Search methods, Sort methods, Big-O

We have been learning about big-oh notation in the last couple of weeks. More specifically, we have been learning about three sets of notations: including O, omega, and theta. These sets encompasses  the sets of function that either grow no faster, no slower, or as fast as various base functions f(n).

Looking up the graphical representations of these functions was actually a refresher; as I have not taken any true math courses for quite a while. Review will be necessary.

It was interesting to think of functions not in run time, but in growth. Rather than assessing a function for its capacity to run within seconds, we look towards the growth in the steps as the input increases, as a means of testing the efficiency of a function. This is certainly a new approach to measuring run times, as someone with limited exposure to programming. I look forward to broadening my knowledge in this area over the course of the next few weeks.