Welcome, aspiring programmer! Today's topic is Merge Sort. Merge Sort is a sorting technique similar to arranging a deck of shuffled cards in order. But for data on an Internet scale, Merge Sort outperforms your regular techniques. Today, we'll explore Merge Sort, code it in C#
, and analyze its speed. Ready? Let's get started!
In computer science, Merge Sort is a popular method to sort elements. Merge Sort uses the same 'divide-and-conquer' strategy for sorting as the familiar Quick Sort algorithm. In the three steps of Merge Sort:
- Split the array into halves.
- Sort each half separately.
- Merge the sorted halves back together.
We will start by building code for merging two sorted parts. The merge process makes two halves play sort and seek. It compares elements from two halves and merges them so that the resulting list is sorted as well.
Let's code a Merge()
function in C#
that will do just that. Note that the final variant of the merge sort function will do every operation "in place," meaning there will not be actual two arrays; we will operate parts of one array. Bearing this in mind, let's implement the Merge
function to take just one array and treat its parts like separate arrays.
C#1void Merge(int[] arr, int left, int mid, int right) 2{ 3 int n1 = mid - left + 1; // Find number of elements in the left array 4 int[] Left = new int[n1]; // Define left array 5 6 int n2 = right - mid; // Find the number of elements in the right array 7 int[] Right = new int[n2]; // Define right array 8 9 // Let's fill in these arrays 10 for (int i = 0; i < n1; i++) 11 Left[i] = arr[left + i]; 12 for (int j = 0; j < n2; j++) 13 Right[j] = arr[mid + 1 + j]; 14}
So far, we've divided our original list into two halves, Left
and Right
.
Now, we'll sort and merge these halves:
C#1 int i = 0, j = 0; 2 int k = left; 3 while (i < n1 && j < n2) 4 { 5 if (Left[i] <= Right[j]) 6 { 7 arr[k] = Left[i]; 8 i++; 9 } 10 else 11 { 12 arr[k] = Right[j]; 13 j++; 14 } 15 k++; 16 } 17}
Seemingly tricky, the code is very straightforward:
We place two pointers, i
and j
, at the beginning of the Left
and Right
arrays.
We choose the smaller element, put it in the final array arr
, and move the corresponding pointer further.
We keep doing this until one of the pointers reaches the end of its array.
We stop the process when one of the pointers reaches the end of its array, but some elements could be left in the other array.
To handle this, let's copy the remaining elements of both arrays (if any) to the end of the resulting arr
array.
C#1 2 // Copy remaining elements of Left[] if any 3 while (i < n1) 4 { 5 arr[k] = Left[i]; 6 i++; 7 k++; 8 } 9 10 // Copy remaining elements of Right[] if any 11 while (j < n2) 12 { 13 arr[k] = Right[j]; 14 j++; 15 k++; 16 }
The merge section is completed. It successfully merges two halves back together in sorted order.
Now, let's implement the method to divide the array into two halves. Coding-wise, we'll need to define a Sort()
method to split the array and manage the merge process. We will split the array and its halves recursively until we end up with small arrays of just one element, which are naturally sorted! Next, we will merge these arrays back together into one big sorted array.
Let's start building the Sort()
method. Initially, we'll handle the splitting part:
C#1void Sort(int[] arr, int left, int right) 2{ 3 if (left < right) 4 { 5 int mid = (left + right) / 2; // Finding the midpoint 6 7 } 8}
Now, we can split our list into two halves, but they still need to be sorted.
Next, we need to sort these halves and merge them together:
C#1 Sort(arr, left, mid); // Sorting the left half 2 Sort(arr, mid + 1, right); // Sorting the right half 3 Merge(arr, left, mid, right); // Merging the sorted halves 4 } 5}
Phew! We've now implemented our Merge Sort algorithm in C#
.
Here is the full code for the Merge Sort algorithm implemented in C#:
C#1using System; 2 3class MergeSortExample 4{ 5 // Method to divide and sort the array 6 static void Sort(int[] arr, int left, int right) 7 { 8 if (left < right) 9 { 10 int mid = (left + right) / 2; 11 12 // Recursively sorting the first and second halves 13 Sort(arr, left, mid); 14 Sort(arr, mid + 1, right); 15 16 // Merging the sorted halves 17 Merge(arr, left, mid, right); 18 } 19 } 20 21 // Method to merge two halves 22 static void Merge(int[] arr, int left, int mid, int right) 23 { 24 int n1 = mid - left + 1; 25 int n2 = right - mid; 26 27 int[] Left = new int[n1]; 28 int[] Right = new int[n2]; 29 30 // Fill the left and right arrays 31 for (int i = 0; i < n1; i++) 32 Left[i] = arr[left + i]; 33 for (int j = 0; j < n2; j++) 34 Right[j] = arr[mid + 1 + j]; 35 36 int i = 0, j = 0; 37 int k = left; 38 while (i < n1 && j < n2) 39 { 40 if (Left[i] <= Right[j]) 41 { 42 arr[k] = Left[i]; 43 i++; 44 } 45 else 46 { 47 arr[k] = Right[j]; 48 j++; 49 } 50 k++; 51 } 52 53 // Copy remaining elements of Left[] if any 54 while (i < n1) 55 { 56 arr[k] = Left[i]; 57 i++; 58 k++; 59 } 60 61 // Copy remaining elements of Right[] if any 62 while (j < n2) 63 { 64 arr[k] = Right[j]; 65 j++; 66 k++; 67 } 68 } 69}
In the computing world, performance matters. The less time it takes for a sorting algorithm to run, the better. Merge Sort shows good performance with the time complexity of O(n log n)
, similar to sorting a huge deck of cards quickly. Thus, it excels when dealing with massive data sets.
Merge Sort is consistent. It's like a reliable late-night tutor that offers predictable performance, regardless of the initial order of the data input. It mimics a reliable friend who will not let down expectations.
However, it tends to use extra memory, creating new arrays during the merge process.
Great job! We've broken down Merge Sort and coded it in C#
. Next up, we have some exciting hands-on exercises for you. Ready to put what you've learned into practice? Let's dive into the fun part! Let's get coding!