Have you ever wonder why some algorithms run faster than others, even when they have a worse Big O complexity? Introduction In typical Data Structures and Algorithms course, we learn about the Asymptotic complexity or Big O notation to describe how complex or efficient an algorithm is in terms of time and space. But on thing that’s rarely discussed is that this notation describes the growth of the algorithm. This means that when we compare which algorithm is “better”, we’re stripping away many important factors such as constant factors or even the hardware model which is abstracted away as if it doesn’t even matter. ...