Computer science
'''Computer science''' (or '''computing science''') is the study and the [[science]] of the theoretical foundations of [[information]] and [[computation]] and their implementation and application in [[computer|computer system]]s.["''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]["''Computer science is the study of computation.''" [http://www.csbsju.edu/computerscience/curriculum Computer Science Department, College of Saint Benedict], Saint John's University]["''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]] Computer science has many sub-fields; some emphasize the computation of specific results (such as [[computer graphics]]), while others relate to properties of [[computational problem]]s (such as [[computational complexity theory]]). 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. A further subfield, [[human-computer interaction]], focuses on the challenges in making computers and computations useful, usable and universally accessible to [[humans|people]].
== History ==
{{main | History of computer science}}
The early foundations of what would become computer science predate the invention of the modern [[digital computer]]. Machines for calculating fixed numerical tasks, such as the [[abacus]], have existed since antiquity. [[Wilhelm Schickard]] built the first mechanical calculator in 1623.[{{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}}] [[Charles Babbage]] designed a [[difference engine]] in [[Victorian era|Victorian]] times (between 1837 and 1901)[{{cite web | url=http://www.sciencemuseum.org.uk/on-line/babbage/index.asp | title=Science Museum - Introduction to Babbage | accessdate=2006-09-24}}] helped by [[Ada Lovelace]].[{{cite web| url=http://www.scottlan.edu/Lriddle/women/ada-love.htm| title=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 | accessdate=2006-05-04}}] Around 1900, the [[IBM]] corporation sold [[Key_punch|punch-card machines]].[{{cite web | url=http://www.pattonhq.com/ibm.html | title=IBM Punch Cards in the U.S. Army | accessdate=2006-09-24}}] However, all of these machines were constrained to perform a single task, or at best some subset of all possible tasks.
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.[{{cite journal | last=Denning | first=P.J. | authorlink=Peter J. Denning | year=2000 | title=Computer Science: The Discipline | url=http://web.archive.org/web/20060525195404/http://www.idi.ntnu.no/emner/dif8916/denning.pdf | journal=Encyclopedia of Computer Science}}] Since practical computers became available, many applications of computing have become distinct areas of study in their own right.
Many initially believed it impossible that "computers themselves could actually be a scientific field of study" (Levy 1984, p. 11), though it was in the "late fifties" (Levy 1984, p.11) that it gradually became accepted among the greater academic population. It is the now well-known IBM brand that formed part of the computer science revolution during this time. 'IBM' (short for International Business Machines) released the IBM 704 and later the IBM 709 computers, which were widely used during the exploration period of such devices. "Still, working with the IBM [computer] was frustrating...if you had misplaced as much as one letter in one instruction, the program would crash, and you would have to start the whole process over again" (Levy 1984, p.13). During the late 1950s, the computer science discipline was very much in its developmental stages, and such issues were commonplace.
Time has seen significant improvements in the useability and effectiveness of computer science technology. Modern society has seen a significant shift from computers being used solely by experts or professionals to a more widespread user base. By the 1990s, computers became accepted as being the norm within everyday life. During this time data entry was a primary component of the use of computers, many preferring to streamline their business practices through the use of a computer. This also gave the additional benefit of removing the need of large amounts of documentation and file records which consumed much-needed physical space within offices.
== Major achievements ==
{{Expand-section|date=June 2008}}
[[Image:Enigma.jpg|170px|thumbnail|right|[[Germany|German]] military used the [[Enigma machine]] during [[World War II]] for communication they thought to be secret. The large-scale decryption of Enigma traffic at [[Bletchley Park]] was an important factor that contributed to Allied victory in WWII.[{{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}}]
* The concept of a [[programming language]], a tool for the precise expression of methodological information at various levels of abstraction.[{{cite book|
| last=Abelson
| first=H.
| authorlink=Hal Abelson
| coauthors=G.J. Sussman with J.Sussman
| year=1996
| title=Structure and Interpretation of Computer Programs
| edition=2nd Ed.
| publisher=MIT Press
| id=ISBN 0-262-01153-0
| 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.
}}]
;Applications outside of computing
* Sparked the [[Digital Revolution]] which led to the current [[Information Age]] and the [[Internet]].[http://www.cis.cornell.edu/Dean/Presentations/Slides/bgu.pdf]
* In [[cryptography]], [[Cryptanalysis of the Enigma|breaking the Enigma machine]] was an important factor contributing to the Allied victory in World War II.[[[David Kahn]], [[The Codebreakers]], 1967, ISBN 0-684-83130-9.]
* [[Scientific computing]] enabled advanced study of the mind and mapping the human genome was possible with [[Human Genome Project]].[[http://www.telegraph.co.uk/money/main.jhtml?xml=/money/2006/08/27/ccsoft27.xml Black box traders are on the march] The Telegraph, August 26, 2006]
== 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. 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 and practitioners of the field of computing were suggested in the ''Communications are 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] Recently the term ''computics'' has been suggested.[IEEE Computer 28(12):p.136] ''Informatik'' was a term used in Europe with more frequency.
