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Computer graphics Computational complexity theory
Programming language theory Human–computer interaction
Computer science deals with the theoretical foundations of information and computation, and of practical techniques for their implementation and application.

Computer science or computing science (sometimes 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.[1][2][3] It is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. According to Peter J. Denning, the fundamental question underlying computer science is, "What can be (efficiently) automated?"[4] Computer science has many sub-fields; some, such as computer graphics, emphasize the computation of specific results, while others, such as computational complexity theory, study the properties of computational problems. 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 languages to solve specific computational problems, and human-computer interaction focuses on the challenges in making computers and computations useful, usable, and universally accessible to people.

The general public sometimes confuses computer science with careers that deal with computers (such as the noun 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.[5]

Contents

History

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.[6] Charles Babbage designed a difference engine in Victorian times[7] helped by Ada Lovelace.[8] Around 1900, punch-card machines[9] were introduced. 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.[10] 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.[4][11] The first computer science degree program in the United States was formed at Purdue University in 1962.[12] 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.[13] 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".[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 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.

Major achievements

The 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.[14]

Despite its short history as a formal academic discipline, computer science has made a number of fundamental contributions to science and society. These include:

Areas 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.[19][20] The Computer Sciences Accreditation Board (CSAB) [21] – which is made up of representatives of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers Computer Society, and the Association for Information Systems – 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.[19]

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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.

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Mathematical logic Automata theory Number theory Graph theory
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Type theory Category theory Computational geometry Quantum computing theory

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,[22] is an open problem in the theory of computation.

Wang tiles.png P = NP ? GNITIRW-TERCES
Computability theory Computational complexity theory Cryptography

Algorithms and data structures

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Analysis of algorithms Algorithms Data structures

Computer elements and architecture

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Digital logic Microarchitecture Multiprocessing

Computational science

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Numerical analysis Computational physics Computational chemistry Bioinformatics
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Computational neuroscience Computational sociology Computational economics Biometrics
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Computer graphics

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. It all started with the grandfather of computer science and artificial intelligence, Alan Turing, who proposed the Turing Test for the purpose of answering the ultimate question... "Can computers think ?".

Brain.png Eye.png Corner.png KnnClassification.svg
Machine Learning Computer vision Image Processing Pattern Recognition
User-FastFission-brain.gif Data.png Sky.png Earth.png
Cognitive Science Data Mining Evolutionary Computation Information Retrieval
Neuron.png English.png Robot.png Wacom Pen-tablet.jpg
Knowledge Representation Natural Language Processing Robotics Human–computer interaction

Software Engineering

The area of software engineering specializes in storage, transfer and communication of data rather than the computational analysis of data. Although many computer scientists seek software engineering positions it is not necessarily computer science related. In 2004, a newly established degree of software engineering established by both ACM and IEEE was formed to address these issues; a document called CCSE was written to explain the details. In addition those with degrees in information technology or management information systems are often found to be necessary supportive roles for both software engineering and computational work.

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Operating systems Computer networks Databases Computer security
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Ubiquitous computing Systems architecture Compiler design Programming languages

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 ACMturingineer, turologist, flow-charts-man, applied meta-mathematician, and applied epistemologist.[23] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.[24] The term computics has also been suggested.[25] In continental Europe, names such as informatique (French), Informatik (German) or informatica (Dutch), derived from information and possibly mathematics or automatic, are more common than names derived from computer/computation.

The renowned computer scientist Edsger Dijkstra stated, "Computer science is no more about computers than astronomy is about telescopes." The design and deployment of computers and computer systems is generally considered the province of disciplines other than computer science. For example, the study of computer hardware is usually considered part of computer engineering, while the study of commercial computer systems and their deployment is often called information technology or information systems. However, there has been much cross-fertilization of ideas between the various computer-related disciplines. Computer science research has also often crossed into other disciplines, such as philosophy, cognitive science, linguistics, mathematics, physics, statistics, and 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.[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.[26]

The academic, political, and funding aspects of computer science tend to depend on whether a department formed with a mathematical emphasis or with an engineering emphasis. Computer science departments with a mathematics emphasis and with a numerical orientation consider alignment computational science. Both types of departments tend to make efforts to bridge the field educationally if not across all research.

