How do you solve Make Array Non-decreasing on LeetCode?

Make Array Non-decreasing (LeetCode #3523) 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: Iterating backwards helps maintain order while counting.

What is the time complexity of Make Array Non-decreasing?

The optimal solution for Make Array Non-decreasing runs in O(n) time and uses O(1) space. This solution runs in linear time as it processes each element once, maintaining a constant space.

What is the brute force solution for Make Array Non-decreasing?

The brute force approach for Make Array Non-decreasing is Brute Force, with O(n²) time complexity and O(1) space complexity. Try every possible subarray and replace it with its maximum, checking if the array becomes non-decreasing. This approach is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Make Array Non-decreasing?

Make Array Non-decreasing uses the following concepts: Array, Stack, Greedy, Monotonic Stack. The recommended patterns to study are: Greedy, Monotonic Stack.

What are the interview tips for Make Array Non-decreasing?

Explain your thought process clearly. Consider edge cases and test your solution. Use examples to illustrate your approach.

What are common mistakes when solving Make Array Non-decreasing?

Not considering edge cases where the array is already non-decreasing. Failing to update the last maximum correctly.

#3523

Make Array Non-decreasing

Medium

ArrayStackGreedyMonotonic StackGreedyMonotonic Stack

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n)Space O(1)

By iterating backwards, we can track the maximum values and determine the longest non-decreasing sequence efficiently.

⚙️

Algorithm

3 steps

1Step 1: Initialize a variable to track the last maximum value and the size of the resulting array.
2Step 2: Iterate through the array from the end to the start, updating the last maximum and counting elements that can be part of the non-decreasing sequence.
3Step 3: Return the size of the resulting non-decreasing array.

solution.py8 lines

1def maxNonDecreasing(nums):
2    last_max = float('inf')
3    count = 0
4    for num in reversed(nums):
5        if num <= last_max:
6            count += 1
7            last_max = num
8    return count

ℹ

Complexity note: This solution runs in linear time as it processes each element once, maintaining a constant space.

1Iterating backwards helps maintain order while counting.
2Replacing subarrays with their maximum can help form longer non-decreasing sequences.

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