Question

In the happy land of elegant code and pretty rainbows, there lives a spoil-sport monster called inefficiency.

A program that processes an array is most elegantly expressed as a sequence of cleanly separated steps that each do something with the array and produce a new array. But building up all those intermediate arrays is somewhat expensive.

Likewise, passing a function to forEach and letting that method handle the array iteration for us is convenient and easy to read. But function calls in JavaScript are costly compared to simple loop bodies.

And so it goes with a lot of techniques that help improve the clarity of a program. Abstractions add layers between the raw things the computer is doing and the concepts we are working with and thus cause the machine to perform more work. This is not an iron law—there are programming languages that have better support for building abstractions without adding inefficiencies, and even in JavaScript, an experienced programmer can find ways to write abstract code that is still fast. But it is a problem that comes up a lot.

Fortunately, most computers are insanely fast. If you are processing a modest set of data or doing something that has to happen only on a human time scale (say, every time the user clicks a button), then it does not matter whether you wrote a pretty solution that takes half a millisecond or a super-optimized solution that takes a tenth of a millisecond.

It is helpful to roughly keep track of how often a piece of your program is going to run. If you have a loop inside a loop (either directly or through the outer loop calling a function that ends up performing the inner loop), the code inside the inner loop will end up running N×M times, where N is the number of times the outer loop repeats and M is the number of times the inner loop repeats within each iteration of the outer loop. If that inner loop contains another loop that makes P rounds, its body will run M×N×P times, and so on. This can add up to large numbers, and when a program is slow, the problem can often be traced to only a small part of the code, which sits inside an inner loop.

This is a book about getting computers to do what you want them to do. Computers are about as common as screwdrivers today, but they contain a lot more hidden complexity and thus are harder to operate and understand. To many, they remain alien, slightly threatening things.