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Computer science

Relationship with other fields

Despite its name, a significant amount of computer science does not involve the study of computers themselves. Because of this, several alternative names have been proposed. Certain departments of major universities prefer the term ''computing science'', to emphasize precisely that difference. Danish scientist Peter Naur suggested the term ''datalogy'', to reflect the fact that the scientific discipline revolves around data and data treatment, while not necessarily involving computers. The first scientific institution to use the term was the Department of Datalogy at the University of Copenhagen, founded in 1969, with Peter Naur being the first professor in datalogy. The term is used mainly in the Scandinavian countries. Also, in the early days of computing, a number of terms for the practitioners of the field of computing were suggested in the ''Communications of the ACM'' – ''turingineer'', ''turologist'', ''flow-charts-man'', ''applied meta-mathematician'', and ''applied epistemologist''.Communications of the ACM 1(4):p.6 Three months later in the same journal, ''comptologist'' was suggested, followed next year by ''hypologist''.Communications of the ACM 2(1):p.4 The term ''computics'' has also been suggested.IEEE Computer 28(12):p.136 In continental Europe, names such as ''informatique'' (French), ''Informatik'' (German) or ''informatica'' (Dutch), derived from information and possibly mathematics or automatic, are more common than names derived from computer/computation. The renowned computer scientist Edsger W. Dijkstra|Edsger Dijkstra stated, "Computer science is no more about computers than astronomy is about telescopes." The design and deployment of computers and computer systems is generally considered the province of disciplines other than computer science. For example, the study of computer hardware is usually considered part of computer engineering, while the study of commercial computer systems and their deployment is often called information technology or information systems. However, there has been much cross-fertilization of ideas between the various computer-related disciplines. Computer science research has also often crossed into other disciplines, such as philosophy, cognitive science, linguistics, mathematics, physics, computational statistics|statistics, and computational economics|economics. Computer science is considered by some to have a much closer relationship with mathematics than many scientific disciplines, with some observers saying that computing is a mathematical science. Early computer science was strongly influenced by the work of mathematicians such as Kurt Gödel and Alan Turing, and there continues to be a useful interchange of ideas between the two fields in areas such as mathematical logic, category theory, domain theory, and algebra. The relationship between computer science and software engineering is a contentious issue, which is further muddied by Debates within software engineering|disputes over what the term "software engineering" means, and how computer science is defined. David Parnas, taking a cue from the relationship between other engineering and science disciplines, has claimed that the principal focus of computer science is studying the properties of computation in general, while the principal focus of software engineering is the design of specific computations to achieve practical goals, making the two separate but complementary disciplines., p. 19: "Rather than treat software engineering as a subfield of computer science, I treat it as an element of the set, Civil Engineering, Mechanical Engineering, Chemical Engineering, Electrical Engineering, .." The academic, political, and funding aspects of computer science tend to depend on whether a department formed with a mathematical emphasis or with an engineering emphasis. Computer science departments with a mathematics emphasis and with a numerical orientation consider alignment computational science. Both types of departments tend to make efforts to bridge the field educationally if not across all research.

Computer science education

Some universities teach computer science as a theoretical study of computation and algorithmic reasoning. These programs often feature the theory of computation, analysis of algorithms, formal methods, Concurrency (computer science)|concurrency theory, databases, computer graphics and systems analysis, among others. They typically also teach computer programming, but treat it as a vessel for the support of other fields of computer science rather than a central focus of high-level study. Other colleges and universities, as well as secondary schools, teach computer science at A level and degree level, which emphasize the practice of advanced programming rather than the theory of algorithms and computation in their computer science curricula. Such curricula tend to focus on those skills that are important to workers entering the software industry. The practical aspects of computer programming are often referred to as software engineering.

See also

References

Further reading


- Association for Computing Machinery. 1998 ACM Computing Classification System. 1998.
- IEEE Computer Society and the Association for Computing Machinery. Computing Curricula 2001: Computer Science. December 15, 2001.
- Peter J. Denning. ''Is computer science science?'', Communications of the ACM, April 2005.
- Donald E. Knuth. ''Selected Papers on Computer Science,'' CSLI Publications, Cambridge Univ. Press, 1996.
- Peter J. Denning, ''Great principles in computing curricula'', Technical Symposium on Computer Science Education, 2004.

External links


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- Directory of free university lectures in Computer Science
- Collection of computer science lectures
- bibliography/ Collection of Computer Science Bibliographies
- CS Directory and resources
- Photographs of computer scientists (Bertrand Meyer's gallery)

Webcasts


- UCLA Computer Science 1 Freshman Computer Science Seminar Section 1
- Berkeley Introduction to Computers Category:Computer science| zh-min-nan:Tiān-náu kho-ha̍k nds-nl:Infermatika simple:Computer science zh-yue:電算 bat-smg:Infuormatėka

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