How do you solve Maximum Total Subarray Value I on LeetCode?

Maximum Total Subarray Value I (LeetCode #3689) 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: Choosing the entire array maximizes the value.

What is the time complexity of Maximum Total Subarray Value I?

The optimal solution for Maximum Total Subarray Value I runs in O(n) time and uses O(1) space. We only traverse the array twice to find max and min, leading to O(n) complexity.

What is the brute force solution for Maximum Total Subarray Value I?

The brute force approach for Maximum Total Subarray Value I is Brute Force, with O(n²) time complexity and O(1) space complexity. Calculate the value of every possible subarray and sum them up for k selections. This method is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Maximum Total Subarray Value I?

Maximum Total Subarray Value I uses the following concepts: Array, Greedy. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Maximum Total Subarray Value I?

Explain your thought process clearly. Discuss edge cases like single-element arrays. Practice similar problems to build confidence.

What are common mistakes when solving Maximum Total Subarray Value I?

Not considering overlapping subarrays. Forgetting to multiply by k.

#3689

Maximum Total Subarray Value I

Medium

ArrayGreedyHash MapArray

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 maximum total value can be achieved by selecting the entire array k times, as it provides the highest difference between max and min.

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Algorithm

3 steps

1Step 1: Calculate the maximum and minimum of the entire array.
2Step 2: Compute the value as max - min.
3Step 3: Multiply this value by k to get the total.

solution.py2 lines

1def maxTotalValue(nums, k):
2    return (max(nums) - min(nums)) * k

ℹ

Complexity note: We only traverse the array twice to find max and min, leading to O(n) complexity.

1Choosing the entire array maximizes the value.
2The same subarray can be selected multiple times.

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