Time complexity of algorithms

O(1) - constant time
O(log(n)) - logarithmic time (binary search)
O(n) - linear time (search min element in unordered list)
O(n * log(n)) - quick sort
O(n**2) - n-sqaured (bubble sort)
O(2**n) - exponential time (recursive problems)
O(n!) - factorial time (traveling salesman problem via brute-force search)

Computational Complexity

Complexity theory: P vs NP

Computational Complexity MIT lecture

• You can't enginner luck
• Solving problem is harder than checking solutions