Window Sliding Technique in C

Loops are part of almost every complex problem. Too many loops/ nested loops increase the required time, thus increasing the time complexity of the program. The window sliding technique is one of the computation techniques used to reduce the number of nested loops used in a program by replacing a nested loop with a single loop to increase the program's efficiency.

This technique is similar if you are familiar with the Sliding window protocol in computer networks. This tutorial explains how this technique is used with different examples.

Generally, when we use a nested loop like this:

Iterations:

The outer loop is executed n times; every time the outer loop executes, the inner loop is executed for (k-i) several times. The average time required to execute the whole loop would be approximately O(N²). Hence, developers don't suggest using loops.

Let us take an example to understand the concept clearly:

Suppose we're supposed to find the maximum sum of 'k' consecutive elements in an array. The user will provide the value of k.

First, if we use the na�ve approach, for every element i in the array, we'll iterate the array from i + 1 till n - 1 where n is the size of the array. We need to do this for every element and compare the sums to get the maximum sum.

Na�ve Brute force method:

Output:

Enter the size of the array: 7
Enter the elements of the array: 9 2 7 9 4 2 8
Enter the size of the sub-array: 3
The maximum sum of 3 consecutive elements of the array: 20

Now, here comes the sliding window technique:

The concept here is that we create a window of size k, and we'll keep sliding it by a unit index. Here, the window isn't any technical term. Rather than using a single value as we do in loops, we use multiple elements simultaneously in each iteration.

For example:

Given an array of size 10:

Suppose we need the maximum sum of 3 consecutive indexes, create a 3-sized window, and keep sliding (traversing) it throughout the array. Here is a pictorial representation:

Iteration 1:

Iteration 2:

Iteration 3:

Iteration 4:

Iteration 5:

Iteration 6:

Iteration 7:

Iteration 8:

• Using this method, there will be no inner loop, and the number of iterations of the one single loop will be (n - k + 1), 8 in this case.
• So, a Sliding window is a technique used to reduce the use of nested loops and replace it with a single loop to reduce the total time complexity.
• Observe that in every iteration, when the window is sliding to the next index, we're deleting the first element from the previous window and adding a new element that is the next succeeding index.

Here is the code:

Output:

Enter the size of the array: 10
Enter the elements: 8 2 1 7 3 2 5 8 1 3
Enter the value of k: 3
The maximum sum of 3 consecutive elements in the array: 15

• The na�ve approach takes O(k*n) time with two nested loops.
• The time complexity is reduced to O(n) by using the Sliding window technique.

Here are the steps to apply the technique to any problem at hand:

1. First, we must see that the window size is constant and shouldn't change. We can use the technique to only such problems.
2. After you ensure that the window size isn't changing, compute the result of the first window to compare to the computations of the rest of the array.
3. Now, use a loop to slide the window index by index till the end and keep updating the required value.