How do you solve Find the K-or of an Array on LeetCode?

Find the K-or of an Array (LeetCode #2917) 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: Understanding bit manipulation is crucial for solving problems involving binary operations.

What is the brute force solution for Find the K-or of an Array?

The brute force approach for Find the K-or of an Array is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach checks each bit position from 0 to 31 for every number in the array. It counts how many numbers have that bit set to 1, and if the count meets or exceeds k, that bit is set in the result. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Find the K-or of an Array?

Find the K-or of an Array uses the following concepts: Array, Bit Manipulation. The recommended patterns to study are: Bit Manipulation, Array.

What are the interview tips for Find the K-or of an Array?

Always clarify the constraints and edge cases before diving into coding. Think about both time and space complexity when discussing your approach. Practice explaining your thought process clearly as you code, as communication is key in interviews.

What are common mistakes when solving Find the K-or of an Array?

Forgetting to check all 32 bits, especially when numbers can be large. Not considering edge cases where k is larger than the number of elements.

#2917

Find the K-or of an Array

Easy

ArrayBit ManipulationBit ManipulationArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

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Intuition

Time O(n)Space O(1)

The optimal solution uses a single pass through the array to count the bits directly, resulting in a more efficient algorithm. We keep track of how many numbers have each bit set and build the result in a single loop.

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Algorithm

5 steps

1Step 1: Initialize an array to count the number of set bits for each of the 32 bit positions.
2Step 2: Loop through each number in the array and update the count for each bit position.
3Step 3: Initialize the result to 0.
4Step 4: Loop through the count array and if any bit count is greater than or equal to k, set that bit in the result.
5Step 5: Return the result.

solution.py13 lines

1# Full working Python code
2
3def k_or(nums, k):
4    count = [0] * 32
5    for num in nums:
6        for bit in range(32):
7            if (num >> bit) & 1:
8                count[bit] += 1
9    result = 0
10    for bit in range(32):
11        if count[bit] >= k:
12            result |= (1 << bit)
13    return result

ℹ

Complexity note: The time complexity is O(n) because we only go through the array once to count the bits and then once more to build the result. The space complexity is O(1) since we use a fixed-size array of size 32.

1Understanding bit manipulation is crucial for solving problems involving binary operations.
2Counting occurrences of bits across multiple numbers can lead to efficient solutions.

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