Sliding Window Technique Cuts Subarray Problem Complexity from O(n²) to O(n)

The sliding window technique is an algorithmic approach that efficiently solves problems involving contiguous subarrays or substrings by maintaining and updating a moving range instead of recalculating from scratch. Common use cases include finding the maximum sum of k consecutive elements, the longest substring without repeating characters, and the smallest subarray meeting a target sum. The method works by removing an element from the left and adding one on the right as the window advances, avoiding redundant computation across overlapping ranges. It is closely related to the two-pointer technique, where a left and right pointer together define the current window boundary. This approach typically reduces time complexity from O(n²) in brute-force solutions to O(n), making it highly effective for large datasets.