Definition: Big - O Notation
When measuring how fast algorithms perform, the Big-O notation is a handy way of stating the complexity of an algorithm (and how long it takes to run) according to the size of the input N. You would always expect that a sorting algorithm would take longer to sort 1,000 elements than 10. The question is "roughly how much longer?" This is what Big-O tells you. It is used by computer scientists to describe algorithms.
There are four commonly used Orders.
- Linear. O(n)
- Logarithmic. O(log(n)).
- n-log-n. O(n * log(n))
- Quadratic. O(n2).
Glossary:
A B C D E F G H I J K L M N O P Q R S T U V W X Y ZExamples:
A simple loop which adds up the elements of an array would have Linear O(n) running time.
