How do you solve Length of the Longest Valid Substring on LeetCode?

Length of the Longest Valid Substring (LeetCode #2781) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Understanding forbidden substrings is crucial for identifying valid substrings.

What is the brute force solution for Length of the Longest Valid Substring?

The brute force approach for Length of the Longest Valid Substring is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves generating all possible substrings of the given string and checking each one against the forbidden list. 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 Length of the Longest Valid Substring?

Length of the Longest Valid Substring uses the following concepts: Array, Hash Table, String, Sliding Window. The recommended patterns to study are: Hash Map, Sliding Window.

What are the interview tips for Length of the Longest Valid Substring?

Always clarify the constraints and edge cases before jumping into coding. Discuss your thought process and approach with the interviewer; it shows your understanding. Practice identifying patterns in problems, as they often lead to optimal solutions.

What are common mistakes when solving Length of the Longest Valid Substring?

Not considering all possible lengths of forbidden substrings. Failing to update the start pointer correctly when a forbidden substring is found.

#2781

Length of the Longest Valid Substring

Hard

ArrayHash TableStringSliding WindowHash MapSliding Window

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n)Space O(n)

Using a sliding window approach allows us to efficiently find the longest valid substring without generating all possible substrings. This method expands and contracts the window based on the presence of forbidden substrings.

⚙️

Algorithm

4 steps

1Step 1: Initialize two pointers (start and end) and a set for forbidden substrings.
2Step 2: Expand the end pointer to include characters until a forbidden substring is found.
3Step 3: If a forbidden substring is found, move the start pointer to exclude characters until the substring is no longer present.
4Step 4: Keep track of the maximum length of valid substrings during the process.

solution.py12 lines

1def longestValidSubstring(word, forbidden):
2    forbidden_set = set(forbidden)
3    max_length = 0
4    start = 0
5    for end in range(len(word)):
6        for length in range(1, 11):  # Check substrings of length 1 to 10
7            if end - length + 1 >= start:
8                substring = word[end - length + 1:end + 1]
9                if substring in forbidden_set:
10                    start = end - length + 2  # Move start past the forbidden substring
11        max_length = max(max_length, end - start + 1)
12    return max_length

ℹ

Complexity note: The time complexity is O(n) because we traverse the string once with the end pointer and potentially check substrings of limited length (up to 10). The space complexity is O(n) due to the storage of the forbidden substrings in a set.

1Understanding forbidden substrings is crucial for identifying valid substrings.
2Using a sliding window can significantly reduce the time complexity compared to brute force.

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