Big O notation
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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(n2) | quadratic |
| O(nc) * | polynomial |
| O(cn) * | exponential |
| O(n!) * | factorial |
> * = where c>1
