I understand the principles of asymptotic notation, and I get what it means when something is O(1) or O(n2) for example. But what does O(log n) mean? or O(n log n) for example?
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I understand the principles of asymptotic notation, and I get what it means when something is O(1) or O(n2) for example. But what does O(log n) mean? or O(n log n) for example?
Check: en.wikipedia.org/wiki/Big_O_notation
Remeber that log increases slowly than a an exponential function. So, if you have an algorithm that is n^2 and other, that doing the same, has a logarithmic function, the last would be more efficient (in general term, not always!).
To evaluate the complexity of a function (or algorithm) you must take in consideration the execution in time and space, mainly. You can evaluate a function or algorithm with other parameters, but, initially, those two would be OK.
EDIT:
http://en.wikibooks.org/wiki/Data_Structures/Asymptotic_Notation
Also, check the sorting algorithms. Will give great insight about complexity.