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Algorithmic Patterns: Sliding Window

When you start to prepare for interviews it is good to know common strategis to solve problem. You may find that several solution strategies for given problem, but a good programmer is one who is proficient at examining the problem to be solved and identifying the appropriate algorithmic technique to use. We are going to review pattern called Sliding Window in this short article. I will try to give you at least a high level overview of Sliding Window stratege. Currently, I have solved around 400 problems in the leetcode and 200 problems in the hackerrank and time to time participate in contests. I usually solve 3 problems in a contest and sometimes 4 problems. Lets come back to the topic.

Generate problem statement for this pattern starts:

Given an array(list), find the average(maximum|minimum|sum) of all contiguous subarrays of size(adds up to) ‘K’

And the approach for this is

Keep track of any consecutive subarrays of size N. You can visualize each contiguous subarray as a sliding window of N elements add/remove as needed

Example: Given an array, find the average of all contiguous subarrays of size 3 in it.

function find_averages_of_subarrays(arr, k) { const result = []; let sum = 0; let start = 0; for (let i = 0; i < arr.length; i++) { sum += arr[i]; // add the next element // slide the window, we don't need to slide if we've not hit the required window size of 'k' if (i >= k - 1) { result.push(sum / k); // calculate the average sum -= arr[start]; // subtract the element from begining start++; // slide the window ahead } } return result; }

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