in a Data Structure

Lesson - 3

The Complete Guide to Implement a Singly Linked List

Lesson - 4

The Ultimate Guide to Implement a Doubly Linked List

Lesson - 5

The Fundamentals for Understanding Circular Linked List

Lesson - 6

The Ultimate Guide To Understand The Differences Between Stack And Queue

Lesson - 7

Implementing Stacks in Data Structures

Lesson - 8

Your One-Stop Solution for Stack Implementation Using Array

Lesson - 9

Your One-Stop Solution for Queue Implementation Using Array

Lesson - 10

Your One-Stop Solution to Learn Depth-First Search(DFS) Algorithm From Scratch

Lesson - 11

Your One-Stop Solution for Stack Implementation Using Linked-List

Lesson - 12

The Definitive Guide to Understand Stack vs Heap Memory Allocation

Lesson - 13

All You Need to Know About Linear Search Algorithm

Lesson - 14

All You Need to Know About Breadth-First Search Algorithm

Lesson - 15

A One-Stop Solution for Using Binary Search Trees in Data Structure

Lesson - 16

The Best Tutorial to Understand Trees in Data Structure

Lesson - 17

A Complete Guide to Implement Binary Tree in Data Structure

Lesson - 18

A Holistic Look at Using AVL Trees in Data Structures

Lesson - 19

All You Need to Know About Tree Traversal in Data Structure

Lesson - 20

The Best Guide You’ll Ever Need to Understand B-Tree in Data Structure

Lesson - 21

The Best Guide You'll Ever Need to Understand Spanning Tree in Data Structure

Lesson - 22

The Best and Easiest Way to Understand an Algorithm

Lesson - 23

Your One-Stop Solution to Understand Shell Sort Algorithm

Lesson - 24

Your One-Stop Solution to Quick Sort Algorithm

Lesson - 25

The Most Useful Guide to Learn Selection Sort Algorithm

Lesson - 26

Everything You Need to Know About Radix Sort Algorithm

Lesson - 27

Everything You Need to Know About the Counting Sort Algorithm

Lesson - 28

Everything You Need to Know About the Merge Sort Algorithm

Lesson - 29

Insertion Sort Algorithm: One-Stop Solution That Will Help You Understand Insertion Sort

Lesson - 30

Everything You Need to Know About the Bubble Sort Algorithm

Lesson - 31

The Best Guide You’ll Ever Need to Understand Bucket Sort Algorithm

Lesson - 32

Your One-Stop Solution to Understand Recursive Algorithm in Programming

Lesson - 33

The Definitive Guide to Understanding Greedy Algorithm

Lesson - 34

Your One-Stop Solution to Understand Backtracking Algorithm

Lesson - 35

The Fundamentals of the Bellman-Ford Algorithm

Lesson - 36

Your One-Stop Solution for Graphs in Data Structures

Lesson - 37

The Best Guide to Understand and Implement Solutions for Tower of Hanoi Puzzle

Lesson - 38

A Simplified and Complete Guide to Learn Space and Time Complexity

Lesson - 39

All You Need to Know About the Knapsack Problem : Your Complete Guide

Lesson - 40

The Fibonacci Series: Mathematical and Programming Interpretation

Lesson - 41

The Holistic Look at Longest Common Subsequence Problem

Lesson - 42

The Best Article to Understand What Is Dynamic Programming

Lesson - 43

A Guide to Implement Longest Increasing Subsequence Using Dynamic Programming

Lesson - 44

A Holistic Guide to Learn Stop Solution Using Dynamic Programming

Lesson - 45

One Stop Solution to All the Dynamic Programming Problems

Lesson - 46

Understanding the Fundamentals of Binomial Distribution

Lesson - 47

Here’s All You Need to Know About Minimum Spanning Tree in Data Structures

Lesson - 48

Understanding the Difference Between Array and Linked List

Lesson - 49

The Best Article Out There to Understand the B+ Tree in Data Structure

Lesson - 50

A Comprehensive Look at Queue in Data Structure

Lesson - 51

Your One-Stop Solution to Understand Coin Change Problem

Lesson - 52

The Best Way to Understand the Matrix Chain Multiplication Problem

Lesson - 53

Your One-Stop Solution to Learn Floyd-Warshall Algorithm for Using Dynamic Programming

Lesson - 54

The Best Tutorial You'll Ever Need for Queue Implementation Using Linked List

Lesson - 55
Insertion Sort Algorithm: One-Stop Solution That Will Help You Understand Insertion Sort

"Insertion sort algorithm" is one of the simplest and most commonly used sorting algorithms when it comes to the ordering of a deck of cards in everyday life. You insert each element into its proper place in the sorted array using this algorithm. Despite its simplicity, Insertion sort is quite inefficient compared to its allies such as quicksort, and merge sort to name a few.