Computer science education

Some universities teach computer science as a theoretical study of computation and algorithmic reasoning. These programs often feature the theory of computation, analysis of algorithms, formal methods, concurrency 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.

See also

References

  1. ^ "Computer science is the study of information" New Jersey Institute of Technology, 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. Retrieved 2006-09-18. 
  7. ^ "Science Museum - Introduction to Babbage". http://www.sciencemuseum.org.uk/on-line/babbage/index.asp. Retrieved 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 2006-05-04. 
  9. ^ "IBM Punch Cards in the U.S. Army". http://www.pattonhq.com/ibm.html. Retrieved 2006-09-24. 
  10. ^ The Association for Computing Machinery (ACM) was founded in 1947.
  11. ^ http://www.cl.cam.ac.uk/conference/EDSAC99/statistics.html
  12. ^ Computer science pioneer Samuel D. Conte dies at 85 July 1, 2002
  13. ^ a b Levy, Steven (1984). Hackers: Heroes of the Computer Revolution. Doubleday. ISBN 0-385-19195-2. 
  14. ^ a b David Kahn, The Codebreakers, 1967, ISBN 0-684-83130-9.
  15. ^ a b http://www.cis.cornell.edu/Dean/Presentations/Slides/bgu.pdf
  16. ^ Constable, R.L. (March 2000) (PDF). Computer Science: Achievements and Challenges circa 2000. http://www.cs.cornell.edu/cis-dean/bgu.pdf. 
  17. ^ Abelson, H.; G.J. Sussman with J. Sussman (1996). Structure and Interpretation of Computer Programs (2nd 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." 
  18. ^ Black box traders are on the march The Telegraph, August 26, 2006
  19. ^ a b Computing Sciences Accreditation Board (28 May 1997). "Computer Science as a Profession". http://www.csab.org/comp_sci_profession.html. Retrieved 2008-09-01. 
  20. ^ 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. 
  21. ^ Computer Sciences Accreditation Board
  22. ^ Clay Mathematics Institute P=NP
  23. ^ Communications of the ACM 1(4):p.6
  24. ^ Communications of the ACM 2(1):p.4
  25. ^ IEEE Computer 28(12):p.136
  26. ^ 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, .."

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Study guide

Up to date as of January 14, 2010
(Redirected to School:Computer science article)

From Wikiversity

Contents

Welcome to the School of Computer science!
Part of Engineering and Technology.
The School of Computer Science is heavily integrated with the School of Mathematics

Computer science, or computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems. Computer science has many 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 problems. 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 languages to solve specific computational problems.

Note: more than one Wikiversity school can 'contain' departments that are 'contained' by "Topic:Computer Science"; schools should cooperate to develop the departments that they have in common. No turf wars should be fought over "ownership" of departments. See: Naming conventions.

Divisions and Departments

The Wikiversity School of Computer Science is still in its formative stages.

If you would like to help, please familiarize yourself with the following:

Participate!

Major divisions

Major divisions may include higher level generalized topics such as Topic:Computer Programming or Topic:Computer Architecture. Please discuss

Specialized departments

Specialized departments may include fields of interest and specialized topics such as Topic:Artificial Intelligence, Topic:Databases or Topic:Operating Systems. These fields might be organized more effectively if the Computer Science Portal can be improved and aligned with CS programs in academia at large.

Browsing Category:Computer Science and its subcategories is a good place to see what we have so far.

See also Computer science program and participate in the main CS School discussion, with your ideas on how to better organize Wikiversity CS-related content.

Thank you for your patience!

Brainstormed listing

Note: The list of divisions and departments is tentative, and is already quite long.

Learning materials and learning projects

Please familiarize yourself with the naming conventions if you haven't already.

Suggested Starting Points

Study Guide

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There are currently a large number of dead Topic: links that refer to empty departments. Until these are populated with content, a list of learning projects that support a "standard" study program is being developed. As this list grows, these learning projects can be used to compose small, more focused programs for special interests.

Learning paths

Research projects

This feature of Wikiversity will be implemented later pending further discussion.

