What is the space complexity of the dynamic programming solution for the Fibonac
Practice Questions
Q1
What is the space complexity of the dynamic programming solution for the Fibonacci sequence using memoization?
O(1)
O(n)
O(n^2)
O(log n)
Questions & Step-by-Step Solutions
What is the space complexity of the dynamic programming solution for the Fibonacci sequence using memoization?
Step 1: Understand what Fibonacci sequence is. It is a series of numbers where each number is the sum of the two preceding ones, usually starting with 0 and 1.
Step 2: Know that a dynamic programming solution with memoization stores previously computed Fibonacci numbers to avoid recalculating them.
Step 3: Realize that in this approach, we need to keep track of all Fibonacci numbers from 0 up to n, where n is the number for which we want to find the Fibonacci value.
Step 4: Understand that storing these computed values requires space. Specifically, we need to store n + 1 values (from 0 to n).
Step 5: Conclude that the space required to store these values is proportional to n, which is expressed as O(n) in Big O notation.
