Sliding Window Technique

The sliding window technique is essential for solving substring and subarray problems efficiently.

Types of Sliding Windows

Fixed-Size Window

The window size is constant throughout. Example: Maximum sum of k consecutive elements

Variable-Size Window

The window size changes based on conditions. Example: Longest substring without repeating characters

Common Problems

1. Maximum Sum Subarray of Size K
2. Longest Substring Without Repeating Characters
3. Minimum Window Substring
4. Fruits into Baskets

Template

def sliding_window(arr, k):
    left = 0
    window_sum = 0
    max_sum = 0

    for right in range(len(arr)):
        window_sum += arr[right]

        if right >= k - 1:
            max_sum = max(max_sum, window_sum)
            window_sum -= arr[left]
            left += 1

    return max_sum

When to Use

• Subarray or substring problems
• Looking for contiguous elements
• Optimization problems with constraints

Practice these patterns and sliding window will become second nature!