  • Proposed Learning project: Screensaver Research - List distributed computing research screensavers (like folding@home) for students to download and run in the background with the eventual goal of writing one purely for wikiversity.
    • Integration with existing Open Source code possible
Please see also http://en.wikiversity.org/wiki/Wikiversity_Distributed_Virtual_Supercomputer
  • Proposed Learning project: 3DTheater.org - 3D Framework and SDK for live or scripted networked 3D Video-Game quality Wikiversity events such as school plays, sporting events, class sessions or virtual social events. Any 3D renderable setting may be explored.[[[Wikiversity_Distributed_Virtual_Supercomputer]]] Any variation of live acting, scripted actor sequences or Artificial Intelligent natural language responses may be incorporated. Any new Virtual 3D Sport may be created to obey its own laws of physics. Any other conceivable (legal and ethical) use for this virtual space could be entertained. The aim of this project would be to raise the level of user configurability such that--like in these wiki pages--the browser can quickly become the author, rendering assets for our 3D virtual campus, and breaking new ground in the field of virtual technology.
    • Video games for education - Wikiversity initiatives related to the Federation of American Scientists report on the National Summit on Educational Games.
  • Proposed Learning project: Remote Learning Development - We are computer scientists (or aspiring to be ones), so I think it would be interesting to have a practical learning project. This could integrate text, video and voice for either peer to peer or group work. I see this as having interest not just to our area, but to all of Wikiversity and maybe even other institutions.
  • Proposed Wikiversity:Sandbox Server: A "sandbox" for testing Computer Programming projects, server administration practice aimed at facilitating enhanced Internet Audio and Video activities, routing node for the Wikiversity Distributed Virtual Supercomputer and a variety of other CS related research projects and learning activities.
  • Proposed Original research: Markerless Tracking: A big challenge in Computer Vision is the recognition and tracking of real objects through sensor-data streams. This is needed for example in Robotics and Augmented Reality to gather informations about the surrounding. Computer Vision techniques gives good results if the objects are very simple and the sensor data is not too biased. Genrally spoken we have a huge amount of computer systems which works well on recognizing and tracking special markers wich could be distributed in the environment. The aim of this project would be to archive a general and widely accepted technique to perform markerless tracking and recognition of the real environment.

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Note: Wikiversity has "Wikiversity participants" who edit web pages. Participants of a school should state their goals and interests and get to work creating learning materials and learning projects. Wikiversity participants do not adopt titles. Just say what you are trying to do and then do it.

  • February 2, 2007 - CQ remembers to update CS news!
  • March 2, 2007 - aicra, joins! - I am working on.....
  • March 5, 2007 - Mattman059 joins! - I am working on Topic:Introductory Discrete Mathematics for Computer Science
  • March 19, 2007 - Vermishis joins! - I am working on organization, appearance, and uniformity. Throughout, the lessons, and departments.
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The histories of Wikiversity pages indicate who the active participants are. If you are an active participant in this school, you can list your name here (this can help small schools grow and the participants communicate better; for large schools it is not needed).

