A programming language is a tool for handling design complexity. That’s what all of computer science is, really — languages, libraries, type systems, garbage collectors, everything you learn about programming. They’re ways to build more and more complex designs without losing your grip.
The way you manage complexity is to be able to ignore it. A good programming tool lets you forget about some part of the problem, so that you can focus on some other part. And it ensures that when you return to the parts you forgot, you haven’t accidentally broken them.
Years ago, When I was taking to programmers about what college I wanted to attend, I had in interesting conversation about how Computer Science education is an utter failure at preparing students for real-world programming. Outside of Software Development, no technical field accepts (sometimes prefers) candidates with “N years of experience” in place of a degree. I’m not sure I know why CS education fails so badly and universally. But my current best guess is that it’s because school never exposes you to enough complexity. Projects have to end in a semester. You never have to deal with a multimillion-line program, written by hundreds of co-workers, dozens of which you need to collaborate with, at unexpected times, for surprising reasons.
. The graphics topics are dated, and there is no discussion about newfangled topics in computing, like the internet. But the meat of the book are timeless computer science fundamentals. It still has the best explanation of what “NP-Complete” means (page 276) that I’ve run across.
. It’s an excellent and fun introduction to the essential theory behind computer science.