Start by checking the frequency of each character and split the string at characters that fail the k threshold. Recursively evaluate segments while updating a running window for valid substrings. This approach ensures that you quickly eliminate invalid partitions and accurately capture the maximum length substring where all characters meet the repetition requirement.
Problem Statement
Given a string s and an integer k, identify the length of the longest contiguous substring where every character occurs at least k times. If no such substring exists, return 0. The input string consists only of lowercase English letters and can be up to 10,000 characters long.
For example, if s = "aaabb" and k = 3, the longest substring satisfying the condition is "aaa" with length 3. If s = "ababbc" and k = 2, the answer is 5 for substring "ababb". Your solution should efficiently handle large strings using appropriate data structures and algorithms tied to character frequency tracking.
Examples
Example 1
Input: s = "aaabb", k = 3
Output: 3
The longest substring is "aaa", as 'a' is repeated 3 times.
Example 2
Input: s = "ababbc", k = 2
Output: 5
The longest substring is "ababb", as 'a' is repeated 2 times and 'b' is repeated 3 times.
Constraints
- 1 <= s.length <= 104
- s consists of only lowercase English letters.
- 1 <= k <= 105
Solution Approach
Frequency Map and Split Points
Compute the frequency of each character. Characters appearing fewer than k times cannot be in any valid substring. Use them as split points to divide the string and recursively solve for each segment, ensuring every character in a substring meets the threshold.
Sliding Window with Dynamic Counters
Use a sliding window to track counts of characters in the current substring segment. Expand the window until an invalid character violates the k condition, then shrink or split at that point. Update the maximum length whenever a valid window is found.
Combine Divide and Conquer with Window Tracking
Merge both strategies by recursively splitting at invalid characters while also applying a sliding window inside segments. This allows handling complex distributions efficiently and avoids repeated scanning of invalid portions, optimizing both time and space usage.
Complexity Analysis
| Metric | Value |
|---|---|
| Time | Depends on the final approach |
| Space | \mathcal{O}(1) |
Time complexity is O(n) on average with recursive splits depending on character distribution. Space complexity is O(1) for counters if using fixed-size arrays for lowercase letters.
What Interviewers Usually Probe
- Check if the candidate identifies characters below k as natural split points.
- Listen for mention of recursive divide-and-conquer or sliding window with frequency counters.
- Evaluate awareness of worst-case behavior when many characters fall below k.
Common Pitfalls or Variants
Common pitfalls
- Counting frequencies globally without handling splits leads to incorrect substring lengths.
- Not updating window counters dynamically can cause unnecessary rescanning.
- Failing to handle edge cases where no valid substring exists, returning negative or wrong values.
Follow-up variants
- Find the longest substring with at least k occurrences of exactly m distinct characters.
- Determine the number of substrings where each character occurs at least k times.
- Compute the longest substring allowing at most x characters to appear fewer than k times.
How GhostInterview Helps
- Automatically identifies split points where characters fail the k repetition condition.
- Tracks valid substring windows dynamically to maximize length without manual scanning.
- Highlights failure patterns and recursion strategies, ensuring efficient segment evaluation.
Topic Pages
Related GhostInterview Pages
- LeetCode Interview Copilot - Use GhostInterview as a live solver when you want direct help with LeetCode-style coding questions.
- Coding Interview Assistant - See how GhostInterview supports array, string, linked list, graph, and tree interview workflows.
- How GhostInterview Works - Review the screenshot, reasoning, and answer flow before using the solver in a live interview.
FAQ
What is the key strategy for Longest Substring with At Least K Repeating Characters?
The core strategy is using character frequency to split the string at invalid points, combined with sliding window updates to track valid substrings efficiently.
Can a sliding window alone solve this problem?
A sliding window alone may not capture all valid segments if characters below k are present, so combining it with divide-and-conquer ensures correctness.
What is the time complexity for this problem?
Time complexity is roughly O(n) on average, but depends on how many splits occur due to characters below the k threshold.
What data structures are most useful here?
Fixed-size arrays or hash maps for character counts are ideal, enabling quick frequency checks and efficient window updates.
How do I handle strings with no valid substring?
If no character meets the minimum repetition k, return 0 immediately to avoid unnecessary computation.
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Find the length of the longest substring after at most k replacements using a sliding window and character count tracking.
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