Friday 21 February 2014

Insertion Sort in Java

Background

 Insertion sort iterates, consuming one input element each repetition, and growing a sorted output list. Each iteration, insertion sort removes one element from the input data, finds the location it belongs within the sorted list, and inserts it there. It repeats until no input elements remain.

At any iteration i, elements 0 to i-1 will be sorted and with each increment in i previous list of sorted elements will grow.

Code :

import java.util.Arrays;

/**
 * Created with IntelliJ IDEA.
 * User: aniket
 * Date: 12/2/14
 * Time: 11:14 AM
 */
public class InsertionSort {


    public void sort(int[] array) {

        for(int i=1;i<array.length;i++){
            int j = i;
            while(j>0 && array[j-1]>array[j]){
                Swapper.inMemorySwap(array,j-1,j);
                j--;
            }
        }

    }

    public static void main(String args[]){

        int[] array = new int[]{2,7,5,9,4,7,1,0};
        System.out.println("Array Before Sort : " + Arrays.toString(array));
        new InsertionSort().sort(array);
        System.out.println("Array after Sort : " + Arrays.toString(array));

    }
}

Output :

Array Before Sort : [2, 7, 5, 9, 4, 7, 1, 0]
Array after Sort : [0, 1, 2, 4, 5, 7, 7, 9]


A slightly better version would be where you don't have to swap numbers every time -

    public static int[] insertionSort(int[] array) {
        
        for(int i=1; i <array.length; i++) {
            int key = array[i];
            int j = i - 1;
            while(j>=0 && array[j] > key ) {
                array[j+1] = array[j];
                j--;
            }
            array[j+1] = key;
        }
        return array;
    }


Complexity

 Worst case complexity is O(N2) like bubble sort. However the best case is O(N) - already sorted array. Both bubble sort and insertion sort are not suitable for sorting large numbers.

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