LeetCode 1748 Sum of Unique Elements | Java Solution DSA and Interview Prep

When preparing for coding interviews or practicing Data Structures and Algorithms (DSA) on LeetCode, one essential problem type involves analyzing arrays for unique elements. Problem 1748, "Sum of Unique Elements", challenges us to find the sum of elements in an array that appear exactly once.

In this blog post, we’ll walk through an optimal Java solution that efficiently solves this problem, ensuring you’re equipped to tackle it in both interviews and your LeetCode practice.

Problem Overview:

Given an array of integers, the task is to return the sum of all unique elements—those that occur exactly once.

For example: input: nums = [1, 2, 3, 2], Output: 4, Explanation: The unique elements are 1 and 3, and their sum is 4.

Solution Approach:

To solve this problem, the key is to efficiently determine the frequency of each element in the array. For this, we can utilize a HashMap to count how many times each number appears. After counting, we simply sum the elements that occur only once.

Step-by-Step Java Solution:

import java.util.HashMap;
import java.util.Map;

public class FindSumOfUniqueNumberInArray {
	
	public static void main(String[] args) {
		int [] nums = {1, 2, 3, 2};
		
System.out.println("Sum of unique number in array is: "+getSumOfUnique(nums));
	}

	private static int getSumOfUnique(int[] nums) {
		if (nums.length==0) {
			return 0;
		}
		
		Map<Integer, Integer> map = new HashMap<Integer, Integer>();
		int sum = 0;
		
		for (int i : nums) {
			map.put(i, map.getOrDefault(i, 0)+1);
		}
		
		for (Map.Entry<Integer, Integer> entry : map.entrySet()) {
			if (entry.getValue()==1) {
				sum += entry.getKey();
			}			
		}
		return sum;
	}
}

Explanation:

HashMap to Track Frequency:
- We first iterate over the array and store the frequency of each number using a HashMap.
- The key represents the number, and the value represents how many times the number appears in the array.
Summing Unique Elements:

After populating the frequency map, we loop through its entries.
If a number appears exactly once (i.e., its frequency is 1), we add it to the sum.

Why This Solution Works Well:

Time Complexity: O(n), where n is the number of elements in the array. We traverse the array twice: once to populate the frequency map and once to compute the sum.
Space Complexity: O(n) due to the storage required for the HashMap.

This solution is both time-efficient and space-efficient, making it an excellent choice for coding interviews and LeetCode practice, where optimized solutions are often key to success.

Common Interview Questions:

What if the array is empty?
If the array is empty, the sum of unique elements is simply 0.
Can this solution be further optimized?
This solution is already optimal in terms of time complexity. However, you can explore alternative data structures if specific constraints are imposed.

Why This Problem Is Important:

This problem combines key DSA concepts—such as frequency counting and hash-based storage—with array manipulation. Mastering problems like this ensures you’re well-prepared for questions that demand algorithmic thinking and efficient space utilization, both crucial for coding interviews and LeetCode challenges.

Conclusion:

By solving LeetCode 1748: Sum of Unique Elements, you not only practice a frequently asked interview question but also strengthen your understanding of HashMaps and array manipulation. This Java solution is efficient, easy to understand, and covers the essential logic needed for solving similar DSA problems.

Keep practicing, and you’ll continue to improve your problem-solving skills, preparing yourself for technical interviews and excelling in competitive programming.

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#LeetCode #Java #DSA #CodingChallenges #ArrayManipulation #Programming #InterviewPrep #CodingInterview #TechInterview #LearnToCode #LeetCodeSolution