How do you solve Final Element After Subarray Deletions on LeetCode?

Final Element After Subarray Deletions (LeetCode #3828) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(1) time complexity and O(1) space complexity. Key insight: Only endpoints can be protected.

What is the time complexity of Final Element After Subarray Deletions?

The optimal solution for Final Element After Subarray Deletions runs in O(1) time and uses O(1) space. The time complexity is constant since we only compare two values, and space complexity is also constant as no additional space is used.

What is the brute force solution for Final Element After Subarray Deletions?

The brute force approach for Final Element After Subarray Deletions is Brute Force, with O(n²) time complexity and O(1) space complexity. This approach explores all possible subarrays that can be removed in each turn, simulating the game until one element remains. It checks every combination of moves for both players, which can be inefficient. The optimal Optimal Solution approach improves this to O(1).

What algorithm or data structure is used to solve Final Element After Subarray Deletions?

Final Element After Subarray Deletions uses the following concepts: Array, Math, Brainteaser, Game Theory. The recommended patterns to study are: Game Theory, Dynamic Programming.

What are the interview tips for Final Element After Subarray Deletions?

Explain your thought process clearly. Discuss edge cases and constraints. Practice similar game theory problems.

What are common mistakes when solving Final Element After Subarray Deletions?

Not considering optimal moves for both players. Overlooking the importance of endpoints.

#3828

Final Element After Subarray Deletions

Medium

ArrayMathBrainteaserGame TheoryGame TheoryDynamic Programming

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(1)Space O(1)

Alice can only protect the endpoints of the array, as Bob can always remove any middle element. Hence, the optimal strategy revolves around preserving the maximum of the endpoints.

⚙️

Algorithm

2 steps

1Step 1: Identify the maximum of the first and last elements of the array.
2Step 2: Return the maximum value since Alice will always choose to protect it.

solution.py2 lines

1def finalElement(nums):
2    return max(nums[0], nums[-1])

ℹ

Complexity note: The time complexity is constant since we only compare two values, and space complexity is also constant as no additional space is used.

1Only endpoints can be protected.
2Bob can always remove middle elements.

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