Problem
Problem Solving Approach
- Find the single number in an array with a linear runtime complexity of O(n) and use only constant extra space with a complexity of O(1).
- One possible approach is to use a hash map to keep track of the frequency of each number, but this requires extra space proportional to the size of the array, which violates the space complexity constraint.
- Since O(n) and O(2n) have the same complexity of O(n), we can use a sorting algorithm to sort the array and then compare adjacent elements to find the single number.
- The approach can be summarized as follows:
- Sort the array.
- Iterate through the array and compare each pair of adjacent elements.
- If the two elements are not equal, the first element is the single number, so return its value.
- This algorithm has a linear runtime complexity of O(n) and uses only constant extra space with a complexity of O(1).
Time O(n), Space O(1)
https://github.com/eunhanlee/leetcode_136_Single_Number
import java.util.*;
class Solution {
/**
* This method finds the single number in an integer array.
*
* @param nums an integer array
* @return the single number
* @throws NoSuchElementException if the single number is not found
*/
public int singleNumber(int[] nums) {
// Sort the given array
Arrays.sort(nums);
// Compare consecutive pairs of elements
for (int i = 0; i < nums.length; i += 2) {
// If the two elements are different, the first one is the single number, so return its value.
if (i == nums.length - 1) return nums[i];
else if (nums[i] != nums[i + 1]) {
return nums[i];
}
}
// If the single number is not found until the end of the array, throw a NoSuchElementException.
// Note that leetcode does not allow throwing a NoSuchElementException.
// However, since the problem guarantees the existence of a single number, you can replace this line with 'return 0;'.
throw new NoSuchElementException();
}
}
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