Introduction

In this blog post, we will explore how to solve the LeetCode problem "2094" 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 integer array digits, where each element is a digit. The array may contain duplicates. You need to find all the unique integers that follow the given requirements: The integer consists of the concatenation of three elements from digits in any arbitrary order. The integer does not have leading zeros. The integer is even. For example, if the given digits were [1, 2, 3], integers 132 and 312 follow the requirements. Return a sorted array of the unique integers. Example 1: Input: digits = [2,1,3,0] Output: [102,120,130,132,210,230,302,310,312,320] Explanation: All the possible integers that follow the requirements are in the output array. Notice that there are no odd integers or integers with leading zeros. Example 2: Input: digits = [2,2,8,8,2] Output: [222,228,282,288,822,828,882] Explanation: The same digit can be used as many times as it appears in digits. In this example, the digit 8 is used twice each time in 288, 828, and 882. Example 3: Input: digits = [3,7,5] Output: [] Explanation: No even integers can be formed using the given digits. Constraints: 3 <= digits.length <= 100 0 <= digits[i] <= 9

Explanation

Here's an efficient solution to the problem:

• Core Idea: Iterate through all possible three-digit combinations, checking for leading zeros and evenness. Use a set to maintain uniqueness and then convert the set to a sorted list for the final result.
• Optimization: Instead of generating all permutations and filtering, directly construct potential numbers by iterating through the digits array three times, applying the constraints at each step. This approach avoids unnecessary computations for odd or leading-zero numbers.

• Leverage Sets: Employ a set (unique_numbers) to automatically handle the uniqueness requirement, avoiding manual checks for duplicates.

• Runtime Complexity: O(N^3), where N is the length of the digits array. Storage Complexity: O(K), where K is the number of unique valid integers. In the worst case, K could be O(N^3), but in practice, it will often be smaller.

Code

    def find_even_numbers(digits):
    """
    Finds all unique three-digit even numbers formed from the given digits.

    Args:
      digits: A list of integers representing digits.

    Returns:
      A sorted list of unique integers that meet the criteria.
    """

    unique_numbers = set()
    n = len(digits)

    for i in range(n):
        for j in range(n):
            for k in range(n):
                if i == j and digits.count(digits[i]) < 2:
                    continue
                if i == k and digits.count(digits[i]) < 2:
                    continue
                if j == k and digits.count(digits[j]) < 2:
                    continue

                num = digits[i] * 100 + digits[j] * 10 + digits[k]

                if digits[i] != 0 and num % 2 == 0:
                    unique_numbers.add(num)

    return sorted(list(unique_numbers))