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  • Karimarie 15:03, 25 September 2006 (UTC) (Network and System Administration)
  • Draicone (talk) (Computer science, coding, media)
  • bakert (talk) (The Art of Computer Programming by Donald Knuth)
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  • CQ (Computer science) (interfaces, media...)
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  • Mariehuynh 09:10, 15 October 2006 (UTC)
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  • Martin Schoeberl (Computer Architecture)
  • doom777 (Higher language Programming)
  • User:Ragpicker(Computer Science)
  • Rahul K( IT security consultant )
  • AustinSmith (Database, Web Applications, Development Theory)
  • Freeman (Machine learning, Data mining) - 22:08, 15 December 2006
  • RISHICHATURVEDI (Computer Science, IET DAVV-INDORE) - 16:00, 19 December 2006
  • owl3638 (Computer Science) - 16:00, 29 December 2006
  • Sterling (Software Engineering: Modelling) - 5 Jan 2007
  • Cio (Computer Science: Programming) - 15 Jan 2007
  • Whisperer 21:20, 29 January 2007 (UTC) (Computer Science: System design and software development, programming(Java, C++))
  • Xenon (Server Admin, Tech Support, Web Consulting etc) - 7th Feb 2007
  • Zorg (Computer Science) - 10 Feb 2007
  • Simon alfie 13:18, 26 February 2007 (UTC) (Software engineer, BSc Computer Science)
  • Crazy LinuxMAN(Basic Linux, Computer Science ,PPC64 ,CELL)
  • aicra 15:58, 2 March 2007 (GNU/Linux, Computer Science, Software Freedom, Embedded)
  • Mattman059 5 March 2007 (Computer Science, Mathematics, Programming(C++,VB,TeX)
  • NDCompuGeek 11:04, 11 March 2007 (UTC) {CS, IT, CTI, DB, DBM, C, C++, C#, VC++, VB, Apple architecture, AMD architecture, MCSE, MCP....)
  • Vermishis 23:16, 19 March 2007 (UTC)(Organization and Interface)
  • Amit Mahajan 19 April March 2007 (Computer Science, Operating System,Embedded System, Programming(C++,C,C#),Scripting(Tcl,Perl)
  • Rizzy (Computer Science, OOP, Software Engineering, Web Development)
  • [[User:raghu/raghunandanan] (Computer Science, programming,webdesign)raghunandanan 04:57, 9 May 2007 (UTC)
  • Gamersedge (Computer Science, tech support enrichment)
  • Zchenyu (Java)
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  • Charles Mwiyeretsi (Computer Science, Programming and alil' hack1n9!)
  • Cjermain 01:41, 23 December 2007 (UTC) (Web Development(PHP, HTML, CSS, XML, Javascript, AJAX), Programming(C++, Java), Database Structures(MySQL, PostgreSQL))
  • Shirleyom 13:49, 8 March 2008 (UTC) (Computer Science)
  • Jekrox 10:16, 22 April 2008 (UTC)
  • Zoltek Learning HTML, hobby programmer
  • Grovermj 11:04, 28 August 2008 (UTC) Uni student, hope to contribute if I can find the motivation :)
  • AFriedman--also involved in the Departments of Neuroscience and Life Sciences; I conduct research in this field on Wikiversity (see my userpage)
  • Kinkydarkbird (Theoretical Computer Science, Complexity Theory, &c.)
  • Koolanu123 05:07, 15 February 2009 (UTC)anu123{comp sci,KSJC coll)

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Up to date as of January 23, 2010
(Redirected to Wikibooks:Computer science bookshelf article)

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Bookshelves

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Sparse text 00%.svg Developing text 25%.svg Maturing text 50%.svg Developed text 75%.svg Comprehensive text: 100%.svg

This bookshelf covers books about computer science - that is, books on software design, computer programming, and the theory of computation. See also Category:Computer science

Edit this list

The following is a list of all computer-related bookshelves:

  • The computer science bookshelf contains books on computer science (e.g. algorithms).
  • The computer software bookshelf contains books about software and operating systems (e.g. OpenOffice, Linux).
  • The programming languages bookshelf contain books about programming languages (e.g. C++, PHP)
  • The domain-specific languages bookshelf contains books about document programming languages (e.g. LaTeX, XML).
  • The information technology bookshelf contains books about hardware, certification, and history and development of information technologies.
  • The electronic games bookshelf contains books about computer games.

