Is Unique Substrings With Equal Digit Frequency easy or hard?

The problem is rated Medium on LeetCode. The main challenge is recognizing the mathematical condition maxFreq × distinctDigits = substring length and combining it with hashing to count only unique substrings efficiently.

Unique Substrings With Equal Digit Frequency Python/Java solution

Implement two nested loops to expand substrings, maintain a digit frequency array, and compute a rolling hash for each extension. When maxFreq × distinctDigits equals the substring length, add the hash to a set. The same logic translates directly to Python, Java, or Go with O(n^2) complexity.

How to solve Unique Substrings With Equal Digit Frequency in O(n^2)?

Fix a starting index and extend the substring one character at a time. Maintain a frequency array for digits 0–9, track distinct digits, and record the maximum frequency. If maxFreq × distinctDigits equals the current substring length, the substring has equal digit frequency. Insert its rolling hash into a set to ensure uniqueness.

What is the best approach for Unique Substrings With Equal Digit Frequency?

The optimal approach expands substrings from each starting index while maintaining digit frequencies. Track the number of distinct digits and the maximum frequency. A substring is valid when maxFreq × distinctDigits equals the substring length. Use a hash set with rolling hash to store unique substrings. This runs in O(n^2) time.

Is Unique Substrings With Equal Digit Frequency asked at Google/Amazon/Meta?

Problems involving substring hashing, frequency counting, and uniqueness checks are common in interviews at companies like Google, Amazon, and Meta. Variations using rolling hash or substring frequency constraints frequently appear in medium-level string questions.

What data structure is used in Unique Substrings With Equal Digit Frequency?

The solution primarily uses a frequency array of size 10 for digit counting and a hash set to store unique substring hashes. Rolling hash is used to represent substrings efficiently without storing the entire string each time.

What is the time complexity of Unique Substrings With Equal Digit Frequency?

The optimized solution runs in O(n^2) time because each starting index expands at most n positions while updating counts in constant time. Space complexity is O(n^2) for storing hashes of unique substrings.

Description Hints 5 Solution Video 21:05

2168. Unique Substrings With Equal Digit Frequency

Medium64.6% acceptance1 companyPremium elsewhere, free here

Given a digit string s, return the number of unique substrings of s where every digit appears the same number of times.

Example 1:

Input: s = "1212"
Output: 5
Explanation: The substrings that meet the requirements are "1", "2", "12", "21", "1212".
Note that although the substring "12" appears twice, it is only counted once.

Example 2:

Input: s = "12321"
Output: 9
Explanation: The substrings that meet the requirements are "1", "2", "3", "12", "23", "32", "21", "123", "321".

Constraints:

1 <= s.length <= 1000
s consists of digits.

Asked at 1 company

Expedia

Topics

Hints open one at a time

Hint 1

With the constraints, could we try every substring?

Hint 2

Yes, checking every substring has runtime O(n^2), which will pass.

Hint 3

How can we make sure we only count unique substrings?

Hint 4

Use a set to store previously counted substrings. Hashing a string s of length m takes O(m) time. Is there a fast way to compute the hash of s if we know the hash of s[0..m - 2]?

Hint 5

Use a rolling hash.

21:05

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