Introduction

In this blog post, we will explore how to solve the LeetCode problem "3485" 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 an array of strings words and an integer k. For each index i in the range [0, words.length - 1], find the length of the longest common prefix among any k strings (selected at distinct indices) from the remaining array after removing the ith element. Return an array answer, where answer[i] is the answer for ith element. If removing the ith element leaves the array with fewer than k strings, answer[i] is 0. Example 1: Input: words = ["jump","run","run","jump","run"], k = 2 Output: [3,4,4,3,4] Explanation: Removing index 0 ("jump"): words becomes: ["run", "run", "jump", "run"]. "run" occurs 3 times. Choosing any two gives the longest common prefix "run" (length 3). Removing index 1 ("run"): words becomes: ["jump", "run", "jump", "run"]. "jump" occurs twice. Choosing these two gives the longest common prefix "jump" (length 4). Removing index 2 ("run"): words becomes: ["jump", "run", "jump", "run"]. "jump" occurs twice. Choosing these two gives the longest common prefix "jump" (length 4). Removing index 3 ("jump"): words becomes: ["jump", "run", "run", "run"]. "run" occurs 3 times. Choosing any two gives the longest common prefix "run" (length 3). Removing index 4 ("run"): words becomes: ["jump", "run", "run", "jump"]. "jump" occurs twice. Choosing these two gives the longest common prefix "jump" (length 4). Example 2: Input: words = ["dog","racer","car"], k = 2 Output: [0,0,0] Explanation: Removing any index results in an answer of 0. Constraints: 1 <= k <= words.length <= 105 1 <= words[i].length <= 104 words[i] consists of lowercase English letters. The sum of words[i].length is smaller than or equal 105.

Explanation

Here's the solution:

• High-Level Approach: The solution iterates through the words array. For each index i, it creates a sub-array excluding the word at index i. Then, it iterates through all possible pairs (or more generally, combinations of size k) of words within this sub-array to compute the longest common prefix (LCP) of each combination. The maximum LCP length found across all combinations is stored as the result for index i. If the sub-array doesn't have at least k elements, the result for i is 0.

• Complexity Analysis:

  • Runtime Complexity: O(n (mCk) l), where n is the length of words, m is (n-1), k is the given parameter, and l is the maximum length of the words. In simpler terms, O(n² l) in the worst-case because mCk becomes close to n^k, however for small constant values of k the problem is in O(n² l)
  • Storage Complexity: O(n), due to the storage of the answer array.

Code

    def longest_common_prefix(str1, str2):
    """
    Calculates the longest common prefix of two strings.
    """
    min_len = min(len(str1), len(str2))
    i = 0
    while i < min_len and str1[i] == str2[i]:
        i += 1
    return str1[:i]

def longest_common_prefix_k(words, k):
    """
    Calculates the length of the longest common prefix among any k strings in the given list.
    Returns 0 if the list has fewer than k strings.
    """
    n = len(words)
    if n < k:
        return 0

    max_lcp_len = 0

    # Iterate through all combinations of k strings.
    import itertools
    for combination in itertools.combinations(words, k):
        # Calculate LCP of the first two strings in the combination.
        lcp = longest_common_prefix(combination[0], combination[1])

        # Iterate through the remaining strings and update the LCP.
        for i in range(2, len(combination)):
            lcp = longest_common_prefix(lcp, combination[i])

        max_lcp_len = max(max_lcp_len, len(lcp))

    return max_lcp_len

def longest_common_prefix_after_removal(words, k):
    """
    Calculates the length of the longest common prefix among any k strings after removing one element.
    """
    n = len(words)
    answer = []
    for i in range(n):
        # Create a new array without the element at index i.
        temp_words = words[:i] + words[i+1:]

        # Calculate the length of the longest common prefix.
        lcp_length = longest_common_prefix_k(temp_words, k)
        answer.append(lcp_length)

    return answer