Theory of computation

Theory of computation

The study of the theory of computation is focused on answering fundamental questions about what can be computed, and what amount of resources are required to perform those computations. In an effort to answer the first question, computability theory examines which computational problems are solvable on various theoretical models of computation. The second question is addressed by computational complexity theory, which studies the time and space costs associated with different approaches to solving a computational problem.

The famous "P=NP?" problem, one of the Millennium Prize Problems,[18] is an open problem in the theory of computation.

P = NP ?
Computability theory Computational complexity theory

[edit] Theoretical computer science

The broader field of theoretical computer science encompasses both the classical theory of computation and a wide range of other topics that focus on the more abstract, logical, and mathematical aspects of computing.

P \rightarrow Q \, \Gamma\vdash x : Int
Mathematical logic Automata theory Number theory Graph theory Type theory Category theory Computational geometry Quantum computing theory

[edit] Algorithms and data structures

O(n2)
Analysis of algorithms Algorithms Data structures

[edit] Programming methodology and languages


Compilers Programming languages

[edit] Computer elements and architecture


Digital logic Microarchitecture Multiprocessing

[edit] Numerical and symbolic computation

y = sin(x) + c
Bioinformatics Cognitive Science Computational chemistry Computational neuroscience Computational physics Numerical algorithms Symbolic mathematics

[edit] 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.[19] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.[20] The term computics has also been suggested.[21] Informatik was a term used in Europe with more frequency.

The renowned computer scientist 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 cognitive science, economics, mathematics, physics (see quantum computing), and linguistics.

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.[4] 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 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.[22]

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.

[edit] 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 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 and vocational programs that teach computer science, 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. However, there is a lot of disagreement over the meaning of the term, and whether or not it is the same thing as programming.

[edit] See also
Computer science portal
Computer networking portal
Information technology portal

* Career domains in computer science
* Computer scientist
* Computing
* English in computer science
* Informatics
* List of academic computer science departments
* List of computer science conferences
* List of computer scientists
* List of publications in computer science
* List of pioneers in computer science
* List of software engineering topics
* Software engineering
* List of open problems in computer science
* Women in computing

[edit] References

1. ^ "Computer science is the study of information" Department of Computer and Information Science, Gutenberg Information Technologies
2. ^ "Computer science is the study of computation." Computer Science Department, College of Saint Benedict, Saint John's University
3. ^ "Computer Science is the study of all aspects of computer systems, from the theoretical foundations to the very practical aspects of managing large software projects." Massey University
4. ^ a b c Denning, P.J. (2000). "Computer Science: The Discipline" (PDF). Encyclopedia of Computer Science. http://web.archive.org/web/20060525195404/http://www.idi.ntnu.no/emner/dif8916/denning.pdf.
5. ^ "Common myths and preconceptions about Cambridge Computer Science"Computer Science Department, University of Cambridge
6. ^ Nigel Tout (2006). "Calculator Timeline". Vintage Calculator Web Museum. http://www.vintagecalculators.com/html/calculator_time-line.html.
7. ^ "Science Museum - Introduction to Babbage". http://www.sciencemuseum.org.uk/on-line/babbage/index.asp. Retrieved on 2006-09-24.
8. ^ "A Selection and Adaptation From Ada's Notes found in "Ada, The Enchantress of Numbers," by Betty Alexandra Toole Ed.D. Strawberry Press, Mill Valley, CA". http://www.scottlan.edu/Lriddle/women/ada-love.htm. Retrieved on 2006-05-04.
9. ^ "IBM Punch Cards in the U.S. Army". http://www.pattonhq.com/ibm.html. Retrieved on 2006-09-24.
10. ^ a b Levy, Steven (1984). Hackers: Heroes of the Computer Revolution. Doubleday. ISBN 0-385-19195-2.
11. ^ a b David Kahn, The Codebreakers, 1967, ISBN 0-684-83130-9.
12. ^ a b http://www.cis.cornell.edu/Dean/Presentations/Slides/bgu.pdf
13. ^ Constable, R.L. (March 2000) (PDF). Computer Science: Achievements and Challenges circa 2000. http://www.cs.cornell.edu/cis-dean/bgu.pdf.
14. ^ Abelson, H.; G.J. Sussman with J.Sussman (1996). Structure and Interpretation of Computer Programs (2nd Ed. ed.). MIT Press. ISBN 0-262-01153-0. "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."
15. ^ Black box traders are on the march The Telegraph, August 26, 2006
16. ^ a b Computing Sciences Accreditation Board (28 May 1997). "Computer Science as a Profession". http://www.csab.org/comp_sci_profession.html. Retrieved on 2008-09-01.
17. ^ Committee on the Fundamentals of Computer Science: Challenges and Opportunities, National Research Council (2004). Computer Science: Reflections on the Field, Reflections from the Field. National Academies Press. ISBN 978-0-309-09301-9. http://www.nap.edu/catalog.php?record_id=11106#toc.
18. ^ Clay Mathematics Institute P=NP
19. ^ Communications of the ACM 1(4):p.6
20. ^ Communications of the ACM 2(1):p.4
21. ^ IEEE Computer 28(12):p.136
22. ^ Parnas, David L. (1998). "Software Engineering Programmes are not Computer Science Programmes". Annals of Software Engineering 6: 19–37. doi:10.1023/A:1018949113292. , 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, ....}."

[edit] 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.

[edit] External links
Sister project Wikibooks has more on the topic of
Computer science
Sister project Wikiversity has learning materials about Portal:Computer Science

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

[edit] Webcasts

* UCLA Computer Science 1 Freshman Computer Science Seminar Section 1
* Berkeley Introduction to Computers

[hide]
v • d • e
Major fields of computer science
Theory of computation
Automata · Computability · Computational complexity · Quantum Computing
Algorithms and data structures
Analysis of algorithms · Algorithm design · Computational geometry
Programming languages
Theory · Compilers · Parsers · Interpreters · Programming paradigms (Declarative · Imperative · Logic · Procedural)
Types of Computation
Cloud computing · Cluster Computing · Distributed computing · Grid computing · Parallel computing
Software engineering
Requirements analysis · Software design · Computer programming · Formal methods · Software testing · Software development process · Design pattern · Software framework
System architecture
Computer architecture · Computer organization · Operating systems · Management information system
Telecomm & Networking
Computer audio · Routing · Network topology · OSI model · Cryptography · World Wide Web · Semantic Web · Internetworking
Databases
Database theory · Data mining · Data modeling · OLAP · Geographic information system
Computer graphics
Visualization · Image processing
Scientific computing
Artificial life · Bioinformatics · Cognitive Science · Computational chemistry · Computational neuroscience · Computational physics · Numerical algorithms · Symbolic mathematics
Artificial intelligence
Automated reasoning · Computational linguistics · Computer vision · Evolutionary computation · Machine learning · Natural language processing · Robotics · Cybernetics
HCI / MMI
Computer accessibility · User interfaces · Wearable computing · Ubiquitous computing · Virtual reality
NOTE: Computer science can also be split up into different topics or fields according to the ACM Computing Classification System.