A 500 foot high Egyptian pyramid took hundreds of thousands of workers several decades to construct. They piled up material brick on brick then finished the outside with a smooth layer of limestone. By contrast, the 1000 foot high Empire State Building was constructed from scratch in less than 11 months by less than 3000 workers. Quite a bit of today's software and its construction process resemble the Egyptian pyramid, but I would dare say that no one currently knows how to organize 3000 programmers to make a major piece of software from scratch in less than 11 months.
I interpret this to mean that "Software Engineering" is still an oxymoron (like airline food, university parking, and even "computer science"). Still, what we do today is rather like the design and construction of buildings before architecture Ñ literally the "tech-ing" of "arches" Ñ in that we can occasionally make something that functions, even if it does resemble a jumble of materials. This is a kind of ancient engineering, an ad hoc cookbook of recipes that have somewhat worked in the past.
Today, science (a concern with what is real) is mixed with mathematics (a concern with what is true) is mixed with engineering (a concern with how something can be made). Each worker in each of these fields also partly works in the other two. Each field has a different temperament associated with it: mathematicians tend to be idealists, scientists realists, and engineers pragmatists. And each finds themselves temporarily adopting a borrowed temperament when they use the other areas to aid advances in the one they most love.
Now what is computing? It seems to be a kind of mathematics -- in that the machine is a kind of inference engine that works out the consequences of relationships -- coupled with a kind of engineering -- in that rather large language representations usually have to be constructed in order to express anything really interesting.
But where is science? In our normal use of the term, we think of being presented with a universe that is not necessarily connected with any of our hopes or beliefs, and science is a special way of getting at how this universe seems to work. In modern times, we especially like to express the way we think the universe works in terms of mathematical models that seem to have enough correspondences with reality to allow both discussion and prediction. We tend to think of science as being analytic.
By contrast, computering seems to be much more synthetic in that we start with rules and compute a kind of "reality". Could there ever be a "computer science"?
I think the answer is yes, and it lies in an analogy to physical world construction. Historically it has not been possible to compute from first principles involving fundamental particles whether a large building or bridge would collapse or stay up. The approach has been to make large structures as well as possible and to study them as though they were part of the universe given to us to understand. This has led to a new kind of scientific engineering which is not an oxymoron, and to a vastly improved set of techniques for building large reliable structures.
I think this is what needs to be done to finally create software engineering. We need to do more building of important software structures, and we need to do it in a form that allows analysis, learning, and reformulating the design and fabrication from what has just been learned.
There seems to be a bit of a chicken and egg problem here. If we don't really have an engineering discipline, then won't it be too difficult to make big constructions that are also understandable enough to learn from? And won't the mess we've made be too difficult to reformulate to give us a chance to understand whether our new findings really have value?
I believe that the secret weapon that can be used to make progress here is extreme late binding. Of what? Of as many things in our development system as possible.
One can make a good argument that most of the advances in both hardware and software design have been facilitated by introducing new latebinding mechanisms. Going way back in hardware, we can think of index and relocation registers, memory management units, etc. In software, we went from absolute instruction locations and formats, to symbolic assemblers, to subroutines, to relocatable code, to hardware independent data structure formats, to garbage collection, to the many late binding advantages of objects, including classes and instances, message sending, encapsulation, polymorphism, and metaprogramming.
In Squeak, you have in your hands one of the most late bound, yet practical, programming systems ever created. It is also an artifact which is wide, broad, and deep enough to permit real scientific study, creation of new theories, new mathematics, and new engineering constructions. In fact, Squeak is primed to be the engine of its own replacement. Since every mechanism that Squeak uses in its own construction is in plain view and is changeable by any programmer, it can be understood and played with. "Extreme play" could very easily result in the creation of a system better than Squeak, very different from Squeak, or both.
We not only give permission for you to do this, we urge you to try! Why? Because our field is still a long way from a reasonable state, and we cannot allow bad defacto standards (mostly controlled by vendors) to hold back progress. You are used to learning a programming system as a language with certain features, with the goal of using the features to make things. Squeak is very good at this and has many features (too many actually!) with which to build things. But the best way to approach the learning you are about to do is to consider Squeak as a metalanguage that can build languages. Besides learning how to make things with the existing features, also try to learn how the features themselves were invented and made. All the code is visible, and much of it has explanations of how it works. Here, the system is the curriculum. Even the online version of this book will have a hard time keeping track of an ever changing and improving system, so it is best to learn how to find out from the system itself what it does. Then try to add new deep features of your own. Eventually, you will form a point of view of your own about better ways to program. Squeak will allow you to add these, or even to replace all of its current features with new ones that you have invented. Some of these ideas will be good enough to advance the art and the engineering and the science and the math of programming.
Then you will have used Squeak in all the ways we intended. At some point a much better system than Squeak will be created, and nothing could make us happier -- especially if you can do it while we're still around to enjoy the new ideas!
Posted with permission of Alan Kay and Prentice-Hall, from Squeak: Object-oriented design with multimedia applications, by Mark Guzdial (Prentice-Hall:2001).