Python 3.14 (Coding): Maximum Subarray Test

The solution approach to the problem is using Kadane's algorithm. The goal is to find the maximum sum of a contiguous subarray within a given array of integers. This algorithm ensures a time complexity of O(n) by tracking the maximum subarray sum while iterating through the array. The function maxSubArray takes a vector of integers nums as input and returns an integer representing the maximum subarray sum. The algorithm iterates through the array, starting from the second element. For each element, if the previous element's contribution to the subarray sum is positive, it adds that contribution to the current element. This step efficiently accumulates the sum of the contiguous subarray ending at the current index. The variable max_sum is updated in each iteration, holding the maximum subarray sum encountered so far. By the end of the loop, it will contain the maximum subarray sum for the entire array. The function returns max_sum, representing the maximum sum of a contiguous subarray. In summary, this code implements Kadane's algorithm to efficiently find the maximum subarray sum within a given array. It optimizes the process by utilizing previous subarray contributions when they are positive. This algorithm is widely used for solving the "Maximum Subarray" problem due to its simplicity and linear time complexity.