Programmatically obtaining Big-O efficiency of code

Question

I wonder whether there is any automatic way of determining (at least roughly) the Big-O time complexity of a given function?

If I graphed an O(n) function vs. an O(n

Answer 1

I don't know what's your objective in doing this, but we had a similar problem in a course I was teaching. The students were required to implement something that works at a certain complexity.

In order not to go over their solution manually, and read their code, we used the method @Godeke suggested. The objective was to find students who used linked list instead of a balansed search tree, or students who implemented bubble sort instead of heap sort (i.e. implementations that do not work in the required complexity - but without actually reading their code).

Surprisingly, the results did not reveal students who cheated. That might be because our students are honest and want to learn (or just knew that we'll check this ;-) ). It is possible to miss cheating students if the inputs are small, or if the input itself is ordered or such. It is also possible to be wrong about students who did not cheat, but have large constant values.

But in spite of the possible errors, it is well worth it, since it saves a lot of checking time.