Polynomial time and exponential time

 Below are some common Big-O functions while analyzing algorithms.

• O(1) - constant time
• O(log(n)) - logarithmic time
• O((log(n))^c) - polylogarithmic time
• O(n) - linear time
• O(n²) - quadratic time
• O(n^c) - polynomial time
• O(cⁿ) - exponential time
• O(n!) - factorial time

(n = size of input, c = some constant)

Here is the model graph representing Big-O complexity of some functions

O(1) = O(yeah)
O(logn) = O(nice)
O(n) = O(k)
O(n^2) = O(my)
O(2^n) = O(no)
O(n!) = O(mg)
O(n^n) = O(sh*t!)