# Solving Leetcode Interviews in Seconds with AI: Maximum Subarray


	# Introduction
	In this blog post, we will explore how to solve the LeetCode problem "53" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like [Chatmagic](https://www.chatmagic.app), we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

	# Problem Statement
	> Given an integer array nums, find the subarray with the largest sum, and return its sum.   Example 1:  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.  Example 2:  Input: nums = [1] Output: 1 Explanation: The subarray [1] has the largest sum 1.  Example 3:  Input: nums = [5,4,-1,7,8] Output: 23 Explanation: The subarray [5,4,-1,7,8] has the largest sum 23.    Constraints:  1 <= nums.length <= 105 -104 <= nums[i] <= 104    Follow up: If you have figured out the O(n) solution, try coding another solution using the divide and conquer approach, which is more subtle. 

	# Explanation
	Here's the solution to find the subarray with the largest sum, along with explanations and the code:

*   **Kadane's Algorithm:** This is a dynamic programming approach. We iterate through the array, keeping track of the current maximum sum ending at the current position and the overall maximum sum encountered so far.
*   **Resetting Current Sum:** If the current maximum sum becomes negative, we reset it to 0, as a negative sum will only decrease the sum of any subsequent subarray.
*   **Updating Overall Max:** In each step, we update the overall maximum sum with the larger value between the current maximum sum and the overall maximum sum.

*   **Runtime Complexity:** O(n)
*   **Storage Complexity:** O(1)

	
	# Code
	```python
	def maxSubArray(nums: list[int]) -> int:
    """
    Finds the contiguous subarray with the largest sum.

    Args:
        nums: An integer array.

    Returns:
        The largest sum of any contiguous subarray.
    """

    max_so_far = nums[0]
    current_max = nums[0]

    for i in range(1, len(nums)):
        current_max = max(nums[i], current_max + nums[i])
        max_so_far = max(max_so_far, current_max)

    return max_so_far
	```