Definition of Big-O

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).

An algorithm with linear running time is preferable to Logarithmic etc.

Glossary:

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Examples: A simple loop which adds up the elements of an array would have Linear O(n) running time.