Top Problems on Sliding Window Technique for Interviews

The Sliding Window Technique is a powerful algorithmic approach used to solve problems involving arrays or lists where a subarray or subsequence is required to be analyzed. This technique allows you to reduce the time complexity of problems that would typically involve nested loops, by maintaining a "window" of elements and sliding it across the array. The window can either expand or shrink based on certain conditions, which helps in optimizing the solution.

Easy

• Maximum sum of a subarray of size k
• Smallest window containing 0, 1 and 2
• Check if Permutation of Pattern is Substring
• Count Strictly Increasing Subarrays
• Remove Consecutive Characters
• Maximum sum of subarray <= x

Medium

• Longest substring with distinct characters
• Substrings with K Distinct
• Maximum Consecutive 1s with K Flips
• Maximum Fruits in Two Baskets
• Substrings of length k with k-1 distinct elements
• Minimum Removals for Target Sum
• Longest Repeating Character Replacement
• Binary subarray with sum
• Subarrays Product Less than K
• Count Occurrences of Anagrams
• Largest sum subarray of size at least k
• Count Distinct Elements In Every Window of Size K
• Subarray with given sum
• First negative integer in every window of size k
• Smallest window that contains all characters of string itself
• Smallest window in a String containing all characters of other String
• Equivalent Sub-Arrays

Hard

• Maximum of minimum for every window size
• Longest Substring with K Uniques
• Minimum Window Substring
• Largest sum subarray with at-least k numbers