What is Big O Notation

When we discussing Programming Algorithm, we will use BIG O NOTATION.

Here’s a quick understading

• It’s written as: O(1), O(n), O(n^2), O(nlog n) …
• The Logarithm log in Big-O-Notation, means log with base 2
• Big-O-Notation doesn’t know concrete time cost, thus there’s no UNIT for it, e.g. seconds, hours
• Big-O-Notation only shows the time cost trends when data growing

5 Most Common Algorithm

Here’s 5 most common algorithm that listing as order from fast to slow :

1. O(log n) Logarithmic time, such as binary search
2. O(n) Linear time, such as simple search
3. O(n * log n) such as Quick Sort
4. O(n2) such as Select sort
5. O(n!) such as Traveller problem

Basic Logarithm

To have better understanding for Big O Notation, we need understand Logarithm.

Definition

Logrithm Properties

Important note:

• the bases of all logarithms in the expression must be the same.
• the arguments of the logarithms must be positive and the bases of the logarithms must be positive and not equal to 1 in order for this property to hold!