Joel Spolsky wrote a brief essay giving advice to software developers entering or attending college. I usually find Joel has an odd mix of very right and very wrong ideas. But one section particularly caught my attention as very wrong, and I decided to post about it.
...if you can't explain why while (*s++ = *t++); copies a string, or if that isn't the most natural thing in the world to you, well, you're programming based on superstition, as far as I'm concerned...
Right. Because programming is all about understanding pointer arithmetic.
This statement has nothing to do with CS, nothing to do with software engineering, nothing to do with digital design or assembly. This strikes me purely as "my language is better than your language" elitism.
I firmly believe in his general thesis: a great software developer pays attention to soft and hard skills. Software development is a continuum of skills: at one extreme, it's all about people -- at the other extreme, it's all about computer science.
However, the argument that the best programmers must know C idioms can be reduced to the argument that the best programmers must know (in depth) electrical engineering, digital design, or physics. Because otherwise, it's just superstition that the machine works!
In today's world, knowledge is the essential resource. It's more important to know how to organize your ignorance than to try to learn everything.
Abstract languages like Simula, Lisp, and Smalltalk completely changed the way we look at computer science. It brought the "people" element back into it - the need to think and communicate primarily at the level of the problem, not at the level of the machine -- but retaining the ability to drop down to machine level when necessary. Abelson and Sussman explained this shift in the preface to SICP, which I think is a good way to end this rant (highlights mine):
First, we want to establish the idea that a computer language is not just a way of getting a computer to perform operations but rather that it is a novel formal medium for expressing ideas about methodology. Thus, programs must be written for people to read, and only incidentally for machines to execute.
Second, we believe that the essential material to be addressed by a subject at this level is not the syntax of particular programming-language constructs, nor clever algorithms for computing particular functions efficiently, nor even the mathematical analysis of algorithms and the foundations of computing, but rather the techniques used to control the intellectual complexity of large software systems.
Underlying our approach to this subject is our conviction that ``computer science'' is not a science and that its significance has little to do with computers. The computer revolution is a revolution in the way we think and in the way we express what we think. The essence of this change is the emergence of what might best be called procedural epistemology -- the study of the structure of knowledge from an imperative point of view, as opposed to the more declarative point of view taken by classical mathematical subjects. Mathematics provides a framework for dealing precisely with notions of ``what is.'' Computation provides a framework for dealing precisely with notions of ``how to.''