3513. Number of Unique XOR Triplets I
SourceBiweekly Contest 154 Q2DifficultyMediumRating1663
Description
You are given an integer array nums of length n, where nums is a permutation of the numbers in the range [1, n].
A XOR triplet is defined as the XOR of three elements nums[i] XOR nums[j] XOR nums[k] where i <= j <= k.
Return the number of unique XOR triplet values from all possible triplets (i, j, k).
Example 1:
Input: nums = [1,2]
Output: 2
Explanation:
The possible XOR triplet values are:
(0, 0, 0) → 1 XOR 1 XOR 1 = 1(0, 0, 1) → 1 XOR 1 XOR 2 = 2(0, 1, 1) → 1 XOR 2 XOR 2 = 1(1, 1, 1) → 2 XOR 2 XOR 2 = 2
The unique XOR values are {1, 2}, so the output is 2.
Example 2:
Input: nums = [3,1,2]
Output: 4
Explanation:
The possible XOR triplet values include:
(0, 0, 0) → 3 XOR 3 XOR 3 = 3(0, 0, 1) → 3 XOR 3 XOR 1 = 1(0, 0, 2) → 3 XOR 3 XOR 2 = 2(0, 1, 2) → 3 XOR 1 XOR 2 = 0
The unique XOR values are {0, 1, 2, 3}, so the output is 4.
Constraints:
1 <= n == nums.length <= 1051 <= nums[i] <= nnumsis a permutation of integers from1ton.
Solutions
Solution 1: Bit Manipulation
Thinking
\(\textit{nums}\) is a permutation of \([1,n]\) and indices may repeat, so the set of triple XORs is determined by \(n\). A cubic enumeration does not match the scale.
For \(n \le 2\) the answer equals \(n\). For \(n \ge 3\) the possible XORs fill \([0, 2^{\lfloor \log_2 n \rfloor + 1} - 1]\), which is \(1 \ll \textit{bitLength}(n)\).
Since \(\textit{nums}\) is a permutation of \([1, n]\), the available values are fixed as \(\{1, 2, \ldots, n\}\). With indices satisfying \(i \le j \le k\), the same index may be chosen more than once, so a XOR triplet is equivalent to picking three numbers (with replacement) from this set and taking their XOR.
When \(n \le 2\), enumeration shows the answers are \(1\) (\(n = 1\)) and \(2\) (\(n = 2\)), i.e., the answer equals \(n\).
When \(n \ge 3\), it can be shown that all possible XOR results exactly fill the interval \([0, 2^{k} - 1]\), where \(2^{k}\) is the smallest power of \(2\) strictly greater than \(n\). This value also equals \(2^{\lfloor \log_2 n \rfloor + 1}\), which can be obtained via each language's bit-length function:
For example, when \(n = 3\), \(\textit{bitLength}(3) = 2\), so the answer is \(4\), matching the example set \(\{0, 1, 2, 3\}\).
The time complexity is \(O(1)\), and the space complexity is \(O(1)\).
1 2 3 4 | |
1 2 3 4 5 6 | |
1 2 3 4 5 6 7 | |
1 2 3 4 5 6 7 | |
1 2 3 4 5 6 7 | |
1 2 3 4 5 6 7 8 9 | |