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| '''Computer science''', or '''computing science''', is the study of the theoretical foundations of [[information]] and [[computation]] and their implementation and application in [[computer system]]s.<ref>"''Computer science is the study of information''" [http://www.njit.edu/v2/archivecatalog/undergraduate/91/19-und.html Department of Computer and Information Science], Guttenberg Information Technologies</ref><ref>"''Computer science is the study of computation.''" [http://www.csbsju.edu/computerscience/curriculum Computer Science Department, College of Saint Benedict], Saint John's University</ref><ref>"''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.''" [http://study.massey.ac.nz/major.asp?major_code=2010&prog_code=93068 Massey University]</ref> Computer science has many [[diversity of computer science|sub-fields]]; some emphasize the computation of specific results (such as [[computer graphics]]), while others (such as [[computational complexity theory]]) relate to properties of [[computational problem]]s. Still others focus on the challenges in implementing computations. For example, [[programming language theory]] studies approaches to describing computations, while [[computer programming]] applies specific [[programming language]]s to solve specific computational problems.
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| == History ==
| | '''Computer science''' is an academic discipline which studies aspects of [[computer|computers]], computation and [[software]]. |
| {{main | History of computer science}}
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| The history of computer science predates the invention of the modern [[digital computer]]. Machines for calculating fixed numerical tasks have existed since antiquity, such as the [[abacus]]. [[Wilhelm Schickard]] built the first mechanical calculator in 1623.<ref>{{cite web|author=Nigel Tout|title=Calculator Timeline|url=http://www.vintagecalculators.com/html/calculator_time-line.html|work=Vintage Calculator Web Museum|date=2006|accessdate=2006-09-18}}</ref> [[Charles Babbage]] designed a [[difference engine]] in [[Victorian era|Victorian]] times<ref>{{cite web | url=http://www.sciencemuseum.org.uk/on-line/babbage/index.asp | title=Science Museum - Introduction to Babbage | accessdate=2006-09-24}}</ref>, and around 1900 the [[IBM]] corporation sold punch-card machines<ref>{{cite web | url=http://www.pattonhq.com/ibm.html | title=IBM Punch Cards in the U.S. Army | accessdate=2006-09-24}}</ref>. However all of these machines were constrained to perform a single task, or at best, some subset of all possible tasks.
| | There are many areas of specialization within computer science. Some of these areas are: |
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| Prior to the 1920s, the term ''[[Human computer|computer]]'' referred to a human clerk who performed calculations. Early researchers in what came to be called computer science, such as [[Kurt Gödel]], [[Alonzo Church]], and [[Alan Turing]], were interested in the question of computability: what things can be computed by a human clerk who simply follows a list of instructions with paper and pencil, for as long as necessary, and without ingenuity or insight? Part of the motivation for this work was the desire to develop ''computing machines'' that could automate the often tedious and error-prone work of a human computer. Their key insight was to construct universal computing systems capable (in theory) of performing all possible computable tasks, and thus generalising all previous dedicated-task machines into the single notion of the universal computer. The creation of the concept of a universal computer marked the birth of modern computer science.
| | * [[Computing Theory]] |
| | | * [[Algorithm|Algorithms]] |
| During the 1940s, as newer and more powerful computing machines were developed, the term ''computer'' came to refer to the machines rather than their human predecessors. As it became clear that computers could be used for more than just mathematical calculations, the field of computer science broadened to study [[computation]] in general. Computer science began to be established as a distinct academic discipline in the 1960s, with the creation of the first computer science departments and degree programs.<ref name="Denning_cs_discipline">{{cite journal | last=Denning | first=P.J. | authorlink=Peter J. Denning | year=2000 | title=[http://cs.gmu.edu/cne/pjd/PUBS/cs99.pdf Computer science:the discipline] | journal=Encyclopedia of Computer Science}}</ref> Since practical computers became available, many applications of computing have become distinct areas of study in their own right.
| | * [[Machine learning]] |
| | | * [[Artificial intelligence]] |
| == Major achievements ==
| | * [[Distributed computing]] |
| Despite its relatively short history as a formal academic discipline, computer science has made a number of fundamental contributions to science and society. These include:
| | * [[Computer architecture]] |
| | | * [[Software engineering]] |
| * A formal definition of [[computation]] and [[computability]], and proof that there are computationally [[halting problem|unsolvable]] and [[Intractable#Intractability|intractable]] problems<ref>{{cite paper | author=Constable, R.L. | date=March 2000 | url=http://www.cs.cornell.edu/cis-dean/bgu.pdf | title=Computer Science: Achievements and Challenges circa 2000}}</ref>. | | * [[Programming language|Programming languages]] |
| * The concept of a [[programming language]], a tool for the precise expression of methodological information at various levels of abstraction<ref>{{cite book| | | * [[Computer network|Computer networks]][[Category:Suggestion Bot Tag]] |
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| | last=Abelson
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| | first=H.
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| | authorlink=Hal Abelson
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| | coauthors=G.J. Sussman with J.Sussman
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| | year=1996
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| | title=Structure and Interpretation of Computer Programs
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| | edition=2nd Ed.
