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m Corrected redirect type from spelling to capitalization. The spelling of the redirect and the target are the same, but their capitalization is different.
 
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#REDIRECT [[Computer science]]
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<div class="thumbcaption">Computer Science deals with the theoretical foundations of information and computation, and with practical techniques for their implementation and application.</div>
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'''Computer Science''' or '''computing science''' (abbreviated '''CS''') is the study of the theoretical foundations of [[information]] and [[computation]] and of practical techniques for their implementation and application in [[computer]] systems.<ref>{{Cite doi|10.1145/63238.63239}} "Computer science and engineering is the systematic study of algorithmic processes-their theory, analysis, design, efficiency, implementation, and application-that describe and transform information."</ref><ref>{{cite conference|author=Wegner, P.|title=Research paradigms in computer science|booktitle=Proceedings of the 2nd international Conference on Software Engineering |location=San Francisco, California, United States| date=October 13–15, 1976|publisher=IEEE Computer Society Press, Los Alamitos, CA|quote=Computer science is the study of information structures}}</ref> Computer scientists invent [[algorithm]]ic processes that create, describe, and transform information and formulate suitable [[abstraction (computer science)|abstraction]]s to model complex systems.


{{Redirect category shell|1=
Computer science has many [[List of computer science fields|sub-fields]]; some, such as [[computational complexity theory]], study the properties of [[computational problem]]s, while others, such as [[computer graphics]], emphasize the computation of specific results. Still others focus on the challenges in implementing computations. For example, [[programming language theory]] studies approaches to describe computations, while [[computer programming]] applies specific [[programming language]]s to solve specific computational problems, and [[human-computer interaction]] focuses on the challenges in making computers and computations useful, usable, and universally accessible to [[humans]].
{{R from capitalization}}

}}
The general public sometimes confuses computer science with careers that deal with computers (such as [[information technology]]), or think that it relates to their own experience of computers, which typically involves activities such as gaming, web-browsing, and word-processing. However, the focus of computer science is more on understanding the properties of the programs used to implement software such as games and web-browsers, and using that understanding to create new programs or improve existing ones.<ref>"''Common myths and preconceptions about Cambridge Computer Science''" [http://www.cl.cam.ac.uk/admissions/undergraduate/myths/ Computer Science Department], [[University of Cambridge]]</ref>

== 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]] designed the first mechanical calculator in 1623, but did not complete its construction.<ref>{{cite web|author=Nigel Tout|title=Calculator Timeline|url=http://www.vintagecalculators.com/html/calculator_time-line.html|work=Vintage Calculator Web Museum|year=2006|accessdate=2006-09-18}}</ref> [[Blaise Pascal]] designed and constructed the first working mechanical calculator, the [[Pascal's calculator|Pascaline]], in 1642. [[Charles Babbage]] designed a [[difference engine]] and then a general-purpose [[Analytical 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 |archiveurl = http://web.archive.org/web/20060908054017/http://www.sciencemuseum.org.uk/on-line/babbage/index.asp <!-- Bot retrieved archive --> |archivedate = 2006-09-08}}</ref>, for which [[Ada Lovelace]] wrote a manual. Because of this work she is regarded today as the world's first [[programmer]].<ref>{{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}}</ref> Around 1900, [[Key punch|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> were introduced. However, 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.<ref>The [[Association for Computing Machinery]] (ACM) was founded in 1947.</ref> 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 1950s and early 1960s.<ref name="Denning_cs_discipline"/><ref>[http://www.cl.cam.ac.uk/conference/EDSAC99/statistics.html CAM.ac.uk]</ref> The first computer science degree program in the United States was formed at [[Purdue University]] in 1962.<ref>[http://www.cs.purdue.edu/feature/conte.html Computer science pioneer Samuel D. Conte dies at 85] July 1, 2002</ref> Since practical computers became available, many applications of computing have become distinct areas of study in their own right.

