Big O

Lesson

Big O is a way to describe the rate of growth of an algorithm based on the input. Specifically, Big O is the upper bound runtime of and algorithm. It is defined as

$\mathrm{f}\left(\mathrm{n}\right)\in\mathrm{O}\left(\mathrm{g}\left(\mathrm{n}\right)\right) \rightarrow \mathrm{f}\left(\mathrm{n}\right)\le\mathrm{\mathrm{c}\mathrm{g}\left(\mathrm{n}\right)}$

where $(c > 0)$ and $(n \ge 0)$