Dijkstra Quotes

Simplicity is a great virtue but it requires hard work to achieve it and education to appreciate it. And to make matters worse: complexity sells better.

The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.

Computer Science is no more about computers than astronomy is about telescopes

Simplicity is prerequisite for reliability.

Raise your quality standards as high as you can live with, avoid wasting your time on routine problems, and always try to work as closely as possible at the boundary of your abilities. Do this, because it is the only way of discovering how that boundary should be moved forward.

I mean, if 10 years from now, when you are doing something quick and dirty, you suddenly visualize that I am looking over your shoulders and say to yourself "Dijkstra would not have liked this", well, that would be enough immortality for me.

I don't know how many of you have ever met Dijkstra, but you probably know that arrogance in computer science is measured in nano-Dijkstras.

Program testing can be used to show the presence of bugs, but never to show their absence!

The use of COBOL cripples the mind; its teaching should, therefore, be regarded as a criminal offense.

If debugging is the process of removing software bugs, then programming must be the process of putting them in.

Besides a mathematical inclination, an exceptionally good mastery of one's native tongue is the most vital asset of a competent programmer.

Progress is possible only if we train ourselves to think about programs without thinking of them as pieces of executable code.

It is not only the violin that shapes the violinist, we are all shaped by the tools we train ourselves to use, and in this respect programming languages have a devious influence: they shape our thinking habits.

The purpose of abstracting is not to be vague, but to create a new semantic level in which one can be absolutely precise.

It is practically impossible to teach good programming to students that have had a prior exposure to BASIC: as potential programmers they are mentally mutilated beyond hope of regeneration.

Your obligation is that of active participation. You should not act as knowledge-absorbing sponges, but as whetstones on which we can all sharpen our wits

The computing scientist’s main challenge is not to get confused by the complexities of his own making.

Dijkstra once said, “Testing shows the presence, not the absence, of bugs.” In other words, a program can be proven incorrect by a test, but it cannot be proven correct. All that tests can do, after sufficient testing effort, is allow us to deem a program to be correct enough for our purposes.

Thank goodness we don't have only serious problems, but ridiculous ones as well.

A popular saying at King Vizimir’s court held that if Dijkstra states it is noon yet darkness reigns all around, it is time to start worrying about the fate of the sun.

By claiming that they can contribute to software engineering, the soft scientists make themselves even more ridiculous. (Not less dangerous, alas!) In spite of its name, software engineering requires (cruelly) hard science for its support.

Testing can only prove the presence of bugs, not their absence. –

Computer science is not about machines, in the same way that astronomy is not about telescopes. There is an essential unity of mathematics and computer science.

John von Neumann draws attention to what seemed to him a contrast. He remarked that for simple mechanisms, it is often easier to describe how they work than what they do, while for more complicated mechanisms, it is usually the other way around.

Computer science is no more about computers than astronomy is about telescopes.” —Edsger W. Dijkstra

The problem that Dijkstra recognized, early on, was that programming is hard, and that programmers don’t do it very well.

In his 1972 essay “The Humble Programmer,” Edsger W. Dijkstra said that “Program testing can be a very effective way to show the presence of bugs, but it is hopelessly inadequate for showing their absence.

Programming, when stripped of all its circumstantial irrelevancies, boils down to no more and no less than very effective thinking so as to avoid unmastered complexity, to very vigorous separation of your many different concerns.

Testing may convincingly demonstrate the presence of bugs, but can never demonstrate their absence."- Edsger W. Dijkstra, Computing Pioneer (1930–2002), "Programming as a discipline of mathematical nature," Am. Math. Monthly, 81 (1974), No. 6, pp. 608–12.

Dijkstra realized that these “good” uses of goto corresponded to simple selection and iteration control structures such as if/then/else and do/while. Modules that used only those kinds of control structures could be recursively subdivided into provable units.

Lisp has jokingly been called “the most intelligent way to misuse a computer”. I think that description is a great compliment because it transmits the full flavor of liberation: it has assisted a number of our most gifted fellow humans in thinking previously impossible thoughts.

The question of whether machines can think is about as relevant as the question of whether submarines can swim.

Seibel: There's a Dijkstra quote about how you can't prove by testing that a program is bug-free, you can only prove that you failed to find any bugs with your tests. But it sort of sounds the same way with a proof-you can't prove a program is bug-free with a proof-you can only prove that, as far as you understand your own proof, it hasn't turned up any bugs.

