Is Maximum Ascending Subarray Sum easy or hard?

Maximum Ascending Subarray Sum is classified as an Easy problem on LeetCode. The challenge focuses on recognizing ascending segments and maintaining a running sum, which makes it a good introduction to array traversal and subarray problems.

Maximum Ascending Subarray Sum Python/Java solution

The common implementation in Python or Java performs a linear scan with two variables: currentSum and maxSum. Compare each element with the previous one to determine whether the ascending sequence continues or resets. This implementation runs in O(n) time and uses constant space.

How to solve Maximum Ascending Subarray Sum in O(n)?

Iterate through the array while maintaining a running sum for the current ascending segment. If nums[i] > nums[i-1], add nums[i] to the current sum; otherwise reset the sum to nums[i]. Track the maximum value of this running sum during the traversal. This single-pass strategy guarantees O(n) time.

What is the best approach for Maximum Ascending Subarray Sum?

The optimal approach uses a single pass through the array while tracking the current ascending segment sum. If the current number is greater than the previous one, add it to the running sum; otherwise reset the sum. This method runs in O(n) time with O(1) space and is the solution typically expected in interviews.

Is Maximum Ascending Subarray Sum asked at Google/Amazon/Meta?

Problems based on array traversal and subarray patterns frequently appear in interviews at companies like Amazon, Google, and Meta. While this exact question may vary, the underlying concept of tracking increasing segments or subarray sums is commonly tested.

What data structure is used in Maximum Ascending Subarray Sum?

The problem primarily uses a basic array traversal technique. No advanced data structures are required—just variables to track the current ascending subarray sum and the maximum sum found so far.

What is the time complexity of Maximum Ascending Subarray Sum?

The optimal algorithm runs in O(n) time because it scans the array exactly once. Each element is processed with a constant number of comparisons and additions. Space complexity is O(1) since only a few variables are used to track the running and maximum sums.

Description Hints 2 Solution Video 10:16

1800. Maximum Ascending Subarray Sum

Easy66.3% acceptance6 companies

Given an array of positive integers nums, return the maximum possible sum of an ascending subarray in nums.

A subarray is defined as a contiguous sequence of numbers in an array.

A subarray [nums_l, nums_l+1, ..., nums_r-1, nums_r] is ascending if for all i where l <= i < r, nums_i < nums_i+1. Note that a subarray of size 1 is ascending.

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

Asked at 6 companies

TCS Microsoft

Google Amazon Meta Bloomberg

Topics

Array

Hints open one at a time

Hint 1

It is fast enough to check all possible subarrays

Hint 2

The end of each ascending subarray will be the start of the next

10:16

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