Find the maximum subarray sum.

Our solution for finding the maximum subarray sum processes the input array by iterating through it while maintaining two variables: max_current and max_global. The max_current variable keeps track of the maximum sum of the subarray ending at the current position, while max_global stores the maximum sum encountered so far.

For each element in the array, we update max_current by taking the maximum of the current element alone or the sum of the current element and max_current. This decision ensures that max_current always holds the maximum sum of the subarray that ends at the current element. We then update max_global to be the maximum of max_global and max_current.

If the input array is empty, the function returns 0 since there are no subarrays to consider.

This approach uses a simple iteration and a couple of variables, making it both straightforward and efficient.

Time Complexity: The solution has a time complexity of O(n), where n is the number of elements in the array. This is because we iterate through the array once, performing constant-time operations (comparison and addition) for each element.

Space Complexity: The solution uses O(1) space since it only requires a fixed amount of extra space for the max_current and max_global variables, regardless of the input size. This makes the solution very efficient in terms of space usage.