Programming

I want to be clear about my purpose here. My point is not to claim that the uniqueness of programming is itself unique. Every interesting field is unique in its own special way. For each field, it is helpful to understand why it is unique if you wish to truly excel, or you may bring inappropriate concepts from other domains in, or export inappropriate programming concepts to other domains. I say that programming has several unique aspects and that these aspects are worth thinking about, but this does not mean that programming is privileged somehow.

The most common complaint about software is that it is "too buggy". The question is, "What does too buggy mean?" People making this complaint are often holding software to absurdly high standards, even when making comparisions to other engineering disciplines. In fact, bridges do fall down. Architects fail; often the designs can be seen to fail and corrected or maintained before catastrophic collapse, but it happens. Software is no more likely to be absolutely perfect than any other human endeavor.

Software is an engineering concern, and one of the things that means is that you can't have anything for free. If faced with the choice between a $100 piece of buggy or incomplete software, and a $50,000 piece of production-quality bullet-proof highly-tested quality software, it's unfair to complain that the $100 piece of software is buggy and incomplete.

Some guy took a crack at answering that question. Or more accurately, he claimed to take a crack at it; he never actually got around to answering it. It occurred to me the questioner does have a point, though.

What is computer science, anyhow?

In my continuing series on why software is special, motivating writing a book about it, this post discusses how software is chaotic.

Here I refer to the mathematical definition of chaos, which I will define as: "A chaotic system is one in which small changes in the initial conditions can cause large and unpredictable changes in the system's iterated state." This is based on the mathematical definition(s), but simplified for our purposes. It's not just a word, it's a quasi-formal concept.

In 2007, with a well-loaded Linux desktop installation, my /usr/bin is 257 megabytes, with debugging off and dynamically-linked libraries not contributing to that count. My particular copy of the Linux kernel 2.6.19 with certain Gentoo patches has 202,381,268 bytes of C code alone. If I'm computing this correctly, at a constant 100 words per minute (5 chars/word), that's 281 24-hour days just to re-type the C code in the kernel.

I've gone on before about how distrustful of metaphors I am, and it seems like every year I'm getting more distrustful of them. Either deal with the thing as it is, or just give up understanding it. Metaphors lead to the beginning of understanding, but no farther.

Programmers aren't immune to the metaphor sickness, and if there's one metaphor you can expect to see trotted out at the earliest available opportunity, it's the "programming as construction" metaphor. This metaphor has been skillfully deconstructed many many times before, but I'm going to deconstruct it from the opposite angle... what if construction was like software engineering?

Engineers of other disciplines often take offense at the claim that software is uniquely difficult. They do have a point. As pointed out by Fred Brooks in hyper-classic The Mythical Man Month, one reason software is hard because software is so uniquely easy. We fundamentally built on top of components that have reliability literally in the 99.999999999% range and beyond; a slow 2GHz CPU that "merely" failed once every trillion operations would still fail on average in eight hours at full load, which would be considered highly unreliable in a server room.

The first step to attaining wisdom is to understand why special "programming wisdom" is needed in the first place. It's easy to get the idea that software is easy to create, because it is partially true. Computers get more powerful every year, and we trade in on that power to make programming easier. Every year results in more and better libraries. Changing software is very easy, and it's relatively easy to test compared to an equivalently-complex real-world object.

This is the first post of my new BlogBook, Programming Wisdom.

This initial post starts off by discussing exactly what I mean by "wisdom" in the context of programming. Non-programmers may still be interested as it is more about wisdom than programming.

On programming.reddit.com, I have referred to a list of Big Haskell Projects I'm keeping. I've been keeping it in my head, because it's been short, but I thought I should go ahead and start actually keeping one.

Haskell as a language intrigues me, but I can't help but notice that there aren't a lot of large projects that use it. My intuition suggests that this could be difficult, because I suspect the type system may become increasingly unwieldy. I once asked about this directly, and the results were less than impressive. I'm asking for examples of large projects because concrete results trump my intuition.

In the interests of honesty and transparency, I'm actually going to keep this list in a public place and try to keep it updated as people suggest things until either A: It satisfies me and I start trying to learn Haskell or B: It becomes too much of a time sink, which would basically mean that there are a lot of large projects. That is, my goal is not to keep a list in perpetuity, but just until the point is made.

Update March 8, 2007: This has been up for three weeks now and attracted some attention from some people who really ought to know. I'm willing to say now that pending further updates, I see no compelling reason to believe that Haskell is practical for larger projects. Furthermore, Haskell arrogance is totally unjustified by evidence. It may someday be proven a compelling choice for Real Programming, but there isn't even any significant evidence of that, let alone enough to justify arrogance.