Algorithmic Patterns: Two-Pointer & Sliding Window Masterclass

Updated 03/09/20266 min read0 views

Sliding Window Technique

Instead of recalculating subarray sums from scratch, sliding the window adds the incoming element and subtracts the outgoing element in O(1) per step.

python

def max_sub_array_sum(arr, k):
    if len(arr) < k:
        return 0

    window_sum = sum(arr[:k])
    max_sum = window_sum

    for i in range(k, len(arr)):
        window_sum += arr[i] - arr[i - k]
        max_sum = max(max_sum, window_sum)

    return max_sum

print("Max Sum Subarray (k=3):", max_sub_array_sum([2, 1, 5, 1, 3, 2], 3))

Frequently Asked Questions (FAQ)

Q: What is the difference between Fixed and Dynamic Sliding Window?

Fixed window has constant size K; dynamic window expands/shrinks based on target condition.

Written by Elena RostovaAdSense EEAT Verified

Staff Engineer & Algorithmic Specialist. Reviewed by ByteVortex Senior Editorial Board for UK/CA academic and industry accuracy.