Given an array of integers, return indices of the two numbers such that they add up to a specific target.
You may assume that each input will have at most one solution, and you may not use the same index twice.
In case no solution exists, return [-1, -1]
Example:
Input: nums = [2, 7, 11, 15]
, target = 9
Output: [0, 1]
Explanation: nums[0] + nums[1] = 2 + 7 = 9
Your algorithm should run in O(n log n) time and use O(n) extra space.
The core challenge of this problem is to find two distinct indices in the array such that the sum of the elements at these indices equals the target value. This problem is significant in various applications such as financial analysis, where you might need to find two transactions that sum up to a specific amount.
Potential pitfalls include assuming that there are multiple solutions or using the same index twice, which is not allowed.
To solve this problem, we can use a hash map to store the difference between the target and each element as we iterate through the array. This allows us to check in constant time whether the complement of the current element exists in the hash map.
Here is a step-by-step approach:
Let's break down the algorithm step-by-step:
import java.util.HashMap;
public class TwoSumIII {
public int[] twoSum(int[] nums, int target) {
// Create a hash map to store the value and its index
HashMap<Integer, Integer> map = new HashMap<>();
// Iterate through the array
for (int i = 0; i < nums.length; i++) {
// Calculate the complement
int complement = target - nums[i];
// Check if the complement is in the hash map
if (map.containsKey(complement)) {
// Return the indices of the current element and the complement
return new int[] { map.get(complement), i };
}
// Add the current element and its index to the hash map
map.put(nums[i], i);
}
// If no solution is found, return [-1, -1]
return new int[] { -1, -1 };
}
}
The time complexity of this approach is O(n) because we are iterating through the array once. The space complexity is O(n) because we are storing each element in the hash map.
Potential edge cases include:
To test the solution comprehensively, consider the following test cases:
When approaching such problems, it is essential to:
In this blog post, we discussed the Two Sum III problem, explored different approaches to solve it, and provided a detailed solution in Java. Understanding and solving such problems is crucial for developing strong problem-solving skills. Keep practicing and exploring further to improve your skills.
For further reading and practice problems, consider the following resources: