Big O

In this section we are going to start by practicing the ability to identify Big O efficiencies of algorithms and functions you began to develop in the previous section.

Here we have a function that returns an array of all binary strings of length n. Because each digit of the string can be either 1 or 0, the number of strings grows very quickly with respect to the size of the strings.


Print the Big O of this function to the console. It will be a function of the size of the strings produced, n. Use the caret, "^", to denote exponents. For example O(n^2) is quadratic ("n squared").

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Each digit of the string can be one of two possibilities: either 1 or 0. There are n digits in each string. This means that to find the total number strings (which is equal to the total amount of work done), just multiply n 2's together. The Big O describes this amount of work.