Let me try to explain to you, what to my taste is characteristic for all intelligent thinking. It is, that one is willing to study in depth an aspect of one's subject matter in isolation for the sake of its own consistency, all the time knowing that one is occupying oneself only with one of the aspects. We know that a program must be correct and we can study it from that viewpoint only; we also know that it should be efficient and we can study its efficiency on another day, so to speak. In another mood we may ask ourselves whether, and if so: why, the program is desirable. But nothing is gained—on the contrary!—by tackling these various aspects simultaneously. It is what I sometimes have called "the separation of concerns", which, even if not perfectly possible, is yet the only available technique for effective ordering of one's thoughts, that I know of. This is what I mean by "focusing one's attention upon some aspect": it does not mean ignoring the other aspects, it is just doing justice to the fact that from this aspect's point of view, the other is irrelevant. It is being one- and multiple-track minded simultaneously.

My point today is that, if we wish to count lines of code, we should not regard them as "lines produced" but as "lines spent": the current conventional wisdom is so foolish as to book that count on the wrong side of the ledger.

In a society in which the educational system is used as an instrument for the establishment of a homogenized culture, in which the cream is prevented from rising to the top, the education of competent programmers could be politically impalatable.

I think it wise, and only honest, to warn you that my goal is immodest. It is not my purpose to "transfer knowledge" to you that, subsequently, you can forget again. My purpose is no less than to effectuate in each of you a noticeable, irreversable change. I want you to see and absorb calculational arguments so effective that you will never be able to forget that exposure.

A new philosophy, a way of life, is not given for nothing. It has to be paid dearly for and only acquired with much patience and great effort.”   Fyodor Dostoyevsky

Computer science is no more about computers than astronomy is about telescopes.

Program testing can be a very effective way to show the presence of bugs, but it is hopelessly inadequate for showing their absence.

Program testing can be used to show the presence of bugs, but never to show their absence!

Computing pioneer Edsger Dijkstra pointed out that computing is the only profession in which a single mind is obliged to span the distance from a bit to a few hundred megabytes, a ratio of 1 to 109, or nine orders of magnitude (Dijkstra 1989).

the automatic computer confronts us with a radically new intellectual challenge that has no precedent in our history." Of course software has become even more complex since 1989, and Dijkstra's ratio of 1 to 109could easily be more like 1 to 1015 today.

Dijkstra pointed out that no one's skull is really big enough to contain a modern computer program (Dijkstra 1972), which means that we as software developers shouldn't try to cram whole programs into our skulls at once; we should try to organize our programs in such a way that we can safely focus on one part of it at a time.

W. Dijkstra, a leading theorist of programming, once summarized the prevalent attitudes toward code writing in the formative period of computing. He declared:   What about the poor programmer? Well, to tell the honest truth, he was hardly noticed. For one thing, the first machines were so bulky that you could hardly move them and besides that, they required such extensive maintenance that it was quite natural that the place where people tried to use the machine was the same laboratory where the machine had been developed. Secondly, the programmer’s somewhat invisible work was without any glamour: You could show the machine to visitors and that was several orders of magnitude more spectacular than some sheets of coding. But most important of all, the programmer himself had a very modest view of his own work: his work derived all its significance from the existence of that wonderful machine. Because the machine was unique, he knew his programs had only local significance. And since the machine would live for a short time... he knew that little or none of his code held lasting value.   The

Edsger Dijkstra said: Program testing can be used to show the presence of bugs, but never to show their absence.

In a free market, actors behave selfishly and try in rational ways to succeed and maximize their gains, which leads, as if by an “invisible hand” (Adam Smith 1776), to economic efficiency and benefits society. The traditional idea was, and for some still is, that business best benefited others, served the public good, by being left to its own devices (“laissez faire, laissez passer”).

Barroso and Holzle of Google have made the case for energy proportional (energy elastic) computing based on the observation that servers in data centers today operate at well below peak load levels on average. According to them, energy efficiency characteristics are primarily the responsibility of component and system designers, “They should aim to develop machines that consume energy in proportion to the amount of work performed” (2007).

