# Big O notation

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## About

*NOTE: This page is a daughter page of:*

**Programming interviews**

**Big O notation** helps classify the running time and space requirements of algorithms based on how they they respond to input size (n). I learnt big O notation back in first year undergraduate, but occasionally forget the names of different notations, hence I've added the table below to remind me:

## Big O notation

Notation | Name |
---|---|

O(1) |
constant |

O(log n) |
logarithmic ... or "linearithmic" for O(n log n) |

O(n) |
linear |

O(n^{2}) |
quadratic |

*O(n^{c}) |
polynomial |

*O(c^{n}) |
exponential |

*O(n!) |
factorial |

> * = where *c>1*