Merge Sort

import java.util.*;

class Solution {
    private static void merge(int[] arr, int low, int mid, int high) {
        ArrayList<Integer> temp = new ArrayList<>();
        int left = low;
        int right = mid + 1;

        while (left <= mid && right <= high) {
            if (arr[left] <= arr[right]) {
                temp.add(arr[left]);
                left++;
            } else {
                temp.add(arr[right]);
                right++;
            }
        }

        while (left <= mid) {
            temp.add(arr[left]);
            left++;
        }

        while (right <= high) {
            temp.add(arr[right]);
            right++;
        }

        for (int i = low; i <= high; i++) {
            arr[i] = temp.get(i - low);
        }
    }

    public static void mergeSort(int[] arr, int low, int high) {
        if (low >= high) return;
        int mid = (low + high) / 2;
        mergeSort(arr, low, mid);
        mergeSort(arr, mid + 1, high);
        merge(arr, low, mid, high);
    }
}

public class tUf {
    public static void main(String args[]) {
        Scanner sc = new Scanner(System.in);
        int n = 7;
        int arr[] = { 9, 4, 7, 6, 3, 1, 5 };
        System.out.println("Before sorting array: ");
        for (int i = 0; i < n; i++) {
            System.out.print(arr[i] + " ");
        }
        System.out.println();
        Solution.mergeSort(arr, 0, n - 1);
        System.out.println("After sorting array: ");
        for (int i = 0; i < n; i++) {
            System.out.print(arr[i] + " ");
        }
        System.out.println();
    }
}

import matplotlib.pyplot as plt

# Example data points: input sizes and their corresponding execution times
input_sizes = [1000, 5000, 10000, 50000, 100000]
execution_times_quick = [1.8, 9.5, 21.3, 110.7, 250.3]  # Replace these with actual results

plt.plot(input_sizes, execution_times_quick, marker='o', linestyle='-', color='r', label='Quick Sort')
plt.title('Quick Sort Time Complexity')
plt.xlabel('Input Size (n)')
plt.ylabel('Execution Time (ms)')
plt.grid(True)
plt.legend()
plt.show()