Sliding Window Maximum | Monotonic Deque | JavaScript | LeetCode 239

📝 Description: 🔥 Day 88 of my LeetCode Daily Challenge! In this problem, I solve LeetCode 239 - Sliding Window Maximum using a Monotonic Deque in JavaScript. This is a classic and highly optimized sliding window problem where we need to find the maximum element in every window of size k. 🧠 Key Idea: We use a deque (double-ended queue) to store indices of elements in a way that: Elements are always in decreasing order The front of the deque always holds the maximum element index ⚡ Approach: For each element: Remove elements from the back of deque if they are smaller than current element 👉 (they can never be maximum again) Add current index to the deque Remove the front if it is out of the current window Once window size is reached (i greater than or equal k-1): 👉 Add the maximum (nums[q.front()]) to result 🚀 Why this works: Each element is: Added once Removed once So we achieve linear time complexity, unlike brute force. ✅ Complexity: Time Complexity: O(n) Space Complexity: O(k) 📚 In this video, you will learn: How to use a Monotonic Deque How to solve Sliding Window Maximum efficiently Why this approach is better than brute force or heap How to maintain decreasing order in deque One of the most important patterns in array problems 🔗 Problem Link: https://leetcode.com/problems/sliding-window-maximum/ If you found this helpful, don’t forget to like, comment, and subscribe for more daily LeetCode solutions, JavaScript DSA problems, and coding interview prep 🚀 #LeetCode #JavaScript #DSA #Day88 #SlidingWindowMaximum #LeetCode239 #SlidingWindow #Deque #MonotonicQueue #CodingInterview #Algorithms #DataStructures #ProblemSolving #LeetCodeJavaScript #100DaysOfCode