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Formatted question description: https://leetcode.ca/all/2433.html
2433. Find The Original Array of Prefix Xor
- Difficulty: Medium.
- Related Topics: Array, Bit Manipulation.
- Similar Questions: Single Number III, Count Triplets That Can Form Two Arrays of Equal XOR, Decode XORed Array.
Problem
You are given an integer array pref of size n. Find and return the array **arr of size n that satisfies**:
pref[i] = arr[0] ^ arr[1] ^ ... ^ arr[i].
Note that ^ denotes the bitwise-xor operation.
It can be proven that the answer is unique.
Example 1:
Input: pref = [5,2,0,3,1]
Output: [5,7,2,3,2]
Explanation: From the array [5,7,2,3,2] we have the following:
- pref[0] = 5.
- pref[1] = 5 ^ 7 = 2.
- pref[2] = 5 ^ 7 ^ 2 = 0.
- pref[3] = 5 ^ 7 ^ 2 ^ 3 = 3.
- pref[4] = 5 ^ 7 ^ 2 ^ 3 ^ 2 = 1.
Example 2:
Input: pref = [13]
Output: [13]
Explanation: We have pref[0] = arr[0] = 13.
Constraints:
-
1 <= pref.length <= 10^5 -
0 <= pref[i] <= 10^6
Solution (Java, C++, Python)
-
class Solution { public int[] findArray(int[] pref) { int n = pref.length; int[] ans = new int[n]; ans[0] = pref[0]; for (int i = 1; i < n; ++i) { ans[i] = pref[i - 1] ^ pref[i]; } return ans; } } -
class Solution { public: vector<int> findArray(vector<int>& pref) { int n = pref.size(); vector<int> ans = {pref[0]}; for (int i = 1; i < n; ++i) { ans.push_back(pref[i - 1] ^ pref[i]); } return ans; } }; -
class Solution: def findArray(self, pref: List[int]) -> List[int]: ans = [pref[0]] for a, b in pairwise(pref): ans.append(a ^ b) return ans -
func findArray(pref []int) []int { n := len(pref) ans := []int{pref[0]} for i := 1; i < n; i++ { ans = append(ans, pref[i-1]^pref[i]) } return ans } -
function findArray(pref: number[]): number[] { let ans = pref.slice(); for (let i = 1; i < pref.length; i++) { ans[i] = pref[i - 1] ^ pref[i]; } return ans; } -
impl Solution { pub fn find_array(pref: Vec<i32>) -> Vec<i32> { let n = pref.len(); let mut res = vec![0; n]; res[0] = pref[0]; for i in 1..n { res[i] = pref[i] ^ pref[i - 1]; } res } }
Explain:
nope.
Complexity:
- Time complexity : O(n).
- Space complexity : O(n).