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| | publisher=MIT Press
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| | id=ISBN 0-262-01153-0
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| | quote=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.
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| }}</ref>
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| * The theory and practice of [[compilers]] for translating between programming languages | |
| * Practical applications: the [[Personal computer|PC]], the [[internet]], [[search engines]], [[scientific computing]] | |
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| == Relationship with other fields ==
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| {{main | Diversity of computer science}}
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| Despite its name, much of computer science does not involve the study of computers themselves. In fact, the renowned computer scientist [[Edsger Dijkstra]] is often quoted as saying, ''"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 system]]s and their deployment is often called [[information technology]] or [[information systems]]. Computer science is sometimes criticized as being insufficiently scientific, a view espoused in the statement ''"Science is to computer science as hydrodynamics is to plumbing"'' credited to [[Stan Kelly-Bootle]]<ref>'''Computer Language''', Oct 1990</ref> and others. 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 [[artificial intelligence]], [[cognitive science]], [[physics]] (see [[quantum computing]]), and [[linguistics]].
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| Computer science is considered by some to have a much closer relationship with [[mathematics]] than many scientific disciplines<ref name="Denning_cs_discipline" />. 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]].
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| 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 [[Diversity of computer science|computer science is defined]]. Some people believe that software engineering is a subset of computer science. Others, taking a cue from the relationship between other engineering and science disciplines, believe that the principle focus of computer science is studying the properties of computation in general, while the principle focus of software engineering is the design of specific computations to achieve practical goals, making them different disciplines. This view is promulgated by (among others) [[David Parnas]]<ref>{{cite journal | last = Parnas
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| | first = David L.
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| | authorlink = David Parnas
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| | year = 1998
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| | title = [http://citeseer.ist.psu.edu/parnas98software.html Software Engineering Programmes are not Computer Science Programmes]
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| | journal = Annals of Software Engineering
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| | volume = 6
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| | pages = 19–37
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| }}, p. 19: "Rather than treat software engineering as a subfield of
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| computer science, I treat it as an element of the set, {Civil Engineering, Mechanical Engineering,
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| Chemical Engineering, Electrical Engineering,....}."</ref>. Still others maintain that software cannot be engineered at all.
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| == Fields of computer science ==
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| Computer science searches for concepts and proofs to explain and describe computational systems of interest. It is a science because given a system of interest it performs /analysis/ and seeks general principals to explain that system. As with all sciences, these theories can then be utilised to synthesize practical engineering applications, which in turn may suggest new systems to be studied and analysed.
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| === Mathematical foundations ===
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| ; [[Mathematical logic]]
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| : Boolean logic and other ways of modeling logical queries; the uses and limitations of formal proof methods
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| ; [[Number theory]]
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| : Theory of proofs and heuristics for finding proofs in the simple domain of integers. Used in [[cryptography]] as well as a test domain in [[artificial intelligence]].
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| ; [[Graph theory]]
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| : Foundations for data structures and searching algorithms.
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| ; [[Type Theory]]
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| : Formal analysis of the types of data, and the use of these types to understand properties of programs — especially program safety.
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| === Theory of computation ===
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| {{main | Theory of computation}}
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| ; [[Automata theory]]
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| : Different logical structures for solving problems.
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| ; [[Computability theory (computer science)|Computability theory]]
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| : What is calculable with the current models of computers. Proofs developed by [[Alan Turing]] and others provide insight into the possibilities of what may be computed and what may not.
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| ; [[Computational complexity theory]]
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| : Fundamental bounds (especially time and storage space) on classes of computations.
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| ; [[Quantum computing]] theory
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| === Algorithms and data structures ===
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| ; [[Analysis of algorithms]]
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| : Time and space complexity of algorithms.
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| ; [[Algorithms]]
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| : Formal logical processes used for computation, and the efficiency of these processes.
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| ; [[Data structure]]s
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| : The organization of and rules for the manipulation of data.
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| === Programming languages and compilers ===
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| ; [[Compiler]]s
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| : Ways of translating computer programs, usually from [[high-level programming language|higher level]] languages to [[low-level programming language|lower level]] ones. Based heavily on mathematical logic.
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| ; [[Programming language]]s
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| : Formal language paradigms for expressing algorithms, and the properties of these languages (EG: what problems they are suited to solve).
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| === Concurrent, parallel, and distributed systems ===
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| ; [[Concurrency (computer science)|Concurrency]]
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| : The theory and practice of simultaneous computation; data safety in any multitasking or multithreaded environment.
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| ; [[Distributed computing]]
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| : Computing using multiple computing devices over a network to accomplish a common objective or task.
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| ; [[Parallel computing]]
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| : Computing using multiple concurrent threads of execution.
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| === Software engineering ===
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| ; [[Formal methods]]
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| : Mathematical approaches for describing and reasoning about software designs.
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| ; [[Software engineering]]
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| : The principles and practice of designing, developing, and testing programs, as well as proper engineering practices.
