The Big-Oh, Part 1

The most important concept in computer science isn’t writing code, it’s efficient algorithms. A programmer works to write code to solve a problem. A computer scientist works to create a repeatable method for solving the problem in the most efficient way.

Big-Oh is a notation for expressing the complexity of an algorithm. We usually use it for time complexity, which is the opposite of time efficiency. The higher the time complexity, the lower the time efficiency. In other words, when we use the word complexity in this way, a more complex algorithm is slower than a less complex one.