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$ curl repovive.com/roadmaps/fundamental-algorithms/sliding-window/maximum-average-subarray-implementation

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$ curl repovive.com/roadmaps/fundamental-algorithms/sliding-window/maximum-average-subarray-implementation

Repovive

Maximum Average Subarray - Implementation - Sliding Window | Fundamental Algorithms | Repovive

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Fundamental Algorithms8 sections · 294 units2h total

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Maximum Average Subarray - Implementation


function findMaxAverage(nums, k):
    windowSum = sum of nums[0..k-1]
    maxSum = windowSum

    for i from k to nums.length - 1:
        windowSum += nums[i] - nums[i - k]
        maxSum = max(maxSum, windowSum)

    return maxSum / k

This runs in $O(n)$ time and $O(1)$ space (excluding input). Each element is added once and removed at most once.