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 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]][''Computer Language'', October 1990] 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 [[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.[{{cite journal | last = Parnas
| first = David L.
| authorlink = David Parnas
| year = 1998
| title = [http://citeseer.ist.psu.edu/parnas98software.html Software Engineering Programmes are not Computer Science Programmes]
| journal = Annals of Software Engineering
| volume = 6
| pages = 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, ....}."]
The academic, political, and funding aspects of computer science tend to have roots as to whether a department in the U.S. formed with either a mathematical emphasis or an engineering emphasis. In general, electrical engineering-based computer science departments have tended to succeed as computer science and/or engineering departments.{{Fact|date=December 2007}} 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.
== Fields of computer science ==
Computer science searches for concepts and [[formal proof]]s to explain and describe computational systems of interest. 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. While the [[ACM Computing Classification System]] can be used to split computer science up into different topics of fields, a more descriptive breakdown follows:
{{Cleanup-laundry|date=February 2008}}
=== Mathematical foundations ===
; [[Mathematical logic]]
: Boolean logic and other ways of modeling logical queries; the uses and limitations of formal proof methods.
; [[Number theory]]
: 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]].
; [[Graph theory]]
: Foundations for data structures and searching algorithms.
; [[Type theory]]
: Formal analysis of the types of data, and the use of these types to understand properties of programs, especially program safety.
; [[Category theory]]
: Category theory provides a means of capturing all of math and computation in a single synthesis.
; [[Computational geometry]]
: The study of [[algorithm]]s to solve problems stated in terms of [[geometry]].
; [[Numerical analysis]]
: Foundations for algorithms in discrete mathematics, as well as the study of the limitations of floating point computation, including [[round-off]] errors.
=== Theory of computation ===
{{main | Theory of computation}}
; [[Automata theory]]
: Different logical structures for solving problems.
; [[Computability theory (computer science)|Computability theory]]
: What is calculable with the current models of computers. Proofs developed by [[Alan Turing]] and others provide insight into the possibilities of what can be computed and what cannot.
; [[Computational complexity theory]]
: Fundamental bounds (especially time and storage space) on classes of computations; in practice, study of which problems a computer can solve with reasonable resources (while computability theory studies which problems can be solved at all).
; [[Quantum computing|Quantum computing theory]]
: Representation and manipulation of data using the quantum properties of particles and quantum mechanism.
=== Algorithms and data structures ===
; [[Analysis of algorithms]]
: Time and space complexity of algorithms.
; [[Algorithms]]
: Formal logical processes used for computation, and the efficiency of these processes.
=== Programming languages and compilers ===
; [[Compiler]]s
: Ways of translating computer programs, usually from [[high-level programming language|higher level]] languages to [[low-level programming language|lower level]] ones.
; [[Interpreter (computing)|Interpreter]]s
: A program that takes in as input a computer program and executes it.
; [[Programming language]]s
: Formal language paradigms for expressing algorithms, and the properties of these languages (e.g., what problems they are suited to solve).
=== Concurrent, parallel, and distributed systems ===
; [[Concurrency (computer science)|Concurrency]]
: The theory and practice of simultaneous computation; data safety in any multitasking or multithreaded environment.
; [[Distributed computing]]
: Computing using multiple computing devices over a network to accomplish a common objective or task and thereby reducing the latency involved in single processor contributions for any task.
; [[Parallel computing]]
: Computing using multiple concurrent threads of execution.
=== Software engineering ===
; [[Algorithm design]]
: Using ideas from algorithm theory to creatively design solutions to real tasks
; [[Computer programming]]
: The practice of using a programming language to implement algorithms
; [[Formal methods]]
: Mathematical approaches for describing and reasoning about software designs.
; [[Reverse engineering]]
: The application of the scientific method to the understanding of arbitrary existing software
; [[Software development]]
: The principles and practice of designing, developing, and testing programs, as well as proper engineering practices.
=== System architecture ===
; [[Computer architecture]]
: The design, organization, optimization and verification of a computer system, mostly about [[CPU]]s and [[memory (computers)|memory]] subsystems (and the bus connecting them).
; [[Computer organization]]
: The implementation of computer architectures, in terms of descriptions of their specific [[electrical circuit]]ry
; [[Operating system]]s
: Systems for managing computer programs and providing the basis of a useable system.
=== Communications ===
; [[Computer audio]]
: Algorithms and data structures for the creation, manipulation, storage, and transmission of [[digital audio]] recordings. Also important in [[voice recognition]] applications.
; [[Computer networking|Networking]]
: Algorithms and protocols for communicating data across different shared or dedicated media, often including [[error correction]].
; [[Cryptography]]
: Applies results from complexity, probability and number theory to invent and break codes.
=== Databases ===
; [[Data mining]]
: Data mining is the extraction of relevant data from all sources of data.
; [[Relational databases]]
: Study of algorithms for searching and processing information in documents and databases; closely related to [[information retrieval]].
