This "cheat sheet" is designed to be a super-high level view of common and/or important computer science concepts. Good for test reviews, preparing for job interviews, brushing up on the basics, becoming a better person, or light reading for putting your significant other to sleep. I will continue to update this so if you have any suggestions or corrections please send a pull request or contact me. Licensed under http://creativecommons.org/licenses/by-sa/3.0/.
+ Limiting behavior (all the second sections are as limit(n)->infinity)
* Big O - f is bounded by g :: f(n) <= g(n)*c (for some constant c) :: an upper bound, can be much higher than actual performance because this is not a tight bound, for example a log(n) algorithm technically is O(n!) but is obviously way better than something that actually gets n! performance
* Small or Little o - f dominated by g :: f(n) < g(n)*c; f(n)/g(n) = 0 :: g gets much larger
* Big Omega - f is bounded below by g :: |f(n)| >= g(n)*c :: a lower bound, bu