Simple explanation - Runtime complexity

Dot point:

- assume each n value can be determined based on the number of iterating its value.

- imagine each row and column value increases, that length is the one to decide its n value.

e.g. 1 row, 1 column = [n = 1], 2 row, 2 column = [n = 2].

What Is the Runtime Complexity or Big ‘O’ Notation?

"We can say that the amount of work had to do N squared O(n²) = (2², 3², 4²) or quadratic runtime."

 

Linear time = O(n)

Constatn time = O(1)

Quadratic time = O(n²)

The O, in this case, stand for Big ‘O’, because is literally a big O.