Skip to main content

Merge Sort | Algorithm | MyCodingNetwork

Merge Sort

Hi there, I am back with another article on one of the most important algorithms in the world of DSA. In this article we would be covering Merge Sort and talk about its various aspects. So, without wasting much time let's jump into the topic right away.

Merge sort is another type of sorting algorithm whose time complexity is O(N*logN). The worst, average and best time complexity of merge sort always remains same, that is, O(N*logN). You must be thinking why the time complexity is same for all cases. Well, the answer to that we will get as we move further in our discussion.

It works on divide and conquer technique, where the given array is divided into smaller somebodies of two halves and then sorting is done.

Source Code:

conquer() function:


divide( ) function:



main( ) function:



Output:

#1 

In the above example, user first enters the length of the array, and then the array elements. The highlighted part are the elements of array after sorting.

#2
Let's take another example.

How it works:


Working:

In the source code, it first takes the array length and its element as input from the user and then divide( ) function is called/invoked on line 73. As shown above, inside the divide( ) function the array is being continuously divided recursively into two halves.

After this, conquer( ) function is used to sort the given sub-arrays. This process takes place inside the function by creating L[ ] and R[ ] integer arrays where the elements of first half is stored in L[ ] array and similarly for second-half R[ ] array is used. 

In further steps, the elements of both the arrays are compared as shown on line 22(L[i]<=R[j]) of the code and the elements are then placed inside the bigger array A[ ](out of which the two subparts are being extracted) according to the requirement, that is, either ascending or descending order.


Why Best, Average and Worst Time Complexity same?

Did you get the answer? If not, then try to understand the methodology of this code. 

See, neither the divide function nor the conquer function depends on the order of elements. The divide function will keep on dividing the array even if the array is sorted. Similarly, the conquer function would traverse and check each element within the given range irrespective of the order in which the elements are arranged (sorted or unsorted).


Hope you liked this explanation, for any doubt/feedback/improvements/corrections you can comment down in the comment section.

Popular posts from this blog

Pattern 6 | Java | MyCodingNetwork | Alok Tripathi (Code 8)

Problem Statement: Write a program to make a square and mark out its diagonals. Accept the length as input from the user and give output in the following manner: And ( In simple words, we have printed stars (*) on the boundary positions of the matrix and on the centre positions of the matrix we have printed blank space( ) )   THE CODE: Sample Output: In the above program, two int variables r to accept the length of square as input. On line 7, following statement is used to accept the input from the user: int r = sc . nextInt ();   For taking the input Scanner class has been used, more about Scanner class Algorithm: Two for loops are defined: ·         First for loop with counter variable i has initial value 1, conditional statement i less than or equal to r and an updating statement i++ . ·         Inside the first loop there is a second for loop, with counter variable j has ini...

Pattern 1 | Java

Problem Statement: Write a program to draw the following pattern of NxN(where N is the input): * * * * * * * * * * * * * * * * * * * * * * * * * (here, N=5) THE CODE Output: Here, the input is 8 Simplification : In the above problem, two for loops are used: 1. The first for loop is having i as counter variable with  initial value of 1 and ending value of 10 with an updation statement i++. 2. The second for loop is having j as counter variable with initial value of 1 and ending value of 10 with an updation statement j++. The second  for loop is used to print  * in the respective column (the value of j represents the column number). It is having a print statement System.out.println("* ") to print * in each column(for convenience, I've added a space for better visibility of columns in the output). The first for loop is used to define rows( the value of i represents the row number). It is having a print statement System.out.print() to change rows each time the second for ...

Exploring Uninformed Search in Artificial Intelligence: Basics and Applications

  In artificial intelligence (AI), search algorithms are essential for solving a variety of problems, from navigating a maze to scheduling tasks. Uninformed search, also known as blind search, is a fundamental category of search techniques where the algorithm has no additional information about the states beyond what is provided in the problem definition to guide the search. This page delves into the basics of uninformed search algorithms, their types, and their applications in AI. Understanding Uninformed Search Uninformed search algorithms explore the search space without any guidance on which paths might lead to the goal more efficiently. They rely solely on the information available from the initial problem setup, such as the start state, goal state, and possible actions. This approach contrasts with informed search algorithms, which utilize heuristics to make more educated guesses about the best path to take. Types of Uninformed Search Algorithms   Several uninformed se...