What is the time complexity of Minimum Prefix Removal to Make Array Strictly Increasing?

The optimal solution for Minimum Prefix Removal to Make Array Strictly Increasing runs in O(n) time and uses O(1) space. This approach only requires a single pass through the array, leading to linear time complexity.

What is the brute force solution for Minimum Prefix Removal to Make Array Strictly Increasing?

The brute force approach for Minimum Prefix Removal to Make Array Strictly Increasing is Brute Force, with O(n²) time complexity and O(1) space complexity. Check every possible prefix removal to find the minimum length that leaves a strictly increasing array. This involves examining all prefixes and their resulting arrays. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Minimum Prefix Removal to Make Array Strictly Increasing?

Minimum Prefix Removal to Make Array Strictly Increasing uses the following concepts: Array. The recommended patterns to study are: Array, Greedy.

What are the interview tips for Minimum Prefix Removal to Make Array Strictly Increasing?

Clarify the problem constraints. Discuss edge cases like single-element arrays. Explain your thought process clearly.

What are common mistakes when solving Minimum Prefix Removal to Make Array Strictly Increasing?

Not checking the entire array for strictness. Confusing strictly increasing with non-decreasing.

#3818

Minimum Prefix Removal to Make Array Strictly Increasing

Medium

ArrayArrayGreedy

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)

Instead of checking all prefixes, we can find the last point where the array stops being strictly increasing. This allows us to directly calculate the prefix length to remove.

⚙️

Algorithm

3 steps

1Step 1: Traverse the array from the end to find the first index where nums[i] >= nums[i + 1].
2Step 2: If such an index is found, return index + 1 as the minimum prefix length to remove.
3Step 3: If no such index exists, return 0 since the array is already strictly increasing.

solution.py5 lines

1def min_prefix_removal(nums):
2    for i in range(len(nums) - 2, -1, -1):
3        if nums[i] >= nums[i + 1]:
4            return i + 1
5    return 0

ℹ

Complexity note: This approach only requires a single pass through the array, leading to linear time complexity.

1Identify the last point of non-increasing order.
2Removing elements from the start simplifies the problem.

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