1800. Maximum Ascending Subarray Sum LeetCode Solution
In this guide, you will get 1800. Maximum Ascending Subarray Sum LeetCode Solution with the best time and space complexity. The solution to Maximum Ascending Subarray Sum problem is provided in various programming languages like C++, Java, and Python. This will be helpful for you if you are preparing for placements, hackathons, interviews, or practice purposes. The solutions provided here are very easy to follow and include detailed explanations.
Problem Statement of Maximum Ascending Subarray Sum
Given an array of positive integers nums, return the maximum possible sum of an strictly increasing subarray in nums.
A subarray is defined as a contiguous sequence of numbers in an array.
Example 1:
Input: nums = [10,20,30,5,10,50]
Output: 65
Explanation: [5,10,50] is the ascending subarray with the maximum sum of 65.
Example 2:
Input: nums = [10,20,30,40,50]
Output: 150
Explanation: [10,20,30,40,50] is the ascending subarray with the maximum sum of 150.
Example 3:
Input: nums = [12,17,15,13,10,11,12]
Output: 33
Explanation: [10,11,12] is the ascending subarray with the maximum sum of 33.
Constraints:
1 <= nums.length <= 100
1 <= nums[i] <= 100
Complexity Analysis
Time Complexity: O(n)
Space Complexity: O(1)
1800. Maximum Ascending Subarray Sum LeetCode Solution in C++
class Solution {
public:
int maxAscendingSum(vector<int>& nums) {
int ans = 0;
int sum = nums[0];
for (int i = 1; i < nums.size(); ++i)
if (nums[i] > nums[i - 1]) {
sum += nums[i];
} else {
ans = max(ans, sum);
sum = nums[i];
}
return max(ans, sum);
}
}; /* code provided by PROGIEZ */
1800. Maximum Ascending Subarray Sum LeetCode Solution in Java
class Solution {
public int maxAscendingSum(int[] nums) {
int ans = 0;
int sum = nums[0];
for (int i = 1; i < nums.length; ++i)
if (nums[i] > nums[i - 1]) {
sum += nums[i];
} else {
ans = Math.max(ans, sum);
sum = nums[i];
}
return Math.max(ans, sum);
}
} // code provided by PROGIEZ
1800. Maximum Ascending Subarray Sum LeetCode Solution in Python
class Solution:
def maxAscendingSum(self, nums: list[int]) -> int:
ans = 0
sum = nums[0]
for i in range(1, len(nums)):
if nums[i] > nums[i - 1]:
sum += nums[i]
else:
ans = max(ans, sum)
sum = nums[i]
return max(ans, sum) # code by PROGIEZ
