Leetcode #1574: Shortest Subarray to be Removed to Make Array Sorted
In this guide, we solve Leetcode #1574 Shortest Subarray to be Removed to Make Array Sorted in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Given an integer array arr, remove a subarray (can be empty) from arr such that the remaining elements in arr are non-decreasing. Return the length of the shortest subarray to remove.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Stack, Array, Two Pointers, Binary Search, Monotonic Stack
Intuition
The constraints hint that we can reason about two ends of the data at once, which is perfect for a two-pointer scan.
Moving one pointer at a time keeps the invariant intact and avoids nested loops.
Approach
Place pointers at the left and right ends and move them based on the comparison or target condition.
This yields a clean linear pass after any required sorting.
Steps:
- Set left and right pointers.
- Move a pointer based on the condition.
- Update the best answer while scanning.
Example
Input: arr = [1,2,3,10,4,2,3,5]
Output: 3
Explanation: The shortest subarray we can remove is [10,4,2] of length 3. The remaining elements after that will be [1,2,3,3,5] which are sorted.
Another correct solution is to remove the subarray [3,10,4].
Python Solution
class Solution:
def findLengthOfShortestSubarray(self, arr: List[int]) -> int:
n = len(arr)
i, j = 0, n - 1
while i + 1 < n and arr[i] <= arr[i + 1]:
i += 1
while j - 1 >= 0 and arr[j - 1] <= arr[j]:
j -= 1
if i >= j:
return 0
ans = min(n - i - 1, j)
for l in range(i + 1):
r = bisect_left(arr, arr[l], lo=j)
ans = min(ans, r - l - 1)
return ans
Complexity
The time complexity is , where is the length of the array. The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.