Leetcode #2909: Minimum Sum of Mountain Triplets II
In this guide, we solve Leetcode #2909 Minimum Sum of Mountain Triplets II 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
You are given a 0-indexed array nums of integers. A triplet of indices (i, j, k) is a mountain if: i < j < k nums[i] < nums[j] and nums[k] < nums[j] Return the minimum possible sum of a mountain triplet of nums.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Array
Intuition
The constraints allow a direct scan that keeps only the essential state.
By translating the requirements into a clean loop, the logic stays easy to reason about.
Approach
Iterate through the data once, updating the state needed to compute the answer.
Return the final state after the traversal is complete.
Steps:
- Parse the input.
- Iterate and update state.
- Return the computed answer.
Example
Input: nums = [8,6,1,5,3]
Output: 9
Explanation: Triplet (2, 3, 4) is a mountain triplet of sum 9 since:
- 2 < 3 < 4
- nums[2] < nums[3] and nums[4] < nums[3]
And the sum of this triplet is nums[2] + nums[3] + nums[4] = 9. It can be shown that there are no mountain triplets with a sum of less than 9.
Python Solution
class Solution:
def minimumSum(self, nums: List[int]) -> int:
n = len(nums)
right = [inf] * (n + 1)
for i in range(n - 1, -1, -1):
right[i] = min(right[i + 1], nums[i])
ans = left = inf
for i, x in enumerate(nums):
if left < x and right[i + 1] < x:
ans = min(ans, left + x + right[i + 1])
left = min(left, x)
return -1 if ans == inf else ans
Complexity
The time complexity is , and the space complexity is . 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.