TITLE: More on the Nature of Computer Science
AUTHOR: Eugene Wallingford
DATE: September 16, 2008  9:43 PM
DESC: 
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BODY:
Another entry generated from a thread on a mailing list...

A recent thread on the SIGCSE list began as a discussion
of how programming language constructs are abstractions
of the underlying hardware, and what that means for how
students understand the code they write.  For example,
this snippet of Java:

<PRE>
    int x = 1;
    while (x &gt; 0)
        x++;
</PRE>

does not result in an infinite, because Java <TT>int</TT>s
are not integers.

This is one of many examples that remind us how important
it is to study computer organization and architecture, and
more generally to learn that abstractions are never 100%
faithful to the details they hide.  If they were, they
would not be abstractions!  A
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2005-05.html#e2005-05-17T08_31_51.htm">
   few good abstractions</A>
make all the difference in how we work, but -- much like
metaphor -- we have to pay attention to what happens at
their edges.

Eventually, the thread devolved toward a standard old
discussion on this list, "What is Computer Science?"
I conjecture that every mailing list, news group, and
bulletin board has a topic that is its "fixed point",
the topic toward which every conversation ultimately
leads if left to proceed long enough, unfettered by
an external force.  Just about every Usenet newsgroup
in which I participated during the late 1980s and early
1990s had one, and the SIGCSE list does, too.  It is,
"What is Computer Science?"

This question matters deeply to many people, who believe
that graduates of CS programs have a particular role to
play in the world.  Some think that the primary job of
undergraduate CS programs is to produce software engineers.
If CS is really engineering (or at least should be thought
of that way for practical reasons), then the courses we
teach and the curricula we design should have specific
outcomes, teach specific content, and imbue in students
the mindset and methodology of an engineer.  If CS is
some sort of liberal art, then our courses and curricula
will look quite different.

Much of this new thread was unremarkable if only because
it all sounded so familiar to me.  One group of people
argued that CS is engineering, and another argued that
it was more than engineering, perhaps even a science.
I must have been in an ornery mood, because one poster's
assertion provoked me to jump into the fray with a few
remarks.  He claimed that CS was not a science, because
it is not a "natural science", and that it is not a
natural science because the object of its study is not
a natural phenomenon:

<BLOCKQUOTE><EM>
I don't believe that I have ever seen a general purpose,
stored-program computing device that occurs in nature...
unless we want to claim that humans are examples of such
devices.
</EM></BLOCKQUOTE>

This seems like such a misguided view of computer
science, but many people hold it.  I'm not surprised that
non-computer scientists believe this, but I am still
surprised to learn that someone in our discipline does,
too.  Different people have different backgrounds and
experiences, and I guess those differences can lead
people to widely diverging viewpoints.

Computer science does not study the digital computer.
Dijkstra told us so a long time ago, and if we didn't
believe him then, we should now, with the advent of
ideas such as quantum computing and biological
computing.

Computer science is about processes that transform
information.  I see many naturally-occurring processes
in the world.  It appears now that life is the result
of an information process, implement in the form of
DNA.  Chemical processes involve information as well
as matter.  And some physicists now believe that the
universe as we experience it is a
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2008-08.html#e2008-08-28T16_22_45.htm">
   projection of two-dimensional information</A>
embodied in the interaction of matter and energy.

When we speak of these disciplines, we are saying
more than that computer scientists use their tool --
a general-purpose computation machine -- to help
biologists, chemists, and physicists do science in
their areas.  We are talking about a more general
view of processes and information, how they behave
in theory and under resource constraints.  Certainly,
computer scientists use their tools to help practitioners
of other disciplines do their jobs differently.  But
perhaps more important, computer scientists seek to
unify our understanding of processes and information
across the many disciplines in which they occur, in
a way that sheds light on how information processing
works in each discipline.  We are still at the advent
of the cycle feeding back what we learn from computing
into the other disciplines, but many believe that this
is where the greatest value of computer science
ultimately lies.  This means that computer science is
wonderful not only because we help others by giving
them tools but also because we are studying something
important in its own right.

If we broaden our definition of "naturally occurring"
to include social phenomena in large. complex systems
that were not designed by anyone in particular, then
the social sciences give rise to a whole new class
of information processes.  Economic markets, political
systems, and influence networks all manifest processes
that manipulate and communicate information.  How do
these processes work?  Are they bound by the same laws
as physical information processing?  These are insanely
interesting questions, whose answers will help us to
understand the world we live in so much better than we
do now.  Again, study of these processes from the
perspective of computer science is only just beginning,
but we have to start somewhere.  Fortunately, some
scientists are
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2008-05.html#e2008-05-03T22_10_00.htm">
   taking the first steps</A>.

I believe everything I've said here today, but that doesn't
mean that I believe that CS is <EM>only</EM> science.  Much
of what we do in CS is engineering: of hardware systems, of
software systems, of larger systems in which the manipulation
of information is but one component.  Much of what we do is
mathematics: finding patterns, constructing abstractions,
and following the implications of our constructions within
a formal system.  That doesn't mean computer science is
not also science.  Some people think we use the scientific
method only as a tool to study engineered artifacts, but
I think that they are missing the big picture of what CS
is.

The fact that people within our discipline still grapple
with this sense of uncertainty about its fundamental nature
does not disconcert me.  We are a young discipline and
unlike any of the disciplines that came before (which are
themselves human constructs in trying to classify knowledge
of the world).  We do not need to hide from this unique
character, but should embrace it.  As Peter Denning has
written over the years  Is computer science science?
Engineering?  Mathematics?  The answer need not be one
of the above.  From different perspectives, it can be
all three.

Of course, we are left with the question of what it is
like for a discipline to comprise all three.  Denning's
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2008-05.html#e2008-05-19T15_55_33.htm">
   Rebooting Computing summit</A>
will bring together people who have been thinking about
this conundrum in an effort to make progress, or chart
a course.  On the CS education front, we need to think
deeply about the implications of CS's split personality
for the design of our curricula.  Owen Astrachan is
working on
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2008-03.html#e2008-03-17T16_18_16.htm">
   innovating the image</A>
of CS in the university by turning our view outward again
to the role of computer science in understanding a world
bigger than the insides of our computers or compilers.
Both of these projects are funded by the NSF, which seems
to appreciate the possibilities.

I can't think about the relationship between computer
science and natural science with thinking of Herb Simon's
seminal <EM> Sciences of the Artificial</EM>.  I don't
know whether reading it would change enough minds, but
it affected deeply how I think about complex systems,
intentionality, and science.
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