Assume that I have designed an algorithm, IS(G, k), for the decision version of the independent set problem. IS(G, k), implemented as a method, returns True if the input instance (G, k) has an independent of size at least k, and False otherwise.

Design an algorithm that reuses IS(G, k) to solve the optimization version of the problem - the problem of finding the maximum size of an independent set. Describe your algorithm in pseudocode, and then using the Big-O notation, give an upper bound on the number of calls to IS(G, k) your algorithm makes in the worst-case scenario.