Although many initially believed it was impossible that computers themselves could actually be a scientific field of study, in the late fifties it gradually became accepted among the greater academic population.<ref name="Levy1984">{{cite book | authorlink = Steven Levy | last = Levy | first = Steven | title = [[Hackers: Heroes of the Computer Revolution]] | year = 1984 | isbn = 0-385-19195-2 | publisher = Doubleday }}</ref> 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".<ref name="Levy1984"/> 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 usability 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. Initially, computers were quite costly, and for their most-effective use, some degree of human aid was needed, in part by professional computer operators. However, as computers became widespread and far more affordable, less human assistance was needed, although residues of the original assistance still remained.

=== Major achievements ===
{{Expand section|date=June 2008}}

[[File:Enigma.jpg|thumb|The [[Germany|German]] military used the [[Enigma machine]] (shown here) 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.<ref name="kahnbook" />]]

Despite its short history as a formal academic discipline, computer science has made a number of fundamental contributions to [[science]] and [[society]]. These include:
* The start of the "digital revolution," which includes the current [[Information Age]] and the [[Internet]].<ref name="bgu">[http://www.cis.cornell.edu/Dean/Presentations/Slides/bgu.pdf Cornell.edu]</ref>
* A formal definition of [[computation]] and [[computability]], and proof that there are computationally [[Undecidable problem|unsolvable]] and [[Computational complexity theory#Intractability|intractable]] problems.<ref>{{Cite journal | 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|format=PDF}}</ref>
* The concept of a [[programming language]], a tool for the precise expression of methodological information at various levels of abstraction.<ref>{{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
| publisher=MIT Press
| 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.
}}</ref>
* In [[cryptography]], [[Cryptanalysis of the Enigma|breaking the Enigma machine]] was an important factor contributing to the Allied victory in World War II.<ref name="kahnbook">[[David Kahn (writer)|David Kahn]], [[The Codebreakers]], 1967, ISBN 0-684-83130-9.</ref>
* [[Scientific computing]] enabled practical evaluation of processes and situations of great complexity, as well as experimentation entirely by software. It also enabled advanced study of the mind, and mapping of the human genome became possible with the [[Human Genome Project]].<ref name="bgu"/> [[Distributed computing]] projects such as [[Folding@home]] explore [[protein folding]].
* [[Algorithmic trading]] has increased the [[Economic efficiency|efficiency]] and [[Market liquidity|liquidity]] of financial markets by using [[artificial intelligence]], [[machine learning]], and other [[statistics|statistical]] and [[Numerical analysis|numerical]] techniques on a large scale.<ref>[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</ref>
* Image synthesis, including video by computing individual video frames.{{Citation needed|date=October 2010}}
* Human language processing, including practical speech-to-text conversion and automated translation of languages{{Citation needed|date=October 2010}}
* [[Simulation]] of various processes, including computational fluid dynamics, physical, electrical, and electronic systems and circuits, as well as societies and social situations (notably war games) along with their habitats, among many others. Modern computers enable optimization of such designs as complete aircraft. Notable in electrical and electronic circuit design are [[SPICE]] as well as software for physical realization of new (or modified) designs. The latter includes essential design software for integrated circuits.{{Citation needed|date=October 2010}}

== Philosophy ==
{{main|Philosophy of computer science}}
Following [[Peter Wegner]], Amnon H. Eden proposes that there are three [[paradigm]]s at work in various areas of computer science:<ref>{{cite doi|10.1007/s11023-007-9060-8}}</ref>
* a "rationalist paradigm", which treats computer science as branch of mathematics, which is prevalent in theoretical computer science, and mainly employs [[deductive reasoning]],
* a "technocratic paradigm", readily identifiable with [[engineering]] approaches, most prominent in software engineering, and
* a "scientific paradigm", which approaches computer-related artifacts from the empirical perspective of [[natural science]]s, and identifiable in some branches of artificial intelligence (the study of [[artificial life]] for instance).

