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Quicksort with Java. This article describes how to implement Quicksort with Java.

Sort algorithms order the elements of an array according to a predefined order. Quicksort is a divide and conquer algorithm. In a divide and conquer sorting algorithm the original data is separated into two parts "divide" which are individually sorted and "conquered" and then combined.

1.2. Description of the algorithm

If the array contains only one element or zero elements then the array is sorted.

If the array contains more than one element then:

Select an element from the array. This element is called the "pivot element". For example select the element in the middle of the array.
All elements which are smaller than the pivot element are placed in one array and all elements which are larger are placed in another array.
Sort both arrays by recursively applying Quicksort to them.
Combine the arrays.

Quicksort can be implemented to sort "in-place". This means that the sorting takes place in the array and that no additional array needs to be created.

2. Quicksort in Java

2.1. Implementation

Create a Java project "de.vogella.algorithms.sort.quicksort" and create the following class.

package de.vogella.algorithms.sort.quicksort;


public class Quicksort  {
    private int[] numbers;
    private int number;

    public void sort(int[] values) {
        // check for empty or null array
        if (values ==null || values.length==0){
            return;
        }
        this.numbers = values;
        number = values.length;
        quicksort(0, number - 1);
    }

    private void quicksort(int low, int high) {
        int i = low, j = high;
        // Get the pivot element from the middle of the list
        int pivot = numbers[low + (high-low)/2];

        // Divide into two lists
        while (i <= j) {
            // If the current value from the left list is smaller than the pivot
            // element then get the next element from the left list
            while (numbers[i] < pivot) {
                i++;
            }
            // If the current value from the right list is larger than the pivot
            // element then get the next element from the right list
            while (numbers[j] > pivot) {
                j--;
            }

            // If we have found a value in the left list which is larger than
            // the pivot element and if we have found a value in the right list
            // which is smaller than the pivot element then we exchange the
            // values.
            // As we are done we can increase i and j
            if (i <= j) {
                exchange(i, j);
                i++;
                j--;
            }
        }
        // Recursion
        if (low < j)
            quicksort(low, j);
        if (i < high)
            quicksort(i, high);
    }

    private void exchange(int i, int j) {
        int temp = numbers[i];
        numbers[i] = numbers[j];
        numbers[j] = temp;
    }
}

2.2. Test

You can use the following JUnit tests to validate the sort method. To learn about JUnit please see JUnit Tutorial.

package de.vogella.algorithms.sort.quicksort;

import java.util.Arrays;
import java.util.Random;

import org.junit.Before;
import org.junit.Test;

import static org.junit.Assert.assertTrue;
import static org.junit.Assert.fail;

public class QuicksortTest {

    private int[] numbers;
    private final static int SIZE = 7;
    private final static int MAX = 20;

    @Before
    public void setUp() throws Exception {
        numbers = new int[SIZE];
        Random generator = new Random();
        for (int i = 0; i < numbers.length; i++) {
            numbers[i] = generator.nextInt(MAX);
        }
    }

    @Test
    public void testNull() {
        Quicksort sorter = new Quicksort();
        sorter.sort(null);
    }

    @Test
    public void testEmpty() {
        Quicksort sorter = new Quicksort();
        sorter.sort(new int[0]);
    }

    @Test
    public void testSimpleElement() {
        Quicksort sorter = new Quicksort();
        int[] test = new int[1];
        test[0] = 5;
        sorter.sort(test);
    }

    @Test
    public void testSpecial() {
        Quicksort sorter = new Quicksort();
        int[] test = { 5, 5, 6, 6, 4, 4, 5, 5, 4, 4, 6, 6, 5, 5 };
        sorter.sort(test);
        if (!validate(test)) {
            fail("Should not happen");
        }
        printResult(test);
    }

    @Test
    public void testQuickSort() {
        for (Integer i : numbers) {
            System.out.println(i + " ");
        }
        long startTime = System.currentTimeMillis();

        Quicksort sorter = new Quicksort();
        sorter.sort(numbers);

        long stopTime = System.currentTimeMillis();
        long elapsedTime = stopTime - startTime;
        System.out.println("Quicksort " + elapsedTime);

        if (!validate(numbers)) {
            fail("Should not happen");
        }
        assertTrue(true);
    }

    @Test
    public void testStandardSort() {
        long startTime = System.currentTimeMillis();
        Arrays.sort(numbers);
        long stopTime = System.currentTimeMillis();
        long elapsedTime = stopTime - startTime;
        System.out.println("Standard Java sort " + elapsedTime);
        if (!validate(numbers)) {
            fail("Should not happen");
        }
        assertTrue(true);
    }

    private boolean validate(int[] numbers) {
        for (int i = 0; i < numbers.length - 1; i++) {
            if (numbers[i] > numbers[i + 1]) {
                return false;
            }
        }
        return true;
    }

    private void printResult(int[] numbers) {
        for (int i = 0; i < numbers.length; i++) {
            System.out.print(numbers[i]);
        }
        System.out.println();
    }
}

3. Complexity Analysis

The following describes the runtime complexity of quicksort.

Quicksort is a fast, recursive, non-stable sort algorithm which works by the divide and conquer principle. Quicksort will in the best case divide the array into almost two identical parts. It the array contains n elements then the first run will need O(n). Sorting the remaining two sub-arrays takes 2* O(n/2). This ends up in a performance of O(n log n).

In the worst case quicksort selects only one element in each iteration. So it is O(n) + O(n-1) + (On-2).. O(1) which is equal to O(n^2).

The average case of quicksort is O(n log n).