Sliding Window Maximum (Size K)
Monotonic deque tracks indices of maximum elements in moving window of size K.
Live loop — open the studio to scrub, add your own array, or race it in Battle Arena.
Asked in interviews at
Reference implementation (Python)
def max_sliding_window(nums, k=3):
from collections import deque
q = deque()
res = []
for i, x in enumerate(nums):
while q and nums[q[-1]] <= x: q.pop()
q.append(i)
if q[0] == i - k: q.popleft()
if i >= k - 1: res.append(nums[q[0]])
return resEmbed this visualization
Drop a live, looping Sliding Window Maximum (Size K) canvas into a blog post or course page.
<iframe src="/embed/sliding-window-maximum" width="100%" height="380" style="border:1px solid #e6e8ec;border-radius:14px" loading="lazy" title="3D algorithm visualization by CodeWithMunnaX"></iframe>Frequently asked
What is the time and space complexity of Sliding Window Maximum (Size K)?
Sliding Window Maximum (Size K) runs in O(n) time and O(k) auxiliary space.
Is the Sliding Window Maximum (Size K) visualizer free?
The core 3D visualizer, Web Audio chimes and step intuition are free. A one-time ₹49 Pro Pass unlocks advanced algorithms, large custom arrays, Battle Arena and reel export.
Which companies ask Sliding Window Maximum (Size K) in interviews?
Sliding Window Maximum (Size K) shows up in interviews at Meta, Google, Uber.
How does the 3D visualization of Sliding Window Maximum (Size K) work?
Each array value becomes a 3D pillar whose height maps to its value. Comparisons glow amber, swaps flash red, and settled elements lock green while a floating pointer badge tracks the active index — synchronized line-by-line with the Python code.