History
The history of computer science predates the invention of the modern digital computer by many centuries. Machines for calculating fixed numerical tasks, such as the abacus, have existed since antiquity. Wilhelm Schickard built the first mechanical calculator in 1623.[4] Charles Babbage designed a difference engine in Victorian times (between 1837 and 1901)[5] helped by Ada Lovelace.[6] Around 1900 the IBM corporation sold punch-card machines.[7] 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.[8] 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 or International Business Machine as the company is officially termed 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). Obviously, during the period of 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 more a more widespread user base. Slowly computers became accepted as being the norm within everyday life, though this was not until the 1990s. 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
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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.<ref name="kahnbook" />
Despite its relatively short history as a formal academic discipline, computer science has made a number of fundamental contributions to science and society. These include:
- Applications within computer science
- A formal definition of computation and computability, and proof that there are computationally unsolvable and intractable problems.[9]
- The concept of a programming language, a tool for the precise expression of methodological information at various levels of abstraction[10]
- Applications outside of computing
- Sparked the Digital Revolution which led to the current Information Age[11]
- In cryptography, breaking the Enigma machine was an important factor contributing to the Allied victory in World War II.[12]
- Scientific computing enabled advanced study of the mind and mapping the human genome was possible with Human Genome Project.[11] Distributed computing projects like Folding@home explore protein folding.
Relationship with other fields
Computer science is frequently derided by the sentence "Any field which has to have 'science' in its name isn't one." This was placed in print by physicist Richard Feynman in his Lectures on Computation (1996) after his passing. He in no way meant to diminish the usefulness of the field.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 applying the datalogy term was DIKU, 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.[13] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.[14] Recently the term computics has been suggested.[15] Infomatik was a term used in Europe with more frequency.
In fact, the renowned computer scientist Edsger Dijkstra is often quoted as saying, "Computer science is no more about computers than astronomy is about telescopes." The design and deployment of computers and computer systems is generally considered the province of disciplines other than computer science. For example, the study of computer hardware is usually considered part of computer engineering, while the study of commercial computer systems 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[16] and others. However, there has been much cross-fertilization of ideas between the various computer-related disciplines. Computer science research has also often crossed into other disciplines, such as artificial intelligence, cognitive science, physics (see quantum computing), and linguistics.
Computer science is considered by some to have a much closer relationship with mathematics than many scientific disciplines.<ref name="Denning_cs_discipline" /> Early computer science was strongly influenced by the work of mathematicians such as Kurt Gödel and Alan Turing, and there continues to be a useful interchange of ideas between the two fields in areas such as mathematical logic, category theory, domain theory, and algebra.
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.[17]
The academic political and funding aspects of computer science tend to have roots as to whether a department in the US formed with either a mathematical emphasis or an engineering emphasis. In general, electrical engineering based CS departments have tended to succeed as computer science and/or engineering departments. CS 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 proofs 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 break down follows:Mathematical foundations
- Boolean logic and other ways of modeling logical queries; the uses and limitations of formal proof methods.
- 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.
- Foundations for data structures and searching algorithms.
- Formal analysis of the types of data, and the use of these types to understand properties of programs — especially program safety.
- Category theory provides a means of capturing all of math and computation in a single synthesis.
- The study of algorithms to solve problems stated in terms of geometry
- the study of set theory
Theory of computation
- Different logical structures for solving problems.
- 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 can not.
- Fundamental bounds (especially time and storage space) on classes of computations.
- Representation and manipulation of data using the quantum properties of particles and quantum mechanism.
Algorithms and data structures
- Time and space complexity of algorithms.
- Algorithms
- Formal logical processes used for computation, and the efficiency of these processes.
- The organization of and rules for the manipulation of data.
Programming languages and compilers
- Ways of translating computer programs, usually from higher level languages to lower level ones.
- A program that takes in as input a computer program and executes it.
- 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
- The theory and practice of simultaneous computation; data safety in any multitasking or multithreaded environment.
- 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.
- Computing using multiple concurrent threads of execution.
Software engineering
- Using ideas from algorithm theory to creatively design solutions to real tasks
- The practice of using a programming language to implement algorithms
- Mathematical approaches for describing and reasoning about software designs.
- The application of the scientific method to the understanding of arbitrary existing software
- The principles and practice of designing, developing, and testing programs, as well as proper engineering practices.
System architecture
- The design, organization, optimization and verification of a computer system, mostly about CPUs and Memory subsystem (and the bus connecting them).
- The implementation of computer architectures, in terms of descriptions of their specific electrical circuitry
- Systems for managing computer programs and providing the basis of a useable system.
Communications
- Algorithms and data structures for the creation, manipulation, storage, and transmission of digital audio recordings. Also important in voice recognition applications.
- Algorithms and protocols for reliably communicating data across different shared or dedicated media, often including error correction.
- Applies results from complexity, probability and number theory to invent and break codes.
Databases
- Data mining is the extracting of the relevant data from all the sources of data
- Study of algorithms for searching and processing information in documents and databases; closely related to information retrieval.
Artificial intelligence
- The implementation and study of systems that exhibit an autonomous intelligence or behaviour of their own.
- The study of digital organisms to learn about biological systems and evolution.
- Solving engines, such as used in Prolog, which produce steps to a result given a query on a fact and rule database.
