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

The brute force approach for Length of the Longest Alphabetical Continuous Substring 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 is alphabetical and keeping track of the longest one found. This is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Length of the Longest Alphabetical Continuous Substring?

Length of the Longest Alphabetical Continuous Substring uses the following concepts: String. The recommended patterns to study are: Two Pointers, Sliding Window.

What are the interview tips for Length of the Longest Alphabetical Continuous Substring?

Always start with the brute force approach to demonstrate understanding, then optimize. Think about edge cases and how your solution handles them. Practice explaining your thought process clearly as you code.

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

Not considering edge cases, such as strings with no alphabetical substrings. Failing to reset the current length when a non-consecutive character is found.

#2414

Length of the Longest Alphabetical Continuous Substring

Medium

StringTwo PointersSliding 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 solution uses a single pass through the string to track the current length of an alphabetical substring and update the maximum length found. This is efficient and avoids the overhead of generating all substrings.

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Algorithm

5 steps

1Step 1: Initialize two variables: max_length to 1 and current_length to 1.
2Step 2: Loop through the string starting from the second character.
3Step 3: If the current character is consecutive to the previous one, increment current_length.
4Step 4: If not, reset current_length to 1.
5Step 5: Update max_length if current_length exceeds it.

solution.py15 lines

1# Full working Python code
2
3def longest_alphabetical_substring(s):
4    max_length = 1
5    current_length = 1
6    for i in range(1, len(s)):
7        if ord(s[i]) == ord(s[i - 1]) + 1:
8            current_length += 1
9        else:
10            current_length = 1
11        max_length = max(max_length, current_length)
12    return max_length
13
14# Example usage
15print(longest_alphabetical_substring('abcde'))  # Output: 5

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Complexity note: The time complexity is O(n) because we only make a single pass through the string, where n is the length of the string. The space complexity is O(1) since we are using a constant amount of extra space.

1The longest possible continuous substring can only be up to 26 characters (the entire alphabet).
2Using a single pass through the string is much more efficient than generating all substrings.

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