„It was the height of the first boom, so it was 1999. It was a good year to be a graduate in computer science.“

—  Marissa Mayer, fortune.com http://fortune.com/2013/10/17/transcript-marissa-mayer-at-fortune-mpw/.
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Friedrich Bauer photo

„Software engineering is the part of computer science which is too difficult for the computer scientist.“

—  Friedrich Bauer German computer scientist 1924 - 2015
Bauer (1971) "Software Engineering." Information Processing: Proceedings of the IFIP Congress 1971, Ljubljana, Yugoslavia, August 23-28, 1971.

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Donald Ervin Knuth photo

„I can’t be as confident about computer science as I can about biology. Biology easily has 500 years of exciting problems to work on. It’s at that level.“

—  Donald Ervin Knuth American computer scientist 1938
Computer Literacy Bookshops Interview http://karthikr.wordpress.com/2006/04/06/donald-knuth-%e2%80%94-computer-literacy-bookshops-interview-1993/ Computer Literacy Bookshops Interview (1993) On why bioinformatics is very exciting

Hal Abelson photo

„Anything which uses science as part of its name isn't: political science, creation science, computer science.“

—  Hal Abelson computer scientist 1947
Source: The Nature of Belief http://www.xent.com/FoRK-archive/sept97/0213.html

Edsger W. Dijkstra photo

„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“

—  Edsger W. Dijkstra Dutch computer scientist 1930 - 2002
Context: 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. Dijkstra (1986) On a cultural gap http://www.cs.utexas.edu/users/EWD/transcriptions/EWD09xx/EWD924.html (EWD 924).

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„Understanding is, after all, what science is all about — and science is a great deal more than mindless computation.“

—  Roger Penrose English mathematical physicist, recreational mathematician and philosopher 1931
As quoted in The Golden Ratio : The Story of Phi, the World's Most Astonishing Number (2002) by Mario Livio, p. 201.

Donald Ervin Knuth photo

„Trees sprout up just about everywhere in computer science…“

—  Donald Ervin Knuth American computer scientist 1938
Vol. IV - A, Combinatorial Algorithms, Section 4.2.1.6 (2011)

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Herbert A. Simon photo

„Now the salient characteristic of the decision tools employed in management science is that they have to be capable of actually making or recommending decisions, taking as their inputs the kinds of empirical data that are available in the real world, and performing only such computations as can reasonably be performed by existing desk calculators or, a little later electronic computers. For these domains, idealized models of optimizing entrepreneurs, equipped with complete certainty about the world - or, a worst, having full probability distributions for uncertain events - are of little use. Models have to be fashioned with an eye to practical computability, no matter how severe the approximations and simplifications that are thereby imposed on them…
The first is to retain optimization, but to simplify sufficiently so that the optimum (in the simplified world!) is computable. The second is to construct satisficing models that provide good enough decisions with reasonable costs of computation. By giving up optimization, a richer set of properties of the real world can be retained in the models… Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science.“

—  Herbert A. Simon American political scientist, economist, sociologist, and psychologist 1916 - 2001
p. 498; As cited in: Arjang A. Assad, ‎Saul I. Gass (2011) Profiles in Operations Research: Pioneers and Innovators. p. 260-1.

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„Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Etiam egestas wisi a erat. Morbi imperdiet, mauris ac auctor dictum.“