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| ; [[Reverse engineering]]
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| : The application of the scientific method to the understanding of arbitrary existing software
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| ; [[Algorithm design]]
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| : Using ideas from algorithm theory to creatively design solutions to real tasks
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| ; [[Computer programming]]
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| : The practice of using a programming language to implement algorithms
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| === Computer architecture ===
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| ; [[Computer architecture]]
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| : The design, organization, optimization and verification of a computer system, mostly about [[CPU]]s and [[Memory (computers)|Memory]] subsystem (and the bus connecting them).
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| ; [[Operating system]]s
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| : Systems for managing computer programs and providing the basis of a useable system.
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| === Communications ===
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| ; [[Computer networking|Networking]]
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| : Algorithms and protocols for reliably communicating data across different shared or dedicated media, often including [[error correction]].
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| ; [[Cryptography]]
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| : Applies results from complexity, probability and number theory to invent and break codes.
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| === Databases ===
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| ; [[Rolodex]]
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| ; [[Flat File String (text) based databases]]
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| ; [[Record Based databases]]
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| ; [[Hierarchical databases]]
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| ; [[Relational databases]]
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| : Study of algorithms for searching and processing data containing references to related data as well as recursive referenced data;
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| ; [[Object Oriented databases]]
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| : Study of algorithms for searching and processing data objects containing data as well as functionality;
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| ; [[Data mining]]
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| : Study of algorithms for searching and processing (related) information in documents and databases; closely related to [[information retrieval]].
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| === Security ===
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| : [[Data Security]]
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| : [[Network Security]]
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| : [[Hardware Security]]
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| : [[Organizational Security]]
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| : [[Security Contingency]]
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| : [[Disaster Security]]
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| === Artificial intelligence ===
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| ; [[Artificial intelligence]]
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| : The implementation and study of systems that exhibit an autonomous intelligence or behaviour of their own.
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| ; [[Automated reasoning]]
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| : Solving engines, such as used in [[Prolog]], which produce steps to a result given a query on a fact and rule database.
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| ; [[Robotics]]
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| : Algorithms for controlling the behavior of robots.
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| ; [[Computer vision]]
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| : Algorithms for identifying three dimensional objects from a two dimensional picture.
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| ; [[Machine learning]]
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| : Automated creation of a set of rules and axioms based on input.
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| === Soft computing ===
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| {{main | Soft computing}}
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| A collective term for techniques used in solving specific problems, see the main article.
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| === Computer graphics ===
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| ; [[Computer graphics]]
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| : Algorithms both for generating visual images synthetically, and for integrating or altering visual and spatial information sampled from the real world.
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| ; [[Image processing]]
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| : Determining information from an image through computation.
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| ; [[Human computer interaction]]
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| : The study and design of computer interfaces that people use.
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| === Scientific computing ===
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| ; [[Computational physics]]
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| : Numerical simulations of large non-analytic systems
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| ; [[Computational chemistry]]
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| ; [[Bioinformatics]]
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| : The use of computer science to maintain, analyse, store [[biological data]] and to assist in solving biological problems such as protein folding.
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| ; [[Computational neuroscience]]
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| : Computational modelling of real brains
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| ; [[Cognitive Science]]
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| : Computational modelling of real minds
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| == Computer science education ==
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| 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.
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| Other colleges and universities, as well as [[secondary school]]s and vocational programs that teach computer science, emphasize the practice of advanced [[computer 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 [[Debates within software engineering|disagreement]] over what the term "software engineering" actually means, and whether it is the same thing as programming.
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| : See [[Peter J. Denning]], ''[http://portal.acm.org/citation.cfm?id=971303 Great principles in computing curricula]'', Technical Symposium on Computer Science Education, 2004.
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| == See also ==
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| * [[Computing]]
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| * [[Informatics]]
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| * [[List of basic computer science topics]]
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| * [[List of computer science conferences]]
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| * [[List of open problems in computer science]]
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| * [[List of publications in computer science]]
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| * [[List of prominent pioneers in computer science]]
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| * [[List of software engineering topics]]
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| * [[Career domains in computer science]]
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| == References ==
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| <div class="references-small">
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| <references/>
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| * [[Association for Computing Machinery]]. [http://www.acm.org/class/1998/overview.html 1998 ACM Computing Classification System]. 1998.
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| * [[IEEE Computer Society]] and the [[Association for Computing Machinery]]. [http://www.computer.org/portal/cms_docs_ieeecs/ieeecs/education/cc2001/cc2001.pdf Computing Curricula 2001: Computer Science]. December 15, 2001.
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| * [[Peter J. Denning]]. ''[http://portal.acm.org/citation.cfm?id=1053309 Is computer science science?]'', Communications of the ACM, April 2005.
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| </div>
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| == External links ==
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| * [http://www.dmoz.org/Computers/Computer_Science/ Open Directory Project: Computer Science]
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| * [http://liinwww.ira.uka.de/bibliography/ Collection of Computer Science Bibliographies]
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| [[Category:Computers Workgroup]]
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| [[Category: CZ Live]] | |