; [[OLAP]]
: Online Analytical Processing, or OLAP, is an approach to quickly provide answers to analytical queries that are multi-dimensional in nature. OLAP is part of the broader category [[business intelligence]], which also encompasses relational reporting and data mining.
=== Artificial intelligence ===
; [[Artificial intelligence]]
: The implementation and study of systems that exhibit an autonomous intelligence or behaviour of their own.
; [[Artificial life]]
: The study of digital organisms to learn about biological systems and evolution.
; [[Automated reasoning]]
: Solving engines, such as used in [[Prolog]], which produce steps to a result given a query on a fact and rule database.
; [[Computer vision]]
: Algorithms for identifying three dimensional objects from one or more two dimensional pictures.
; [[Machine learning]]
: Automated creation of a set of rules and axioms based on input.
; [[Natural language processing]]/[[Computational linguistics]]
: Automated understanding and generation of human language
; [[Robotics]]
: Algorithms for controlling the behavior of robots.
=== Visual rendering (or Computer graphics) ===
; [[Computer graphics]]
: Algorithms both for generating visual images synthetically, and for integrating or altering visual and spatial information sampled from the real world.
; [[Image processing]]
: Determining information from an image through computation.
=== Human-Computer Interaction ===
; [[Human computer interaction]]
: The study of making computers and computations useful, usable and universally accessible to [[user (computing)|people]], including the study and design of computer interfaces through which people use computers.
=== Scientific computing ===
; [[Bioinformatics]]
: The use of computer science to maintain, analyse, and store [[biological data]], and to assist in solving biological problems such as [[protein folding]], function prediction and [[phylogeny]].
; [[Cognitive Science]]
: Computational modelling of real minds
; [[Computational chemistry]]
: Computational modelling of theoretical chemistry in order to determine chemical structures and properties
; [[Computational neuroscience]]
: Computational modelling of real brains
; [[Computational physics]]
: Numerical simulations of large non-analytic systems
; [[Numerical analysis|Numerical algorithms]]
: Algorithms for the numerical solution of mathematical problems such as [[Root-finding algorithm|root-finding]], [[Numerical integration|integration]], the [[Numerical ordinary differential equations|solution of ordinary differential equations]] and the approximation/evaluation of [[special functions]].
; [[Symbolic mathematics]]
: Manipulation and solution of expressions in symbolic form, also known as [[Computer algebra]].
=== Didactics of computer science/informatics ===
{{main | Didactics of informatics}}
The subfield didactics of computer science focuses on cognitive approaches of developing competencies of computer science and specific strategies for analysis, design, implementation and evaluation of excellent lessons in computer science.
== 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 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.
== See also ==
{{portal}}
: ''Main list: [[List of basic computer science topics]]''
* [[Computer scientist]]
* [[Career domains in computer science]]
* [[English in computer science]]
* [[Women in computer science]]
* [[Computing]]
* [[Informatics]]
* [[List of academic computer science departments]]
* [[List of computer science conferences]]
* [[List of open problems in computer science]]
* [[List of prominent pioneers in computer science]]
* [[List of publications in computer science]]
* [[List of software engineering topics]]
* [[List of computer scientists]]
== References ==
{{reflist|2}}
* [[Association for Computing Machinery]]. [http://www.acm.org/class/1998/overview.html 1998 ACM Computing Classification System]. 1998.
* [[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.
* [[Peter J. Denning]]. ''[http://portal.acm.org/citation.cfm?id=1053309&coll=&dl=ACM&CFID=15151515&CFTOKEN=6184618 Is computer science science?]'', Communications of the ACM, April 2005.
* {{cite book | authorlink = Steven Levy | last = Levy | first = Steven | title = [[Hackers: Heroes of the Computer Revolution]] | year = 1984 | id = ISBN 0-385-19195-2 | publisher = Doubleday }}
* [[Donald E. Knuth]]. ''Selected Papers on Computer Science,'' CSLI Publications, Cambridge Univ. Press, 1996.
* [[Peter J. Denning]], ''[http://portal.acm.org/citation.cfm?id=971303&dl=ACM&coll=&CFID=15151515&CFTOKEN=6184618 Great principles in computing curricula]'', Technical Symposium on Computer Science Education, 2004.
== External links ==
{{wikibooks}}
{{wikiversity | Portal:Computer Science}}
* {{dmoz|Computers/Computer_Science/}}
* [http://www.lecturefox.com/computerscience/ Directory of free university lectures in Computer Science]
* [http://liinwww.ira.uka.de/ bibliography/ Collection of Computer Science Bibliographies]
* [http://csdir.org/ CS Directory and resources]
* [http://se.ethz.ch/~meyer/gallery/ Photographs of computer scientists] ([[Bertrand Meyer]]'s gallery)
=== Webcasts ===
* [http://www.oid.ucla.edu/webcasts/courses/2006-2007/2006fall/cs1 UCLA Computer Science 1 Freshman Computer Science Seminar Section 1]
* [http://webcast.berkeley.edu/course_details.php?seriesid=1906978395 Berkeley Introduction to Computers]
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