Introduction

In this blog post, we will explore how to solve the LeetCode problem "2370" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

Problem Statement

You are given a string s consisting of lowercase letters and an integer k. We call a string t ideal if the following conditions are satisfied: t is a subsequence of the string s. The absolute difference in the alphabet order of every two adjacent letters in t is less than or equal to k. Return the length of the longest ideal string. A subsequence is a string that can be derived from another string by deleting some or no characters without changing the order of the remaining characters. Note that the alphabet order is not cyclic. For example, the absolute difference in the alphabet order of 'a' and 'z' is 25, not 1. Example 1: Input: s = "acfgbd", k = 2 Output: 4 Explanation: The longest ideal string is "acbd". The length of this string is 4, so 4 is returned. Note that "acfgbd" is not ideal because 'c' and 'f' have a difference of 3 in alphabet order. Example 2: Input: s = "abcd", k = 3 Output: 4 Explanation: The longest ideal string is "abcd". The length of this string is 4, so 4 is returned. Constraints: 1 <= s.length <= 105 0 <= k <= 25 s consists of lowercase English letters.

Explanation

Here's the breakdown of the solution:

• Dynamic Programming: We use dynamic programming to store the length of the longest ideal subsequence ending with each character 'a' to 'z'. The DP array dp of size 26 stores the maximum length of ideal subsequences ending with each alphabet.
• Iterative Calculation: Iterate through the input string s. For each character, determine the possible previous characters based on the allowed difference k. Update the DP array based on the longest subsequence found so far, considering the allowed difference.

• Maximum Length: After processing the entire string, find the maximum value in the DP array, which represents the length of the longest ideal string.

• Time & Space Complexity: O(N), where N is the length of the string s. Storage complexity is O(1), as the dp array has a fixed size of 26 (for each alphabet).

Code

    def longest_ideal_string(s: str, k: int) -> int:
    """
    Finds the length of the longest ideal string.

    Args:
        s: The input string.
        k: The maximum allowed difference between adjacent characters.

    Returns:
        The length of the longest ideal string.
    """

    dp = [0] * 26  # dp[i] stores the length of longest ideal string ending with char 'a' + i

    for char in s:
        index = ord(char) - ord('a')
        max_len = 1  # Initialize with length 1 for the current character itself

        for i in range(26):
            if abs(i - index) <= k:
                max_len = max(max_len, dp[i] + 1)

        dp[index] = max_len

    return max(dp)