What is happening in “the last mile” (the access networks) caused by the end user’s behavior will have a big impact on the debate of data center sustainability. Research conducted by Bell Labs and the University of Melbourne (CEET 2013) show that by 2015 wireless cloud (Wi-Fi and cellular technology) will consume between 32 TWh (low scenario) and 43 TWh (high scenario) compared to only 9.2 TWh in 2012. An increase between 248% and 367%. The take-up of wireless devices is shown by the fact that global mobile data traffic overall is currently increasing at 78% per annum and mobile cloud traffic specifically is increasing at 95% per annum. Wireless cloud traffic is about 20% of mobile traffic and approximately 35% of data center traffic. The result of this is that wireless access network technologies account for 90% of total wireless cloud energy consumption. Data centers account for only about 9%. The energy consumption of wireless user devices is negligible.

And this is not the only example. During recent warm, dry summers in 2003, 2006, and 2009, several thermoelectric power plants in Europe were forced to reduce production because of restricted availability of cooling water.

The key questions asked are, “Is it better to try to live within that limit by accepting a self-imposed restriction on growth? Or is it preferable to go on growing until some other natural limit arises, in the hope at that time another technological leap will allow growth to continue still longer.

in September 2019, a parliamentarian named Pia Dijkstra announced that she would push forward an assisted-dying bill designed for elderly people with “completed lives.” When I asked Dijkstra about her motivations, she answered me with typically Dutch blasé: “We think that people have the right to decide, themselves, when their life is complete. They should not have to take actions that are nasty, like putting a plastic bag over your head so you suffocate.

Seibel: What's your desert-island list of books for programmers? Peyton Jones: Well, you should definitely read Jon Bentley's Programming Pearls. Speaking of pearls, Brian Hayes has a lovely chapter in this book Beautiful Code entitled, “Writing Programs for ‘The Book’” where I think by “The Book” he means a program that will have eternal beauty. You've got two points and a third point and you have to find which side of the line between the two points this third point is on. And several solutions don't work very well. But then there's a very simple solution that just does it right. Of course, Don Knuth's series, The Art of Computer Programming. I don't think it was ever anything I read straight through; it's not that kind of book. I certainly referred to it a lot at one stage. Chris Okasaki's book Purely Functional Data Structures. Fantastic. It's like Arthur Norman's course only spread out to a whole book. It's about how you can do queues and lookup tables and heaps without any side effects but with good complexity bounds. Really, really nice book. Everyone should read this. It's also quite short and accessible as well. Structure and Interpretation of Computer Programs. Abelson and Sussman. I loved that. And Compiling with Continuations, Andrew Appel's book about how to compile a functional program using continuation passing style. Also wonderful. Books that were important to me but I haven't read for a long time: A Discipline of Programming by Dijkstra. Dijkstra is very careful about writing beautiful programs. These ones are completely imperative but they have the “Hoare property” of rather than having no obvious bugs they obviously have no bugs. And it gives very nice, elegant reasoning to reason about it. That's a book that introduced me for the first time to reasoning about programs in a pretty watertight way. Another book that at the time made a huge impression on me was Per Brinch Hansen's book about writing concurrent operating systems. I read it lots of times.

Another important set of new ideas for designing the bugs out of programs derives largely from Dijkstra,[3] and is built on a theoretical structure by B öhm and Jacopini.[4] Basically the approach is to design programs whose control structures consist only of loops defined by a statement such as DO WHILE, and conditional portions delineated into groups of statements marked with brackets and conditioned by an IF . . . THEN . . . ELSE. B öhm and Jacopini show these structures to be theoretically sufficient; Dijkstra argues that the alternative, unrestrained branching via GO TO, produces structures that lend themselves to logical errors. The basic notion is surely sound.

Ciência da Computação tem tanto a ver com o computador como a astronomia com o telescópio, a biologia com o microscópio, ou a química com os tubos de ensaio. A ciência não estuda ferramentas, mas o que fazemos e o que descobrimos com elas.

Dijkstra almost laughs: The droid sounds offended—or eager to be offended. So he just says, “Well, I guess we’re all rivals in the end, aren’t we? Competition makes the world go ’round.

Dijkstra tries to raise his hands, but the wrench comes crashing down on his head. Crack. Crack. The droid is relentless. Crack. Dijkstra sees his own blood in his eyes. Crack. He falls to the floor. Crack. Crack. The droid is smashing his head in. Crack. Crack.