#####   ######  #####    ###    #   #  ###  #   #  ######
##  ##  ##      ##  ##  ## ##   #   #   #   #   #  ##
#####   ####    #####   #   #   #   #   #   #   #  ####
##  #   ##      ##      ## ##    # #    #    # #   ##
##   #  ######  ##       ###      #    ###    #    ######

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

░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░████████████████████████████████████████████████████████████████████████████████████████████████████████

#####   ######  #####    ###    #   #  ###  #   #  ######
##  ##  ##      ##  ##  ## ##   #   #   #   #   #  ##
#####   ####    #####   #   #   #   #   #   #   #  ####
##  #   ##      ##      ## ##    # #    #    # #   ##
##   #  ######  ##       ###      #    ###    #    ######

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

Repovive

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

Repovive.

Fundamental Algorithms8 sections · 294 units2h total

Open in Course

Sliding Window Maximum - Implementation

Here is the implementation using a monotonic deque:

function maxSlidingWindow(nums, k):
    deque = empty deque (stores indices)
    result = []

    for i from 0 to nums.length - 1:
        // Remove indices outside window
        while deque not empty and deque.front() <= i - k:
            deque.popFront()

        // Remove smaller elements
        while deque not empty and nums[deque.back()] < nums[i]:
            deque.popBack()

        deque.pushBack(i)

        if i >= k - 1:
            result.append(nums[deque.front()])

    return result

$O(n)$ time (each index added/removed once), $O(k)$ space for deque.