Dynamic Programming Questions Medium
The time complexity of the Dynamic Programming approach for solving the Maximum Product Subarray problem is O(n), where n is the length of the input array.
In the Dynamic Programming approach, we maintain two variables, maxProduct and minProduct, which represent the maximum and minimum product subarrays ending at the current index. We update these variables as we iterate through the array, considering the current element and the previously calculated maximum and minimum products.
By keeping track of the maximum and minimum products at each index, we can handle both positive and negative numbers in the array. This approach allows us to find the maximum product subarray efficiently.
Since we iterate through the array once, the time complexity of the Dynamic Programming approach is O(n), where n is the length of the input array.