How do you solve Longest Subsequence With Non-Zero Bitwise XOR on LeetCode?

Longest Subsequence With Non-Zero Bitwise XOR (LeetCode #3702) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: The XOR of the entire array determines the possibility of a non-zero result.

What is the time complexity of Longest Subsequence With Non-Zero Bitwise XOR?

The optimal solution for Longest Subsequence With Non-Zero Bitwise XOR runs in O(n) time and uses O(1) space. Only one pass through the array is needed to compute the XOR, hence O(n).

What is the brute force solution for Longest Subsequence With Non-Zero Bitwise XOR?

The brute force approach for Longest Subsequence With Non-Zero Bitwise XOR is Brute Force, with O(n²) time complexity and O(1) space complexity. Generate all possible subsequences and check their XOR. This is straightforward but inefficient for large arrays. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Longest Subsequence With Non-Zero Bitwise XOR?

Longest Subsequence With Non-Zero Bitwise XOR uses the following concepts: Array, Bit Manipulation. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Longest Subsequence With Non-Zero Bitwise XOR?

Explain your thought process clearly. Consider edge cases like all elements being the same. Practice similar bit manipulation problems.

What are common mistakes when solving Longest Subsequence With Non-Zero Bitwise XOR?

Assuming all subsequences need to be checked. Not considering the XOR of the entire array first.

#3702

Longest Subsequence With Non-Zero Bitwise XOR

Medium

ArrayBit ManipulationHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(1)

💡

Intuition

Time O(n)Space O(1)

If the XOR of the entire array is non-zero, the answer is the length of the array. If it's zero, removing one element may yield a non-zero XOR.

⚙️

Algorithm

3 steps

1Step 1: Calculate the XOR of the entire array.
2Step 2: If the XOR is non-zero, return the length of the array.
3Step 3: If the XOR is zero, return the length of the array minus one.

solution.py5 lines

1def longest_non_zero_xor(nums):
2    total_xor = 0
3    for num in nums:
4        total_xor ^= num
5    return len(nums) if total_xor != 0 else len(nums) - 1

ℹ

Complexity note: Only one pass through the array is needed to compute the XOR, hence O(n).

1The XOR of the entire array determines the possibility of a non-zero result.
2Removing one element can change the XOR from zero to non-zero.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.