# Java – Sorting Algorithms

``` Complexity Quicksort Mergesort Heapsort Time Complexity O(nlogn) O(nlogn) O(nlogn) Space Complexity O(1) O(n) Could be O(1) Quicksort Quicksort is similar to MergeSort in that the sort is accomplished by dividing the array into two partitions and then sorting each partition recursively. In Quicksort, the array is partitioned by placing all items smaller than some pivot item before that item and all items larger than the pivot item after it. There are many different versions of Quicksort that pick pivot in different ways. Always pick first element as pivot. Always pick last element as pivot. Pick a random element as pivot. Pick median as pivot. Implement Quicksort in Java using Arrays (Takes the last element as pivot) public class QuickSortArray { private int partition (int arr[], int low, int high) { int pivot = arr[high]; int i = low - 1; for (int j=low; j<high; j++) { // If current element is smaller than or equal to pivot if (arr[j] < pivot) { i++; //swap arr[i] and arr[j] int temp1 = arr[i]; arr[i] = arr[j]; arr[j] = temp1; } } //swap arr[i+1] and arr[high] (pivot) int temp2 = arr[i+1]; arr[i+1] = arr[high]; arr[high] = temp2; return i+1; //the position of pivot } public void quickSort (int[] arr, int low, int high) { if (low < high) { //pi is partitioning index int pi = partition (arr, low, high); // recursively sort elements before partition and after partition quickSort (arr, low, pi-1); quickSort (arr, pi+1, high); } } } Implement Quicksort in Java using LinkedList (Takes the median as pivot) public class QuickSortList { public ListNode sortList(ListNode head) { if (head == null || head.next == null) { return head; } ListNode mid = findMedian(head); // O(n) ListNode leftDummy = new ListNode(0), leftTail = leftDummy; ListNode rightDummy = new ListNode(0), rightTail = rightDummy; ListNode middleDummy = new ListNode(0), middleTail = middleDummy; while (head != null) { if (head.val < mid.val) { leftTail.next = head; leftTail = head; } else if (head.val > mid.val) { rightTail.next = head; rightTail = head; } else { middleTail.next = head; middleTail = head; } head = head.next; } leftTail.next = null; middleTail.next = null; rightTail.next = null; ListNode left = sortList(leftDummy.next); ListNode right = sortList(rightDummy.next); return concat(left, middleDummy.next, right); } private ListNode findMedian(ListNode head) { ListNode slow = head, fast = head.next; while (fast != null && fast.next != null) { slow = slow.next; fast = fast.next.next; } return slow; } private ListNode concat(ListNode left, ListNode middle, ListNode right) { ListNode dummy = new ListNode(0), tail = dummy; tail.next = left; tail = getTail(tail); tail.next = middle; tail = getTail(tail); tail.next = right; tail = getTail(tail); return dummy.next; } private ListNode getTail(ListNode head) { if (head == null) { return null; } while (head.next != null) { head = head.next; } return head; } } Mergesort Mergesort is based on divide-and-conquer paradigm. It involves the following three steps: Divide the array into two (or more) subarrays. Sort each subarray (Conquer). Merge them into one. Implement Mergesort in Java using Arrays public class MergeSortArray { public void sortArray (int[] arr, int left, int right) { if (left < right) { int mid = left + (right - left)/2; sortArray (arr, left, mid); sortArray (arr, mid+1, right); mergeArray (arr, left, mid, right); } } private void mergeArray (int[] arr, int left, int mid, int right) { int n1 = mid - left + 1; int n2 = right - mid; int[] L = new int[n1]; int[] R = new int[n2]; for (int i=0; i < n1; i++) { L[i] = arr[left + i]; } for (int j=0; j < n2; j++) { R[j] = arr[mid + 1 + j]; } /* Merge the temp arrays */ // Initial indexes of first and second subarrays int i = 0, j = 0; // Initial index of merged subarry array int k = left; while (i < n1 && j < n2) { if (L[i] <= R[j]){ arr[k] = L[i]; i++; } else { arr[k] = R[j]; j++; } k++; } /* Copy remaining elements of L[] if any */ while (i < n1) { arr[k] = L[i]; i++; k++; } /* Copy remaining elements of R[] if any */ while (j < n2) { arr[k] = R[j]; j++; k++; } } } Implement Mergesort in Java using LinkedList /** * Definition for ListNode. * public class ListNode { * int val; * ListNode next; * ListNode(int val) { * this.val = val; * this.next = null; * } * } */ public class MergeSortList { /** * @param head: The head of linked list. * @return: The head of the sorted linked list. */ public ListNode sortList(ListNode head) { if (head == null || head.next == null) { return head; } ListNode mid = findMid(head); ListNode right = sortList(mid.next); mid.next = null; ListNode left = sortList(head); return mergeList(left, right); } private ListNode findMid (ListNode head) { ListNode slow = head; ListNode fast = head.next; while (fast != null && fast.next != null) { slow = slow.next; fast = fast.next.next; } return slow; } private ListNode mergeList (ListNode left, ListNode right) { ListNode dummy = new ListNode(0); ListNode tail = dummy; while (left != null && right != null) { if (left.val <= right.val) { tail.next = left; left = left.next; } else { tail.next = right; right = right.next; } tail = tail.next; } if (left != null) { tail.next = left; } else { tail.next = right; } return dummy.next; } } Heapsort Heap sort is a comparison based sorting technique based on Binary Heap data structure. It is similar to selection sort where we first find the maximum element and place the maximum element at the end. We repeat the same process for remaining element. Heap Sort Algorithm for sorting in increasing order: Build a max heap from the input data. At this point, the largest item is stored at the root of the heap. Replace it with the last item of the heap followed by reducing the size of heap by 1. Finally, heapify the root of tree. Repeat above steps while size of heap is greater than 1. Implement Heapsort in Java using Arrays public class HeapSort { public void sort(int arr[]) { int n = arr.length; // Build heap (rearrange array) for (int i = n / 2 - 1; i >= 0; i--) heapify(arr, n, i); // One by one extract an element from heap for (int i=n-1; i>=0; i--) { // Move current root to end int temp = arr[0]; arr[0] = arr[i]; arr[i] = temp; // call max heapify on the reduced heap heapify(arr, i, 0); } } // To heapify a subtree rooted with node i which is // an index in arr[]. n is size of heap void heapify(int arr[], int n, int i) { int largest = i; // Initialize largest as root int l = 2*i + 1; // left = 2*i + 1 int r = 2*i + 2; // right = 2*i + 2 // If left child is larger than root if (l < n && arr[l] > arr[largest]) largest = l; // If right child is larger than largest so far if (r < n && arr[r] > arr[largest]) largest = r; // If largest is not root if (largest != i) { int swap = arr[i]; arr[i] = arr[largest]; arr[largest] = swap; // Recursively heapify the affected sub-tree heapify(arr, n, largest); } } } References Foundations of Algorithms, Richard E. Neapolitan, Chapter 2 Divide and Conquer Sorting, CMU Big-O Algorithm Complexity Cheat Sheet Java sorting algorithms - Implementations Merge Sort, GeeksforGeeks Quick Sort, GeeksforGeeks Heap Sort, GeeksforGeeks ```