Contents

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General topics

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Theory

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Networking

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Programming

Programming languages

MULTI PARADIGMAda Programming Development stage: 75% (as of Jul 27, 2005)C++Common Lisp Development stage: 25% (as of Feb 01, 2005)Objective-C Development stage: 25% (as of Jan, 01 0000)Perl Development stage: 50% (as of Jan, 01 0000)Python Development stage: 50% (as of Jan, 01 0000)Tcl Development stage: 75% (as of Oct, 10 2005)Visual Basic Development stage: 50% (as of Oct 24, 2005)JavaScript Development stage: 50% (as of Nov 04, 2005)IMPERATIVEBourne Shell Scripting Development stage: 50% (as of October 10, 2005)CFortran Development stage: 25% (as of Sep, 09 2005)PHP Development stage: 75% (as of Oct, 31 2005)Icon Development stage: 25% (as of Jan, 01 0000)QBasic Development stage: 25% (as of Jan, 01 0000)ActionScript Development stage: 25% (as of Jan, 18 2007)Turing Development stage: 25% (as of Jan, 01 0000)DECLARATIVEApache Ant - Development stage: 75% (as of Feb 26, 2007)(Feb 26, 2007)XForms - Development stage: 75% (as of Feb 26, 2007)(Feb 26, 2007)OBJECT ORIENTEDC# Programming Development stage: 50% (as of May 9, 2007)Delphi Programming Development stage: 25% (as of August 1, 2008)Java Programming Development stage: 25% (as of Nov 23, 2005)Ruby Development stage: 25% (as of Jan, 01 0000)Visual Basic .NET Development stage: 25% (as of Oct, 30, 2005)Objective-JLOGICProlog Development stage: 50% (as of Jan, 01 0000)FUNCTIONALErlang Development stage: 50% (as of Aug, 20 2008)Haskell Development stage: 50% (as of Jun, 18 2006)ASSEMBLY LANGUAGESx86 Assembly Development stage: 50% (as of {{{2}}})MIPS Assembly Development stage: 25% (as of {{{2}}})SPARC Assembly Development stage: 25% (as of {{{2}}})360 Assembly Development stage: 25% (as of {{{2}}})

(edit template)
All Programming language books...
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TEXT PROCESSINGAWK Development stage: 00% (as of Oct 10, 2005)Regular Expressions Development stage: 00% (as of Jun 2, 2006)MARKUPCSS – HTML – XHTML – XForms Development stage: 50% (as of Sep, 13 2006) – XML: Managing Data Exchange — CONFIGURATION MANAGEMENT – Ant- Development stage: 25% (as of Oct, 05 2005)TYPESETTINGLaTeXPostScript FAQTeXHARDWARE PROGRAMMINGProgrammable LogicDATABASE – MySQL – SQL – XQuery

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Computational Intelligence

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Human Computer Interaction

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Software Design

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Embedded Systems

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Computer science is the science of how to treat information. There are many different areas in computer science. Some of the areas consider problems in a more abstract way. Some areas need special machines, called computers. A person who works with computers will often need math, science, and logic in order to make and use computers.

Contents

Common tasks for a computer scientist

Asking questions

This is so that they can find new and easier ways to do things.

Asking the right question

Computers can do some things easily (for example: simple math, or sorting out a list of names from A-to-Z). Computers cannot do some things, though. Computers cannot answer questions when there is not enough information, or when there is no real answer. Also, computers may take too much time to finish long tasks. For example, it may take too long to find the shortest way through all of the towns in the USA - so instead a computer will try to make a close guess. A computer will answer these simpler questions much faster.

Answering the question

Algorithms are ways to solve problems or do things. Think about playing cards, for example. A computer scientist wants to sort the cards. First he wants to sort them out by color. Then he wants to order them by number (2, 3, 4, 5, 6, 7, 8, 9, 10, Jack, Queen, King, and Ace). The computer scientist may see different ways to sort the playing cards. He must now think about of how he will do it. When he decides, he has created an algorithm. After making the algorithm, the scientist needs to test whether the algorithm always does what it should. Then, the scientist can see how well his program sorts the cards.

A simple but very slow algorithm could be: drop the cards, pick them up, and check whether they are sorted. If they are not, do it again. This method will work, but it will often take a very long time.

A person may do this better by looking through all the cards, finding the first card (2 of diamonds), and putting it at the start. After this, he looks for the second card, and so on. This works much faster, and does not need much space.

Computer science began during World War II and separated from the other sciences during the 1960's and 1970's. Now, computer science uses special methods of doing things, and has its own special words. It is related to electrical engineering, mathematics, and language science.

Computer science looks at the theoretical parts of computers. Computer engineering looks at the physical parts of computers (the parts that a person can touch), and software engineering looks at the use of computer programs and how to make them.

Parts of computer science

Central math

  • Boolean algebra (when something can only be true or false)
  • Computer numbering formats (how computers count)
  • Discrete mathematics (math with numbers a person can count)
  • Symbolic logic (clear ways of talking about math)

How an ideal computer works

Computer science at work

What computer science does

Other pages

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