Find K-Length Substrings With No Repeated Characters - Video Solutions

Problem Overview: Given a string s and an integer k, count how many substrings of length k contain only unique characters. Every character inside the window must appear exactly once.

Approach 1: Brute Force with Set Check (O(n * k) time, O(k) space)

Iterate over every possible substring of length k. For each starting index, extract the substring and insert its characters into a set. If the set size equals k, the substring contains no duplicates. This approach directly checks uniqueness but repeatedly scans overlapping substrings, which makes it inefficient when k is large. Still useful as a baseline implementation and helps validate the sliding window optimization.

Approach 2: Sliding Window + Hash Table (O(n) time, O(min(n, k)) space)

Maintain a window of size k using two pointers. A frequency map (hash table) tracks how many times each character appears in the current window. As you expand the right pointer, increment the character count. When the window exceeds size k, remove the leftmost character and update the map. A valid substring occurs when the window length is k and every character frequency is exactly one.

The key insight: instead of re-checking the entire substring, reuse information from the previous window. Each character is added and removed at most once, giving linear traversal of the string. Hash lookups and updates happen in constant time.

This pattern appears frequently in sliding window problems that track constraints inside a fixed-size substring. The frequency map is typically implemented using a dictionary or array, which is a standard use of a hash table. Since the input is a sequence of characters, the problem also falls under classic string processing techniques.

Recommended for interviews: The sliding window + hash table approach. Interviewers expect you to recognize overlapping substrings and avoid recomputing uniqueness from scratch. Showing the brute force idea first demonstrates understanding of the problem space, but the O(n) sliding window solution shows mastery of common string optimization patterns.