How do you solve Unique Substrings in Wraparound String on LeetCode?

Unique Substrings in Wraparound String (LeetCode #467) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: Understanding the wraparound nature of the string is crucial for efficiently checking substrings.

What is the brute force solution for Unique Substrings in Wraparound String?

The brute force approach for Unique Substrings in Wraparound String is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves generating all possible substrings of the input string and checking if each substring exists in the wraparound string. This is straightforward but inefficient for larger strings. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Unique Substrings in Wraparound String?

Unique Substrings in Wraparound String uses the following concepts: String, Dynamic Programming. The recommended patterns to study are: Dynamic Programming, Sliding Window.

What are the interview tips for Unique Substrings in Wraparound String?

Always clarify the problem statement and constraints before jumping into coding. Consider edge cases, such as strings with repeated characters or single characters. Discuss your thought process and approach with the interviewer to showcase your understanding.

What are common mistakes when solving Unique Substrings in Wraparound String?

Failing to account for the wraparound condition correctly when generating substrings. Not using a set or array to track unique substrings, leading to incorrect counts.

#467

Unique Substrings in Wraparound String

Medium

StringDynamic ProgrammingDynamic ProgrammingSliding Window

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

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Intuition

Time O(n)Space O(1)

The optimal approach leverages dynamic programming to count the length of valid substrings that can be formed in the wraparound string. By tracking the longest valid substring ending at each character, we can efficiently calculate the number of unique substrings.

⚙️

Algorithm

4 steps

1Step 1: Initialize an array to track the length of valid substrings ending at each character.
2Step 2: Iterate through the string and update the length for each character based on the previous character's wraparound condition.
3Step 3: Use a HashMap to store the maximum length of valid substrings for each character.
4Step 4: Sum the lengths of unique substrings for each character to get the total count.

solution.py15 lines

1# Full working Python code
2def unique_substrings_optimal(s):
3    max_length = [0] * 26
4    current_length = 0
5    total_unique = 0
6
7    for i in range(len(s)):
8        if i > 0 and (ord(s[i]) - ord(s[i - 1]) + 26) % 26 == 1:
9            current_length += 1
10        else:
11            current_length = 1
12        index = ord(s[i]) - ord('a')
13        max_length[index] = max(max_length[index], current_length)
14
15    return sum(max_length)

ℹ

Complexity note: The time complexity is O(n) because we iterate through the string once. The space complexity is O(1) since we only use a fixed-size array of size 26 for the alphabet.

1Understanding the wraparound nature of the string is crucial for efficiently checking substrings.
2Dynamic programming can significantly reduce the time complexity by avoiding redundant checks.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.