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When you say that something is O(N) or O(N^2) or whatever, you are saying that as N changes then the resource in question (time or memory normally) changes with that relation to it. So if something is O(N) and N doubles, then the time taken doubles.
To be pedantic, that's not true. O(N) means that the growth is at most linear. O(N^2) means that the growth is at most quadratic. This means that any algorithm that is O(N) is also O(N log N) and O(N^2).

If you want to express that an algorithm is linear (and not worst case linear), the correct function is use is called Θ.

Note also that hash lookups are, worst case, Θ(N). There's always a chance that all hash keys map to the same value, resulting in a linear list that needs to be searched.


In reply to Re^2: elsif chain vs. dispatch by JavaFan
in thread elsif chain vs. dispatch by sflitman

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