Dynamic Programming Questions Medium
The time complexity of the Dynamic Programming approach for solving the Maximum Subarray problem is O(n), where n is the size of the input array.
In the Dynamic Programming approach, we use a bottom-up approach to calculate the maximum subarray sum for each subarray ending at index i. We start by initializing the maximum subarray sum as the first element of the array. Then, for each subsequent element, we compare the current element with the sum of the current element and the maximum subarray sum ending at the previous element. We update the maximum subarray sum if the sum of the current element and the previous maximum subarray sum is greater than the current element itself.
By iterating through the entire array once, we can calculate the maximum subarray sum for each subarray ending at each index. Therefore, the time complexity of the Dynamic Programming approach for solving the Maximum Subarray problem is O(n).