Define Big ‘O’ notation. State the two factors which determine the complexity of an algorithm.

Big 'O' notation is a mathematical notation used to describe the limiting/asymptotic behaviour of an algorithm - it expresses the upper bound on the growth rate of the running time (or space requirement) of an algorithm as a function of the size of its input (in the worst case), ignoring constant factors and lower-order terms. The two factors that determine the complexity of an algorithm are: 1. Time Complexity - the amount of time (number of basic operations) the algorithm takes to execute, as a function of the input size. 2. Space Complexity - the amount of memory/storage the algorithm requires, as a function of the input size.