== Fields of computer science ==

As a discipline, computer science spans a range of topics from theoretical studies of algorithms and the limits of computation to the practical issues of implementing computing systems in hardware and software.<ref name="CSAB1997">{{cite web|author=Computing Sciences Accreditation Board|title=Computer Science as a Profession|url=http://www.csab.org/comp_sci_profession.html |date=28 May 1997| accessdate=2010-05-23 |archiveurl = http://web.archive.org/web/20080617030847/http://www.csab.org/comp_sci_profession.html |archivedate = 2008-06-17}}</ref><ref>{{cite book|author=Committee on the Fundamentals of Computer Science: Challenges and Opportunities, National Research Council |title=Computer Science: Reflections on the Field, Reflections from the Field|url=http://www.nap.edu/catalog.php?record_id=11106#toc|publisher=National Academies Press|isbn=978-0-309-09301-9|year=2004}}</ref>
[[CSAB (professional organization)|CSAB]], formerly called ''Computing Sciences Accreditation Board'' – which is made up of representatives of the [[Association for Computing Machinery]] (ACM), and the [[IEEE Computer Society]] (IEEE-CS)<ref>[http://www.csab.org/ CSAB, Inc.]</ref> – identifies four areas that it considers crucial to the discipline of computer science: ''theory of computation'', ''algorithms and data structures'', ''programming methodology and languages'', and ''computer elements and architecture''. In addition to these four areas, CSAB also identifies fields such as software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, computer-human interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.<ref name="CSAB1997"/>

=== Theoretical computer science ===
{{main|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.
{| style="border:1px solid #ccc; text-align:center; margin:auto;" cellspacing="15"
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| [[Mathematical logic]]
| [[Computational number theory|Number theory]]
| [[Graph theory]]
| [[Category theory]]
| [[Quantum computer|Quantum computing theory]]
|}

==== Theory of computation ====
{{main|Theory of computation}}
According to [[Peter J. Denning]], the fundamental question underlying computer science is, ''"What can be (efficiently) automated?"''<ref name="Denning_cs_discipline">{{cite journal | last=Denning | first=P.J. | authorlink=Peter J. Denning | year=2000 | title=Computer Science: The Discipline | url=http://www.idi.ntnu.no/emner/dif8916/denning.pdf | journal=Encyclopedia of Computer Science|format=PDF |archiveurl = http://web.archive.org/web/20060525195404/http://www.idi.ntnu.no/emner/dif8916/denning.pdf |archivedate = 2006-05-25}}</ref> 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 (computer science)|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 multitude of computational problem.

The famous "[[P = NP problem|P=NP?]]" problem, one of the [[Millennium Prize Problems]],<ref>[http://www.claymath.org/millennium/P_vs_NP/ Clay Mathematics Institute] P=NP</ref> is an open problem in the theory of computation.

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| '''P = NP''' ?
| '''GNITIRW-TERCES'''
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| [[Automata theory]]
| [[Computability theory]]
| [[Computational complexity theory]]
| [[Cryptography]]
|}

==== Information and coding theory ====
{{main|Information theory|Coding theory}}
{{Expand section|date=March 2011}}
Information theory is related to the quantification of information.This was developed by Claude E. Shannon to find
fundamental limits on signal processing operations such as compressing data and on reliably storing and communicating data.
Coding theory is the study of the properties of codes and their fitness for a specific application. Codes are used for data compression, cryptography, error-correction and more recently also for network coding. Codes are studied for the purpose of designing efficient and reliable data transmission methods.

==== Algorithms and data structures ====

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| <math>O(n^2)</math>
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|-
| [[Analysis of algorithms]]
| [[Algorithms]]
| [[Data structures]]
| [[Computational geometry]]
|}

==== Programming language theory ====
{{main|Programming language theory}}
Programming language theory is a branch of computer science that deals with the design, implementation, analysis, characterization, and classification of [[programming language]]s and their individual [[Programming language#Elements|features]]. It falls within the discipline of computer science, both depending on and affecting [[mathematics]], [[software engineering]] and [[linguistics]]. It is a well-recognized branch of computer science, and an active research area, with results published in numerous [[Academic journal|journals]] dedicated to PLT, as well as in general computer science and engineering publications.

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| <math>\Gamma\vdash x: \text{Int}</math>
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| [[File:Python add5 syntax.svg|96px]]
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| [[Type theory]]
| [[Compiler design]]
| [[Programming languages]]
|}

==== Formal methods ====
{{main|Formal methods}}
Formal methods are a particular kind of [[mathematically]]-based techniques for the [[formal specification|specification]], development and [[formal verification|verification]] of [[software]] and [[hardware]] systems. The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design. However, the high cost of using formal methods means that they are usually only used in the development of high-integrity systems, where [[safety]] or [[security]] is of utmost importance. Formal methods are best described as the application of a fairly broad variety of [[theoretical computer science]] fundamentals, in particular [[logic in computer science|logic]] calculi, [[formal language]]s, [[automata]] theory, and [[program semantics]], but also [[type systems]] and [[algebraic data types]] to problems in software and hardware specification and verification.

