TITLE: A Program is an Idea
AUTHOR: Eugene Wallingford
DATE: November 24, 2007 5:43 AM
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Recently I claimed that
scientists should learn to program.
Why? I think that there are reasons beyond the more general
reasons that others should learn.
As more and more science becomes computational, or relies on
computation in some fundamental way, scientists will build
models of their theories using programs. There are, of course,
many modeling tools to support this activity. But a scientist
should understand something about how these tools work in order
to understand better the models built with them. Scientists
may not need to understand their software tools as well as the
computer scientists who build them, but they should probably
understand them better than my grandma knows how her e-mail
tool works.
Actually, scientists may want to know a lot about their tools.
My physicist and chemist friends talk and write often about
how they build their own instruments and mock up equipment
for special-purpose experiments. There is great power in
building the instruments one uses -- something I've written
about as a computer scientist writing his own tools. Then
again, my scientist friends don't blow their own glass or
make their own electrical wire, so there is some point at
which the process of tool-building bottoms out. I'm not sure
we have a very good sense where the process of a scientist
writing her own software will bottom out just yet.
Being able to write code, even if only short scripts, puts a
lot of power into the scientist's hands. It is the
power to express an idea.
And that's what programs are: ideas.
I read that line in an
article by Paul Graham
about how programmers work best. But the crux of his whole
argument comes down to that one line: a program is an idea.
As a scientist creates an idea, explores it, shapes it, and
communicates it, a program can be the evolving idea embodied
-- concrete, unambiguous, portable. That is part of what I
inferred from the presentations of earth scientist Noah
Diffenbaugh and physics educators Ruth Chabay and Bruce
Sherwood at the
SECANT workshop,
Programs are part of how the scientist works and part of how
the scientist communicates the result.
Reader
Darius Bacon
sent me some some neat comments in response to my Programming
Scientists entry on just this point. Darius expressed frustration
with the way that many scientific papers formally explain their
experiments and results. "Why don't you just *write a program*?"
he asks. He agrees that especially scientists should learn how
to program, because it may help them learn to communicate their
ideas better. I look forward to him saying more about this in
his blog.
A scientist can communicate an idea to others with a program,
but they can also think better with a program. Graham
captured this from the perspective of the software developer
in the article I quoted earlier:
Your code is your understanding of the problem you're exploring.
Every programmer knows what this means. I can think all the
Big Thoughts I like, but until I have working a program, I'm
never quite certain that these thoughts make sense. Writing a
program forces me to specify and clarify; it rejects fuzziness
and incoherence. As my program grows and evolves, it reflects
the growth and evolution of my idea. Graham says it more strongly:
the program is the growth and evolution of my idea.
Whether this is truth or merely literary device, thinking of
the program as the idea is a useful mechanism for holding myself
accountable to making my idea clear enough to execute.
This is one of the senses in which Darius Bacon's notion of
program-as-explanation works. A program might be clearer than
the prose, "and even if it isn't at first, at least I could
reverse-engineer it, because it has to be precise enough to
execute" (my emphasis). And what helps us communicate
better can also help us to think better, because the program
in which we embody our thoughts has to be precise enough to
execute.
I know this sounds like a lot of high-falutin' philosophizing.
But I think it is one of the Big Ideas that computing has
given the world. It's one of the reasons that teaching
everyone a little programming would be good.
There are practical reasons for learning to program, too,
and I think we can be more practical and concrete in saying
why programming is especially important to scientists. In
science, the 20th century was the century of the mathematical
formula. The ideas we explored, and the level at which we
understand them, were in most ways expressible with small
systems of equations. But as we tackle more complex problems
and try to understand more complex systems, individual formulae
become increasingly unsatisfactory as models. The 21st century
will be the century of the algorithm! And the best way to
express and test an algorithm is... write a program.
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