Core Java

Sliding Window Algorithm in Java

1. Introduction

This is an in-depth article related to the Sliding Window Algorithm. This algorithm cuts down the necessity of nested loops by having one loop. This brings down the complexity in time.

2. Sliding Window Algorithm

2.1 Prerequisites

Java 7 or 8 is required on the Linux, windows, or mac operating systems. Maven 3.6.1 is required for building the spring and hibernate application.

2.2 Download

You can download Java 8 can be downloaded from the Oracle website. Apache Maven 3.6.1 can be downloaded from the Apache site. Spring framework’s latest releases are available from the spring website.

2.3 Setup

You can set the environment variables for JAVA_HOME and PATH. They can be set as shown below:

export JAVA_HOME
export PATH

The environment variables for maven are set as below:

Maven Environment
export M2_HOME=/users/bhagvan.kommadi/Desktop/apache-maven-3.6.1
export M2=$M2_HOME/bin
export PATH=$M2:$PATH

2.4 The Idea Behind the Algorithm

The basic idea is to have one loop instead of multiple nested loops. The time complexity comes down to the order of n instead of order of square of n. Given an array, if you are asked to find the max or min of the range of elements in the array. This algorithm is used on sorted elements in a given array. The technique starts from both ends, left and right. The values of the elements for a given range are calculated from both ends. We need to remove the elements as movement happens from the left to right range.

2.5  Fixed-Size Sliding Window Example

If the length of the ranges is fixed, the algorithm is called fixed-size sliding window algorithm. You can see the implementation of the algorithm in java as shown in the code below.

Fixed Size Sliding Window

import java.util.LinkedList;
import java.util.Scanner;
public class FixedSizeSlidingWindow {
    static int[] sarr;
    public static void main(String[] args) {
        Scanner scanner = new Scanner(;
        int[] arr = new int[scanner.nextInt()];
        for (int i = 0; i < arr.length; i++) {
            arr[i] = scanner.nextInt();
        System.out.print("arr[]: {");
        for (int i = 0; i < arr.length; i++) {
            System.out.print(" "+arr[i]);

        System.out.println(" }");
        int slidingWindow = scanner.nextInt();
       algo(arr, slidingWindow);
    public static void algo(int[] arr, int k) {
        LinkedList linkedList = new LinkedList();
        for (int i = 0; i < arr.length; i++) {
            while (!linkedList.isEmpty() && arr[linkedList.getLast()] <= arr[i]) {

            while (!linkedList.isEmpty() && linkedList.getFirst() = k-1)

                System.out.print(" "+arr[linkedList.getFirst()]);

Let us look at the output of the code when executed.

Fixed Size Sliding Window Output

(base) apples-MacBook-Air:slidingwindow bhagvan.kommadi$ javac 
(base) apples-MacBook-Air:slidingwindow bhagvan.kommadi$ java FixedSizeSlidingWindow
arr[]: { 4 5 -3 5 1 4 }
 5 5 5 5

2.6 Flexible-Size Sliding Window Example

Now let us look at the variable length of the ranges, the algorithm is called flexible size sliding window algorithm. If you have n elements in an array, we need to select x elements whose sum of the value is p. This is an example where a flexible size sliding window algorithm is applicable. We try to solve LeetCode’s Longest Substring without repeating characters in the code below.

Flexible Size Sliding Window

public class FlexibleSlidingWindow {
	public static void main(String[] args)
		FlexibleSlidingWindow algo = new FlexibleSlidingWindow();
		int longStringLength = algo.lengthSubstring("sentence");
    public int lengthSubstring(String str) {
        if (str == null || str.length() == 0)
            return 0;

        if (str.length() == 1)
            return 1;

        int maxSubstringLength = Integer.MIN_VALUE;

        int[] characterIndex = new int[128];
        int startWindowIdx = 0;

        for (int endWindowIdx = 0; endWindowIdx < str.length(); endWindowIdx++) {
            startWindowIdx = Math.max(startWindowIdx, characterIndex[str.charAt(endWindowIdx)]);

            maxSubstringLength = Math.max(endWindowIdx - startWindowIdx + 1, maxSubstringLength);
            characterIndex[str.charAt(endWindowIdx)] = endWindowIdx + 1;
        return maxSubstringLength;

Let us look at the output of the code when executed.

Flexible Size Sliding Window Output

(base) apples-MacBook-Air:slidingwindow bhagvan.kommadi$ 
java FlexibleSlidingWindow

3. Download the Source Code

You can download the full source code of this example here: Sliding Window Algorithm in Java

Bhagvan Kommadi

Bhagvan Kommadi is the Founder of Architect Corner & has around 20 years’ experience in the industry, ranging from large scale enterprise development to helping incubate software product start-ups. He has done Masters in Industrial Systems Engineering at Georgia Institute of Technology (1997) and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras (1993). He is member of IFX forum,Oracle JCP and participant in Java Community Process. He founded Quantica Computacao, the first quantum computing startup in India. Markets and Markets have positioned Quantica Computacao in ‘Emerging Companies’ section of Quantum Computing quadrants. Bhagvan has engineered and developed simulators and tools in the area of quantum technology using IBM Q, Microsoft Q# and Google QScript. He has reviewed the Manning book titled : "Machine Learning with TensorFlow”. He is also the author of Packt Publishing book - "Hands-On Data Structures and Algorithms with Go".He is member of IFX forum,Oracle JCP and participant in Java Community Process. He is member of the MIT Technology Review Global Panel.
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Arnaud Kleinveld
Arnaud Kleinveld
1 year ago

The linkedList is never been added to!?

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