==== Concurrent, parallel and distributed systems ====
{{main|Concurrency (computer science)|Distributed computing}}
Concurrency is a property of systems in which several computations are executing simultaneously, and potentially interacting with each other. A number of mathematical models have been developed for general concurrent computation including [[Petri nets]], [[process calculi]] and the [[Parallel Random Access Machine]] model. A distributed system extends the idea of concurrency onto multiple computers connected through a network. Computers within the same distributed system have their own private memory, and information is often exchanged amongst themselves to achieve a common goal.

==== Databases and information retrieval ====
{{main|Database|Database management systems}}
A database is intended to organize, store, and retrieve large amounts of data easily. Digital databases are managed using database management systems to store, create, maintain, and search data, through [[database models]] and [[query languages]].
{{Expand section|date=January 2011}}

=== Applied computer science ===

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''.<ref>Communications of the ACM 1(4):p.6</ref> Three months later in the same journal, ''comptologist'' was suggested, followed next year by ''hypologist''.<ref>Communications of the ACM 2(1):p.4</ref> The term ''computics'' has also been suggested.<ref>IEEE Computer 28(12):p.136</ref> In continental Europe, names such as ''informatique'' (French), ''Informatik'' (German) or ''informatika'' ([[Slavic languages]]), 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 system]]s 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.<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]].

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.<ref>{{Cite 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, [...]"</ref>

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 with [[computational science]]. Both types of departments tend to make efforts to bridge the field educationally if not across all research.

==== Artificial intelligence ====
{{main|Artificial intelligence}}
This branch of computer science aims to create synthetic systems which solve computational problems, reason and/or communicate like animals and humans do. This theoretical and applied subfield requires a very rigorous and integrated expertise in multiple subject areas such as [[applied mathematics]], [[logic]], [[semiotics]], [[electrical engineering]], [[philosophy of mind]], [[neurophysiology]], and [[social intelligence]] which can be used to advance the field of intelligence research or be applied to other subject areas which require computational understanding and modelling such as in [[finance]] or the [[physical sciences]]. This field started in full earnest when [[Alan Turing]], the pioneer of computer science and [[artificial intelligence]], proposed the [[Turing Test]] for the purpose of answering the ultimate question... "Can computers think ?".

{| style="border:1px solid #ccc; text-align:center; margin:auto;" cellspacing="15"
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| [[Machine Learning]]
| [[Computer vision]]
| [[Image Processing]]
| [[Pattern Recognition]]
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| [[File:User-FastFission-brain.gif|96px]]
| [[File:data.png|96px]]
| [[File:sky.png|96px]]
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| [[Cognitive Science]]
| [[Data Mining]]
| [[Evolutionary Computation]]
| [[Information Retrieval]]
|-
| [[File:neuron.svg|96px]]
| [[File:english.png|96px]]
| [[File:HONDA ASIMO.jpg|64px]]
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| [[Knowledge Representation]]
| [[Natural Language Processing]]
| [[Robotics]]
|}

==== Computer architecture and engineering ====
{{main|Computer architecture|Computer engineering}}
Computer architecture, or digital computer organization, is the conceptual design and fundamental operational structure of a computer system. It focuses largely on the way by which the central processing unit performs internally and accesses addresses in memory. The field often involves disciplines of computer engineering and electrical engineering, selecting and interconnection hardware components to create computers that meet functional, performance, and cost goals.

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| [[Digital logic]]
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| [[Multiprocessing]]
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| [[Operating systems]]
| [[Computer networking|Computer networks]]
| [[Databases]]
| [[Computer security]]
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|-
| [[Ubiquitous computing]]
| [[Systems architecture]]
| [[Compiler design]]
| [[Programming languages]]
|}

==== Computer graphics and visualization ====
{{main|Computer graphics (computer science)}}
Computer graphics is the study of digital visual contents, and involves syntheses and manipulations of image data. The study is connected to many other fields in computer science, including [[computer vision]], [[image processing]], and [[computational geometry]], and are heavily applied in the fields of [[special effects]] and [[video games]].

