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Maximum Subarray Sum Problem

Maximum Subarray Sum Problem

23 Sep 2025
Beginner
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3 min read
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The Maximum Subarray Sum Problem is a classic algorithmic problem where you are given an array of integers (which may include negative numbers) and need to find the contiguous subarray with the largest sum. Return the maximum sum. This problem is efficiently solved using Kadane’s Algorithm. 

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Example:

  • Input: nums = [-2, 1, -3, 4, -1, 2, 1, -5, 4]
  • Output: 6
  • Explanation: The subarray [4, -1, 2, 1] has the largest sum = 6.

Logic

Enter an array of numbers (comma-separated) to find the maximum subarray sum.

Program (Python - Kadane’s Algorithm)

The following Python code uses Kadane’s Algorithm to solve the Maximum Subarray Sum Problem efficiently with O(n) time complexity.


def maxSubArray(nums):
    max_sum = nums[0]
    current_sum = nums[0]
    
    for num in nums[1:]:
        current_sum = max(num, current_sum + num)
        max_sum = max(max_sum, current_sum)
    
    return max_sum

# Example usage
nums = [-2, 1, -3, 4, -1, 2, 1, -5, 4]
print(maxSubArray(nums))  # Output: 6

Output

For the input nums = [-2, 1, -3, 4, -1, 2, 1, -5, 4], the output is:

6

Explanation:

The subarray [4, -1, 2, 1] has the maximum sum of 6.

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About Author
Amit Kumar Ghosh (SDE and Mentor)

As a software developer with a wealth of experience, he brings a unique combination of technical acumen and a passion for mentorship to my role. With 6 years of experience, he has honed the skills in C/C++, Java, Python, SQL, C#, JavaScript, React, Java Spring etc. and has a proven track record of delivering high-quality, scalable software solutions and core Computer fundamental knowledge DSA, OOPs, CN, OS etc.

As a teacher, his approach revolves around interactive techniques, prioritizing hands-on learning and real-world projects. He explains concepts clearly, offer practical examples, and encourage questions to foster a supportive environment.
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