By the end of this tutorial, you will have a better understanding of the fundamental technicalities of the Insertion sort with all the necessary details along with practical implementations.

What Is the Insertion Sort Algorithm?

Insertion sort algorithm is a basic sorting algorithm that sequentially sorts each item in the final sorted array or list. It is significantly low on efficiency while working on comparatively larger data sets. While other algorithms such as quicksort, heapsort, or merge sort have time and again proven to be far more effective and efficient.

Now, have a look at the working of the Insertion sort algorithm to get a better understanding of the insertion sort.

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How Does Insertion Sort Work?

how does insertion sort work

To sort an array in ascending order, you will follow the steps below:

  1. Iterate through the array from arr[1] to arr[n].
  2. Compare the current element (key) to one that came before it.
  3. If the data at the current index is less than the data at the previous index, you will compare it to the element before it.
  4. You will shift bigger elements to the next index to make space for swapped elements, and then you will iterate the same steps again to sort the complete array.

And this is how the Insertion sort algorithm works. Now implement this algorithm through a simple C++ code.

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How to Implement the Insertion Sort Algorithm?

You will be provided with a one-dimensional array of elements {6, 5, 4, 2, 3}. You have to write a code to sort this array using the insertion sort algorithm. The final array should come out to be as {2, 3, 4, 5, 6}.


//A C++ program to sort an array using insertion sort

#include <bits/stdc++.h>

using namespace std;

//A Function to sort an array using insertion sort

void insertion_sort(int array[], int size)


int i, key, k;

for (i = 1; i < size; i++)


key = array[i];

k = i - 1;

// Move Ar[0..i-1] elements, 

//which are larger than the key, 

//to one place over their present location

while (k >= 0 && array[k] > key)


array[k + 1] = array[k];

k = k - 1;


array[k + 1] = key;



// A function to print the array of size n

void print_array(int array[], int size)


int i;

for (i = 0; i < size; i++)

cout << array[i] << " ";

cout << endl;


/* Driver code */

int main()


int arr[] = { 6, 5, 4, 2, 3 };

int size = sizeof(arr) / sizeof(arr[0]);

cout<<"Array before sorting:\n";

print_array(arr, size);

insertion_sort(arr, size);

cout<<"\nArray after sorting:\n";

print_array(arr, size);

return 0;



You have now explored the working of insertion sort with a code. Now, look at some of the advantages of the Insertion sort.

What Are the Advantages of the Insertion Sort?

You will now look at a few major benefits of using insertion sort and a few scenarios where insertion sort is proven to be delivering the best performance.

  • It, like other quadratic sorting algorithms, is efficient for small data sets.
  • It just necessitates a constant amount of O(1) extra memory space.
  • It works well with data sets that have been sorted in a significant way.
  • It does not affect the relative order of elements with the same key.

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What Are the Disadvantages of the Insertion Sort?

Despite its simplicity and effectiveness over smaller data sets, Insertion sort does a few downfalls. This tutorial will now address a few major drawbacks which you should consider before you implement insertion sort in real-time

  • Insertion sort is inefficient against more extensive data sets
  • The insertion sort exhibits the worst-case time complexity of O(n2)
  • It does not perform well than other, more advanced sorting algorithms

With this, you have come to an end of this tutorial. You will now look at what could be your next steps to master sorting algorithms.

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Next Steps

Your next stop in mastering data structures should be the selection Sort Algorithm. The selection sort algorithm divides the list into two parts, with the sorted half on the left and the unsorted half on the right, using in-place comparisons.

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If you have any questions or require clarification on this "Merge Sort Algorithm" tutorial, please leave them in the comments section below. Our expert team will review them and respond as soon as possible.

About the Author

Vaibhav KhandelwalVaibhav Khandelwal

Vaibhav Khandelwal is a proactive tech geek who's always on the edge of learning new technologies. He is well versed in competitive programming and possess sound knowledge of web development. He likes to read fictional and sci-fi novels and likes to play strategy games like chess.

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