The Sad Reality of Post-Mature Optimization
I find that these debates often come down to an either-or proposition: "put off optimization indefinitely" or "optimize to the max the whole way through." But it should never be so black and white. From a business view, both approaches are wrong, as they tend to entail unnecessary costs.The OP is right that if you completely ignore performance as you code, you'll be doing things so blatantly wrong everywhere that it's difficult or impossible to fix. But, Knuth is right too: It's counterproductive to spend 10 times as long developing version 0.1 just to make sure it's the fastest 0.1 there could possibly be. This is because your early code is likely to change a great deal over the course of the project. You'll refactor, you'll add and remove features, and you'll realize you were wrong about where the bottlenecks are. Much of your early optimization effort will have been wasted.After much programming experience, including trying both extremes, I've learned that a middle road is the most cost-effecive. The real quote from Knuth, so says Wikipedia, is: "We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil." He's not saying to ignore performance. He's not arguing that you should blindly accept obviously unperformant architectures, such as the OP's example of iterating over a huge array when a hash would clearly be better. He's saying you shouldn't obsess over the "small efficiencies," the time-consuming rewrites of every little, rarely-called function to shave off 5% of execution time. At least not early in a project. I think Knuth would support doing that for a highly mature product, at least in some cases. Indeed, much of Knuth's most well-known work is entirely focused on performance. He's just telling people not to be overzealous.So how does all this translate into everyday practice? I think a lot of it has to do with instincts and experience, which let you estimate the labor costs and performance benefits of individual optimizations. For example, as a web programmer, this ethos leads to decisions like this:- I WILL prevent a given method from loading the same database records twice, even if loading them twice is the easy way.
- I WON'T rewrite the SQL that my ORM generates in most cases.
- I WON'T worry about the performance difference between calling an object's instance variable accessor vs reading the instance variable directly.