Maximum Absolute Sum of Any Subarray

Maximum Absolute Sum of Any Subarray is a Medium Data Structures and Algorithms interview problem you can solve, run and submit on Thita.ai. It belongs to the Dynamic Programming (DP) Patterns pattern, in the 1D Array (Kadane's Algorithm for Max/Min Subarray) subpattern.

Problem statement

You are given an integer array nums. The absolute sum of a subarray [numsl, numsl+1, ..., numsr-1, numsr] is abs(numsl + numsl+1 + ... + numsr-1 + numsr).

Return the maximum absolute sum of any (possibly empty) subarray of nums.

Note that abs(x) is defined as follows: If x is a negative integer, then abs(x) = -x.

If x is a non-negative integer, then abs(x) = x.

Example 1: Input: nums = [1,-3,2,3,-4] Output: 5 Explanation: The subarray [2,3] has absolute sum = abs(2+3) = abs(5) = 5.

Example 2: Input: nums = [2,-5,1,-4,3,-2] Output: 8 Explanation: The subarray [-5,1,-4] has absolute sum = abs(-5+1-4) = abs(-8) = 8.

Constraints: 1 <= nums.length <= 105 -104 <= nums[i] <= 104

Topics and companies

Topics: nan.

Reported in interviews at nan.

How to practise Maximum Absolute Sum of Any Subarray on Thita.ai

Starter code is provided in C, C#, C++, dart, elixir, erlang, Go, Java, JavaScript, Kotlin, PHP, Python, python3, racket, Ruby, Rust, Scala, Swift and TypeScript. Your solution runs against 5 test cases for this problem, with the AI coach available for a hint when you are stuck rather than a finished answer. The reference solution runs in O(n) time and O(1) space.

Open Maximum Absolute Sum of Any Subarray in the code editor, or read the Maximum Absolute Sum of Any Subarray editorial for a worked solution with its approach and complexity analysis.

Where Maximum Absolute Sum of Any Subarray sits in the DSA pattern sheet

Problems related to Maximum Absolute Sum of Any Subarray

Other problems that use the same 1D Array (Kadane's Algorithm for Max/Min Subarray) and Dynamic Programming (DP) Patterns techniques:

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