*This works on Linux Firefox with Moonlight 3 Preview Release it is a little slow but it works.*

The following is a brief summary of the functions demonstrated in the application. You can get more detail here.

Function | Description | Example |
---|---|---|

O(1) | Constant complexity regardless of the domain size. | Array direct indexing, Hash table |

O(n) | Linear complexity. As the domain size increases, the time/complexity increases linearly. If you double the items the complexity will double. | Sequential search |

O(log n) | Logarithmic complexity. As the domain size increases, the time/complexity increases logorithmically | Binary Search on sorted data, Lookup in balanced binary tree |

O(n log n) | Log Linear complexity. As the domain size increases, the time/complexity increases at a log linear or geometric rate. | Heap Sort, Merge Sort, Quick Sort^{1} |

O(n²) | Quadratic complexity. As the domain size increases, the time/complexity increases quadratically. | Bubble Sort, Insertion sort |

O(n³) | Cubic complexity. As the domain size increases, the time/complexity increases at a cubic rate. | Naive multiplication of two nxn matrices. |

O(2ⁿ) | Exponential complexity. As the domain size increases, the time/complexity increases exponentialy. | Some graph algoritms like finding the exact solution to the traveling salesman problem. |

^{1}Quick sort has best and average case of O(n log n) but worst case of O(n²)
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