==== Computer security and cryptography ====
{{main|Computer security|Cryptography}}
Computer security is a branch of computer technology, whose objective includes protection of information from unauthorized access, disruption, or modification while maintaining the accessibility and usability of the system for its intended users. Cryptography is the practice and study of hiding (encryption) and therefore deciphering (decryption) information. Modern cryptography is largely related to computer science, for many encryption and decryption algorithms are based on their computational complexity.

==== Computational science ====

[[Computational science]] (or [[scientific computing]]) is the field of study concerned with constructing [[scientific modelling|mathematical model]]s and [[numerical analysis|quantitative analysis]] techniques and using computers to analyse and solve [[scientific]] problems. In practical use, it is typically the application of [[computer simulation]] and other forms of [[computation]] to problems in various scientific disciplines.

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| [[Numerical analysis]]
| [[Computational physics]]
| [[Computational chemistry]]
| [[Bioinformatics]]
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==== Information science ====
{{main|Information science}}

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| [[Information Retrieval]]
| [[Knowledge Representation]]
| [[Natural Language Processing]]
| [[Human–computer interaction]]
|}

{{Expand section|date=January 2011}}

==== Software engineering ====
{{main|Software engineering}}
Software engineering is the study of designing, implementing, and modifying software in order to ensure it is of high quality, affordable, maintainable, and fast to build. It is a systematic approach to software design, involving the application of engineering practices to software.
{{Expand section|date=January 2011}}

== 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 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 process aspects of computer programming are often referred to as [[software engineering]].

Yet while computer science professions increasingly drive the U.S. economy, computer science education is absent in most American K-12 curricula. A report entitled [http://www.acm.org/runningonempty/ "Running on Empty: The Failure to Teach K-12 Computer Science in the Digital Age"] was released in October 2010 by [http://www.acm.org/ Association for Computing Machinery (ACM)] and [http://csta.acm.org/ Computer Science Teachers Association (CSTA)], and revealed that only 14 states have adopted significant education standards for high school computer science. The report also found that only nine states count high school computer science courses as a core academic subject in their graduation requirements. In tandem with "Running on Empty," a new, non-partisan advocacy coalition--[http://www.computinginthecore.org/ Computing in the Core (CinC)]--was founded to influence federal and state policy, such as the [http://www.govtrack.us/congress/bill.xpd?bill=h111-5929&tab=summary Computer Science Education Act], which calls for grants to states to develop plans for improving computer science education and supporting computer science teachers.

== See also ==
{{Portal box|Computer science}}
{{Wikipedia-Books|Computer science}}
{{Main|Outline of computer science}}
{{colbegin|2}}
* [[Academic genealogy of computer scientists]]
* [[Computer scientist]]
* [[Computing]]
* [[History of computer science]]
* [[Informatics (academic field)|Informatics]]
* [[List of academic computer science departments]]
* [[List of computer science conferences]]
* [[List of computer scientists]]
* [[Unsolved problems in computer science|List of open problems in computer science]]
* [[List of important publications in computer science|List of publications in computer science]]
* [[List of pioneers in computer science]]
* [[List of software engineering topics]]
* [[Philosophy of computer science]]
* [[Women in computing]]
{{colend}}

