I am trying to understand time complexity and recurrence relations. Can you explain in detail the time complexity and recurrence relation of the mergesort algorithm and how you come to that answer? Can you also show how the lines of code get you to the answer for time complexity and the recurrence relation? Here is the Mergesort Algorithm code. // C# program for Merge Sort using System;   class GfG {       // Merges two subarrays of []arr.     // First subarray is arr[l..m]     // Second subarray is arr[m+1..r]     static void merge(int[] arr, int l, int m, int r)     {         // Find sizes of two         // subarrays to be merged         int n1 = m - l + 1;         int n2 = r - m;           // Create temp arrays         int[] L = new int[n1];         int[] R = new int[n2];         int i, j;           // Copy data to temp arrays         for (i = 0; i < n1; ++i)             L[i] = arr[l + i];         for (j = 0; j < n2; ++j)             R[j] = arr[m + 1 + j];           // Merge the temp arrays           // Initial indexes of first         // and second subarrays         i = 0;         j = 0;           // Initial index of merged         // subarray array         int k = l;         while (i < n1 && j < n2) {             if (L[i] <= R[j]) {                 arr[k] = L[i];                 i++;             }             else {                 arr[k] = R[j];                 j++;             }             k++;         }           while (i < n1) {             arr[k] = L[i];             i++;             k++;         }           while (j < n2) {             arr[k] = R[j];             j++;             k++;         }     }       // Main function that     // sorts arr[l..r] using     // merge()     static void mergeSort(int[] arr, int l, int r)     {         if (l < r) {               // Find the middle point             int m = l + (r - l) / 2;               // Sort first and second halves             mergeSort(arr, l, m);             mergeSort(arr, m + 1, r);               // Merge the sorted halves             merge(arr, l, m, r);         }     }       // A utility function to     // print array of size n     static void printArray(int[] arr)     {         int n = arr.Length;         for (int i = 0; i < n; ++i)             Console.Write(arr[i] + " ");         Console.WriteLine();     }       // Driver code     public static void Main(String[] args)     {         int[] arr = { 12, 11, 13, 5, 6, 7 };         Console.WriteLine("Given array is");         printArray(arr);         mergeSort(arr, 0, arr.Length - 1);         Console.WriteLine("\nSorted array is");         printArray(arr);     } }

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
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I am trying to understand time complexity and recurrence relations. Can you explain in detail the time complexity and recurrence relation of the mergesort algorithm and how you come to that answer? Can you also show how the lines of code get you to the answer for time complexity and the recurrence relation? Here is the Mergesort Algorithm code.

// C# program for Merge Sort

using System;

 

class GfG {

 

    // Merges two subarrays of []arr.

    // First subarray is arr[l..m]

    // Second subarray is arr[m+1..r]

    static void merge(int[] arr, int l, int m, int r)

    {

        // Find sizes of two

        // subarrays to be merged

        int n1 = m - l + 1;

        int n2 = r - m;

 

        // Create temp arrays

        int[] L = new int[n1];

        int[] R = new int[n2];

        int i, j;

 

        // Copy data to temp arrays

        for (i = 0; i < n1; ++i)

            L[i] = arr[l + i];

        for (j = 0; j < n2; ++j)

            R[j] = arr[m + 1 + j];

 

        // Merge the temp arrays

 

        // Initial indexes of first

        // and second subarrays

        i = 0;

        j = 0;

 

        // Initial index of merged

        // subarray array

        int k = l;

        while (i < n1 && j < n2) {

            if (L[i] <= R[j]) {

                arr[k] = L[i];

                i++;

            }

            else {

                arr[k] = R[j];

                j++;

            }

            k++;

        }

 

        while (i < n1) {

            arr[k] = L[i];

            i++;

            k++;

        }

 

        while (j < n2) {

            arr[k] = R[j];

            j++;

            k++;

        }

    }

 

    // Main function that

    // sorts arr[l..r] using

    // merge()

    static void mergeSort(int[] arr, int l, int r)

    {

        if (l < r) {

 

            // Find the middle point

            int m = l + (r - l) / 2;

 

            // Sort first and second halves

            mergeSort(arr, l, m);

            mergeSort(arr, m + 1, r);

 

            // Merge the sorted halves

            merge(arr, l, m, r);

        }

    }

 

    // A utility function to

    // print array of size n

    static void printArray(int[] arr)

    {

        int n = arr.Length;

        for (int i = 0; i < n; ++i)

            Console.Write(arr[i] + " ");

        Console.WriteLine();

    }

 

    // Driver code

    public static void Main(String[] args)

    {

        int[] arr = { 12, 11, 13, 5, 6, 7 };

        Console.WriteLine("Given array is");

        printArray(arr);

        mergeSort(arr, 0, arr.Length - 1);

        Console.WriteLine("\nSorted array is");

        printArray(arr);

    }

}

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