What is the brute force solution for Longest Substring with At Least K Repeating Characters?

The brute force approach for Longest Substring with At Least K Repeating Characters is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves checking every possible substring of the input string to see if it meets the requirement of having all characters appear at least k times. This is straightforward but inefficient, especially for longer strings. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Longest Substring with At Least K Repeating Characters?

Longest Substring with At Least K Repeating Characters uses the following concepts: Hash Table, String, Divide and Conquer, Sliding Window. The recommended patterns to study are: Hash Map, Divide and Conquer.

What are the interview tips for Longest Substring with At Least K Repeating Characters?

Always clarify the problem requirements and constraints before diving into coding. Think about edge cases and test your solution against them. Explain your thought process clearly as you code; this helps the interviewer understand your reasoning.

What are common mistakes when solving Longest Substring with At Least K Repeating Characters?

Failing to handle edge cases where no characters meet the frequency requirement. Not considering the impact of splitting the string on the overall substring length.

#395

Longest Substring with At Least K Repeating Characters

Medium

Hash TableStringDivide and ConquerSliding WindowHash MapDivide and Conquer

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

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Intuition

Time O(n)Space O(n)

The optimal solution uses a recursive approach that divides the string based on the characters that do not meet the frequency requirement. This allows us to efficiently find the longest valid substring by breaking the problem down into smaller parts.

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Algorithm

3 steps

1Step 1: Count the frequency of each character in the string.
2Step 2: Identify characters that occur less than k times; if none, return the length of the string.
3Step 3: Split the string at these characters and recursively find the longest valid substring in each part.

solution.py13 lines

1# Full working Python code
2
3def longestSubstring(s, k):
4    from collections import Counter
5    freq = Counter(s)
6    for char in freq:
7        if freq[char] < k:
8            return max(longestSubstring(sub, k) for sub in s.split(char))
9    return len(s)
10
11# Example usage
12print(longestSubstring('aaabb', 3))  # Output: 3
13print(longestSubstring('ababbc', 2))  # Output: 5

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Complexity note: The time complexity is O(n) because we only traverse the string a limited number of times. The space complexity is O(n) due to the storage of character frequencies and the potential substrings created during the split.

1Identifying characters that do not meet the frequency requirement allows for efficient substring splitting.
2Recursive approaches can simplify complex problems by breaking them down into manageable parts.

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