== References ==
{{Reflist|2}}

== Further reading ==
{{refbegin|2}}
; Overview
* {{cite book|first=Allen B.|last=Tucker|authorlink=Allen B. Tucker|title=Computer Science Handbook|edition=2nd|publisher=Chapman and Hall/CRC|year=2004|isbn=158488360X}}
** "Within more than 70 chapters, every one new or significantly revised, one can find any kind of information and references about computer science one can imagine. [...] all in all, there is absolute nothing about Computer Science that can not be found in the 2.5 kilogram-encyclopaedia with its 110 survey articles [...]." (Christoph Meinel, ''[[Zentralblatt MATH]]'')
* {{cite book|first=Jan|last=van Leeuwen|authorlink=Jan van Leeuwen|title=Handbook of Theoretical Computer Science|publisher=The MIT Press|year=1994|isbn=0262720205}}
** "[...] this set is the most unique and possibly the most useful to the [theoretical computer science] community, in support both of teaching and research [...]. The books can be used by anyone wanting simply to gain an understanding of one of these areas, or by someone desiring to be in research in a topic, or by instructors wishing to find timely information on a subject they are teaching outside their major areas of expertise." (Rocky Ross, ''[[SIGACT News]]'')
* {{cite book|title=Encyclopedia of Computer Science|edition=4th|first1=Anthony|last1=Ralston|authorlink=Anthony Ralston|first2=Edwin D.|last2=Reilly|authorlink2=Edwin D. Reilly|first3=David|last3=Hemmendinger|authorlink3=David Hemmendinger|publisher=Grove's Dictionaries|year=2000|isbn=156159248X|url=http://portal.acm.org/ralston.cfm}}
** "Since 1976, this has been the definitive reference work on computer, computing, and computer science. [...] Alphabetically arranged and classified into broad subject areas, the entries cover hardware, computer systems, information and data, software, the mathematics of computing, theory of computation, methodologies, applications, and computing milieu. The editors have done a commendable job of blending historical perspective and practical reference information. The encyclopedia remains essential for most public and academic library reference collections." (Joe Accardin, Northeastern Illinois Univ., Chicago)
;Selected papers
* {{cite book|first=Donald E.|last=Knuth|authorlink=Donald Knuth|title=Selected Papers on Computer Science|publisher=CSLI Publications, [[Cambridge University Press]]|year=1996}}
** "Covering a period from 1966 to 1993, its interest lies not only in the content of each of these papers &mdash; still timely today &mdash; but also in their being put together so that ideas expressed at different times complement each other nicely." (N. Bernard, ''Zentralblatt MATH'')
;Articles
* 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.
* 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.
* Research evaluation for computer science, Informatics Europe [http://www.informatics-europe.org/docs/research_evaluation.pdf report]. Shorter journal version: Bertrand Meyer, Christine Choppy, Jan van Leeuwen and Jorgen Staunstrup, ''Research evaluation for computer science'', in [[Communications of the ACM]], vol. 52, no. 4, pp. 31-34, April 2009.
; Curriculum and classification
* [[Association for Computing Machinery]]. [http://www.acm.org/class/1998/overview.html 1998 ACM Computing Classification System]. 1998.
* Joint Task Force of Association for Computing Machinery (ACM), [[Association for Information Systems]] (AIS) and [[IEEE Computer Society]] (IEEE-CS). [http://www.acm.org/education/curric_vols/CC2005-March06Final.pdf Computing Curricula 2005: The Overview Report]. September 30, 2005.
* [[Norman Gibbs]], [[Allen Tucker]]. "A model curriculum for a liberal arts degree in computer science". ''Communications of the ACM'', Volume 29 Issue 3, March 1986.
{{refend}}

== External links ==
{{Sister project links}}
* {{dmoz|Computers/Computer_Science/}}
* [http://www.lib.uwaterloo.ca/society/compsci_soc.html Scholarly Societies in Computer Science]
* [http://jeffhuang.com/best_paper_awards.html Best Papers Awards in Computer Science since 1996]
* [http://se.ethz.ch/~meyer/gallery/ Photographs of computer scientists] by [[Bertrand Meyer]]
; Bibliography and academic search engines
* [http://citeseerx.ist.psu.edu/ CiteSeer<sup>''x''</sup>]: search engine, digital library and repository for scientific and academic papers with a focus on computer and information science.
* [http://dblp.uni-trier.de/ DBLP Computer Science Bibliography]: computer science bibliography website hosted at Universität Trier, in Germany.
* [http://liinwww.ira.uka.de/bibliography/ The Collection of Computer Science Bibliographies]
;Webcasts
* [http://www.lecturefox.com/computerscience/ Directory of free university lectures in Computer Science]
* [http://videolectures.net/Top/Computer_Science/ Collection of computer science lectures]
* [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]

{{Computer Science}}

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