Question

following the text book, I do measure performance whenever I try optimizing my code. Sometimes, however, the performance gain is rather small and I can’t decisively decide whether I should implement that optimization.

For example, when a fix shortens an average response time of 100ms to 90ms under some conditions, should I implement that fix? What if it shortens 200ms to 190ms? How many condition should I try before I can conclude that it will be beneficial overall?

I guess it’s not possible to give a straight forward answer to this, as it depends on too many things, but is there a good rule of thumb that I should follow? Are there any guideline/best-practices?

EDIT:Thanks for the great answers! I guess the moral of the story is, there is no easy way to tell whether you should, but there ARE guidelines that can aid that process.. Things you should consider, things you shouldn’t do etc. This particular time I ended up implementing the fix, even though it made a few line of code into 20-30 lines of code. Because our app. is very performance critical, and it was a consistent 10% gain in various realistic cases.

Answer 1

I think the rule of thumb (at least for me) is two-fold:

1. “It matters if it matters”–in the business world, this generally means that it matters if the clients care. That is, if the end users will “notice” the difference between 100ms and 90ms (I’m not being facetious here), then it matters.
2. If “it matters,” then you will want to test your code thoroughly against a realistic variety of use cases that are likely to arise or at least may arise. If an optimization speeds up code in 50% of cases, but actually runs slower than what you previously had the other 50% of the time, obviously, it may not be worth implementing.

Regarding point 1 above: by suggesting an end user of your software might “notice” a 10ms difference, I don’t mean to suggest that they will actually visibly see a difference. But if your app runs on a server with millions of connections and every little speed increase takes a substantial load off the server, that might matter to the client running the server. Or if your app performs extremely time-critical work, this is another case where the result of a 10ms speedup might be noticeable, even if the speedup itself isn’t.