Edsger W. Dijkstra Quotes

A confusion of even longer standing came from the fact that the unprepared included the electronic engineers that were supposed to design, build and maintain the machines. The job was actually beyond the electronic technology of the day, and, as a result, the question of how to get and keep the physical equipment more or less in working condition became in the early days the all-overriding concern. As a result, the topic became – primarily in the USA – prematurely known as 'computer science' – which, actually, is like referring to surgery as 'knife science' – and it was firmly implanted in people's minds that computing science is about machines and their peripheral equipment. Quod non [Latin: "Which is not true"]. We now know that electronic technology has no more to contribute to computing than the physical equipment. We now know that programmable computer is no more and no less than an extremely handy device for realizing any conceivable mechanism without changing a single wire, and that the core challenge for computing science is hence a conceptual one, viz., what (abstract) mechanisms we can conceive without getting lost in the complexities of our own making.

Probably I am very naive, but I also think I prefer to remain so, at least for the time being and perhaps for the rest of my life.

The question of whether Machines Can Think... is about as relevant as the question of whether Submarines Can Swim.

I think of the company advertising "Thought Processors" or the college pretending that learning BASIC suffices or at least helps, whereas the teaching of BASIC should be rated as a criminal offence: it mutilates the mind beyond recovery.

How do we convince people that in programming simplicity and clarity —in short: what mathematicians call "elegance"— are not a dispensable luxury, but a crucial matter that decides between success and failure?

[Though computer science is a fairly new discipline, it is predominantly based on the Cartesian world view. As Edsgar W. Dijkstra has pointed out] A scientific discipline emerges with the - usually rather slow! - discovery of which aspects can be meaningfully 'studied in isolation for the sake of their own consistency.

About the use of language: it is impossible to sharpen a pencil with a blunt axe. It is equally vain to try to do it with ten blunt axes instead.

We can found no scientific discipline, nor a hearty profession, on the technical mistakes of the Department of Defense and, mainly, one computer manufacturer.

Programming is one of the most difficult branches of applied mathematics; the poorer mathematicians had better remain pure mathematicians.

In the good old days physicists repeated each other's experiments, just to be sure. Today they stick to FORTRAN, so that they can share each other's programs, bugs included.

FORTRAN, 'the infantile disorder', by now nearly 20 years old, is hopelessly inadequate for whatever computer application you have in mind today: it is now too clumsy, too risky, and too expensive to use.

APL is a mistake, carried through to perfection. It is the language of the future for the programming techniques of the past: it creates a new generation of coding bums.

The effective exploitation of his powers of abstraction must be regarded as one of the most vital activities of a competent programmer.

If you want more effective programmers, you will discover that they should not waste their time debugging, they should not introduce the bugs to start with.

Using PL/1 must be like flying a plane with 7000 buttons, switches and handles to manipulate in the cockpit.