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James Gosling on Java, May 2001
A Conversation with Java's Creator, James Gosling
by Bill Venners
First Published in JavaWorld, June 2001

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Programmer Productivity versus Program Performance

Bill Venners: Okay. New subject. We've talked about complexity and performance and change. Another thing that matters, to some extent, is the productivity of the programmer. I was wondering to what extent programmer productivity was a concern or goal, how it entered your thinking, as you were designing Java. And to what extent did you made tradeoffs in programmer productivity versus program performance?

James Gosling: It's funny how some of these things like performance and reliability actually fit hand in hand with developer productivity. There's a folk theorem out there that systems with very loose typing are very easy to build prototypes with. That may be true. But the leap from a prototype built that way to a real industrial strength system is pretty vast.

By and large, I wasn't really concerned about how quickly you could slap together a demo. I was much more concerned about how quickly you could build a real system. And boy, strong typing is a great thing there. Anything that tells you about a mistake earlier not only makes things more reliable because you find the bugs, but the time you don't spend hunting bugs is time you can spend doing something else. I don't know what fraction of my life I blew away hunting down obscure memory corruption bugs in random bags of C code, but it's a lot. You can get a huge amount of developer productivity just out of making things less error prone.

Bill Venners: That's interesting, because the next thing I was going to ask about was weak typing and Python. Have you ever done anything with Python?

James Gosling: A little bit. Things like Python can be pretty nice. One of the issues with weak typing systems is they tend to be very hard to get them up to really high performance. In a lot of systems, for example, when integers overflow, they turn into doubles or big ints, or whatever. That means that adding a number together is not just an add instruction. It's: "Gee, are these guys both integers? Okay. Then I guess I can do an add. Let's get the integers. Oh, but this guy's a bigger number than that."

So an add isn't one instruction any more. I cared pretty deeply that a = b + c should almost always be compiled into one instruction on just about any architecture. And you look at any of the JITs today and they pretty much do that. a, b, and c get optimized in the registers. And that's what it is most of these days. So you pay an awful lot for weak typing.

Bill Venners: In performance?

James Gosling: In performance. There are certain forms of weak typing which can actually be pretty useful. If you have something where you are worried about numeric range overflow, or you have something that is mostly a small integer but occasionally turns into a 500 bit number, it's kind of nice to have it roll over. Statistically speaking, those are pretty hard to find. Most people are unwilling to give up their performance for that flexibility, at least in the production systems.

In a lot of systems, however, it just doesn't matter if you spend 10-20 times as long doing an integer wrap. And also, a lot depends on how much you can vary in the libraries. So, for instance, PERL is in some sense is a horrific language in terms of performance, because everything is based around strings. But if the stuff you're doing really is string processing, the weak-typing polymorphic dispatch of everything doesn't matter because all the computation you're doing is done in the string matching algorithms, and they have optimized the hell out of that.

And so, you can end up with systems that perform just fine, so long as the real work is being done in libraries and what you're doing in the language is stitching things together. But it does mean that the language then becomes something that you can't actually use for everything. You can't use it for writing a string matching algorithm in something like PERL. Without the built-in string matching algorithms, it would be pretty slow. Whereas in Java, the string matching libraries are all written in Java. In the world of mathematics, it's a property generally known as completeness. How much of a system can you describe in itself, without having to go outside the system? That actually works pretty well in Java. You can write all kinds of funky low level stuff and the performance is good enough.

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