Sliding Window Technique Explained: A Key DSA Pattern for Coding Interviews
The sliding window is a high-frequency algorithmic pattern used to solve subarray and substring problems efficiently, distinct from the two-pointer technique. It works by maintaining a moving window over an array or string, updating results incrementally rather than recalculating from scratch each time. Fixed sliding windows maintain a constant size, while variable windows expand and shrink dynamically based on validity conditions. Common interview problems solved with this pattern include longest substring without repeating characters, maximum sum subarray of size k, and minimum window substring. Key mistakes to avoid include recalculating window sums in a loop, forgetting to shrink the window, and using a list instead of a set or dictionary for duplicate checks.
