Tinsology

The word optimal has become a buzz word that gets tossed around too easily. Something a professor of mine pointed out a few weeks ago: By definition, optimal is something that isn’t realistic to achieve in the context of programming or software engineering. If something is optimal, there is no room for improvement, which is never the case. Some people may be irritated by the misuse of this word, but I think what is worse is the practice of optimizing.

There is a fine line between making meaningful improvements to the performance of your program,  and wasting coding time. If you have some data that needs to be searched through, a good use of your time would be deciding on a data structure to store your data, and an algorithm to search through it. A bad use of your time would be to go through all of your loops and change i++ to ++i. For those of you who are not aware of the difference, ++i is slightly faster than i++. The difference, however, is so tiny that you should never spend any amount of time changing one to the other. The same thing goes for print and echo. In PHP echo is slightly faster than print, but in a real world application it would be difficult to measure the difference.

I like to call these practices trivial over optimizations. There is a non-trivial kind of over optimization that I think is an even bigger time waster. Earlier I mentioned that a good use of your time would be deciding which data structure to use to store data that you plan to search through. This being the case you might want to spend some time comparing the performance differences between a binary search tree and a priority queue, correct? Maybe. If this program is being written to control someone’s pacemaker then the answer is certainly yes. If you plan to sort someone’s play list with this program then the answer is probably no.

There is a third kind of optimization that is not an optimization at all: If you are searching through ten items, a linear search is faster than a binary search. This is because of the over-head in constructing the binary search tree. Optimization is a practice that should belong to programs that are dealing with a large amount of data, or are time-critical. If you are concerned with the performance of your program the solution is not to optimize the code you have, the solution is to learn to write code in such a way that it doesn’t need to be optimized. This is something that comes with experience and attention to detail.