What is the time complexity of Maximum Number of Distinct Elements After Operations?

The optimal solution for Maximum Number of Distinct Elements After Operations runs in O(n log n) time and uses O(n) space. Sorting the array takes O(n log n), and using a set for distinct elements takes O(n).

What is the brute force solution for Maximum Number of Distinct Elements After Operations?

The brute force approach for Maximum Number of Distinct Elements After Operations is Brute Force, with O(n²) time complexity and O(n) space complexity. Try every possible combination of adding values from [-k, k] to each element and count distinct elements. This is inefficient but straightforward. The optimal Optimal Solution approach improves this to O(n log n).

What algorithm or data structure is used to solve Maximum Number of Distinct Elements After Operations?

Maximum Number of Distinct Elements After Operations uses the following concepts: Array, Greedy, Sorting. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Maximum Number of Distinct Elements After Operations?

Explain your thought process clearly. Discuss edge cases like all elements being the same. Practice similar problems to build intuition.

What are common mistakes when solving Maximum Number of Distinct Elements After Operations?

Not considering the range of adjustments correctly. Overlooking the need to sort for duplicates.

#3397

Maximum Number of Distinct Elements After Operations

Medium

ArrayGreedySortingHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n log n)Space O(n)

Sort the array and adjust each element to maximize distinct values by filling gaps with the allowed range.

⚙️

Algorithm

3 steps

1Step 1: Sort the array to handle duplicates easily.
2Step 2: Use a set to track distinct elements and iterate through the sorted array.
3Step 3: For each element, calculate the nearest available distinct value within the range and add it to the set.

solution.py8 lines

1def maxDistinct(nums, k):
2    nums = sorted(set(nums))
3    distinct = set()
4    for num in nums:
5        while num in distinct:
6            num += 1
7        distinct.add(num)
8    return len(distinct)

ℹ

Complexity note: Sorting the array takes O(n log n), and using a set for distinct elements takes O(n).

1Sorting helps manage duplicates effectively.
2Using a set ensures uniqueness while adjusting values.

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