- Algorithms for identifying three dimensional objects from one or more two dimensional pictures.
- Automated creation of a set of rules and axioms based on input.
- Automated understanding and generation of human language
- Algorithms for controlling the behavior of robots.
Visual rendering (or Computer graphics)
- Algorithms both for generating visual images synthetically, and for integrating or altering visual and spatial information sampled from the real world.
- Determining information from an image through computation.
Human-Computer Interaction
- The study of making computers and computations useful, usable and universally accessible to people, including the study and design of computer interfaces through which people use computers.
Scientific computing
- 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.
- Computational modelling of real minds
- Computational modelling of theoretical chemistry in order to determine chemical structures and properties
- Computational modelling of real brains
- Numerical simulations of large non-analytic systems
- Algorithms for the numerical solution of mathematical problems such as root-finding, integration, the solution of ordinary differential equations and the approximation/evaluation of special functions.
- Manipulation and solution of expressions in symbolic form, also known as Computer algebra.
Didactics of computer science / 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.Since 1960 experts of higher education, the pioneers of didactics of computer science, are developing guidelines and curricula recommendations.
Ten years later computer science has been a subject of secondary education. Didactics of computer science became also a study subject of teacher education.
At present, the educational aims of the subject computer science at schools are completely changing from programming of small imperative solutions to modelling, construction and deconstruction of complex and object oriented systems of computer science. But there is a big gap between the didactic needs and the published research results in this field, e. g.:
- The Educational Value of Informatics,
- Fundamental Ideas of Informatics,
- Didactic Systems of Informatics,
- Understanding of Informatics Systems,
- Educational Standards of Informatics,
- International Curricula.
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 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 disagreement over what the term "software engineering" actually means, and whether it is the same thing as programming.
- See Peter J. Denning, Great principles in computing curricula, Technical Symposium on Computer Science Education, 2004.
See also
- Main list: List of basic computer science topics
- Career domains 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
1. ^ "Computer science is the study of information" Department of Computer and Information Science, Guttenberg 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. ^ Nigel Tout (2006). Calculator Timeline. Vintage Calculator Web Museum. Retrieved on 2006-09-18.
5. ^ Science Museum - Introduction to Babbage. Retrieved on 2006-09-24.
6. ^ 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. Retrieved on 2006-05-04.
7. ^ IBM Punch Cards in the U.S. Army. Retrieved on 2006-09-24.
8. ^ Denning, P.J. (2000). "Computer Science: The Discipline". Encyclopedia of Computer Science.
9. ^ Constable, R.L. (March 2000). "Computer Science: Achievements and Challenges circa 2000".
10. ^ Abelson, H.; G.J. Sussman with J.Sussman (1996). Computer Science: Achievements and Challenges circa 2000, 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.
11. ^ [1]
12. ^ David Kahn, The Codebreakers, 1967, ISBN 0-684-83130-9.
13. ^ Communications of the ACM 1(4):p.6
14. ^ Communications of the ACM 2(1):p.4
15. ^ IEEE Computer 28(12):p.136
16. ^ Computer Language, Oct 1990
17. ^ Parnas, David L. (1998). "Software Engineering Programmes are not Computer Science Programmes". Annals of Software Engineering 6: 19–37. , 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, ....}."
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. ^ Nigel Tout (2006). Calculator Timeline. Vintage Calculator Web Museum. Retrieved on 2006-09-18.
5. ^ Science Museum - Introduction to Babbage. Retrieved on 2006-09-24.
6. ^ 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. Retrieved on 2006-05-04.
7. ^ IBM Punch Cards in the U.S. Army. Retrieved on 2006-09-24.
8. ^ Denning, P.J. (2000). "Computer Science: The Discipline". Encyclopedia of Computer Science.
9. ^ Constable, R.L. (March 2000). "Computer Science: Achievements and Challenges circa 2000".
10. ^ Abelson, H.; G.J. Sussman with J.Sussman (1996). Computer Science: Achievements and Challenges circa 2000, 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.
11. ^ [1]
12. ^ David Kahn, The Codebreakers, 1967, ISBN 0-684-83130-9.
13. ^ Communications of the ACM 1(4):p.6
14. ^ Communications of the ACM 2(1):p.4
15. ^ IEEE Computer 28(12):p.136
16. ^ Computer Language, Oct 1990
17. ^ Parnas, David L. (1998). "Software Engineering Programmes are not Computer Science Programmes". Annals of Software Engineering 6: 19–37. , 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, ....}."
- Association for Computing Machinery. 1998 ACM Computing Classification System. 1998.
- IEEE Computer Society and the Association for Computing Machinery. Computing Curricula 2001: Computer Science. December 15, 2001.
- Peter J. Denning. Is computer science science?, Communications of the ACM, April 2005.
- Donald E. Knuth. Selected Papers on Computer Science, CSLI Publications, Cambridge Univ. Press, 1996.
External links
- Computer science at the Open Directory Project
- Computer Science Directory - search engine and directory dedicated to computer science.
- Directory of free university lectures in Computer Science
- Collection of Computer Science Bibliographies
- Photographs of computer scientists (Bertrand Meyer's gallery)
Information is the result of processing, gathering, manipulating and organizing data in a way that adds to the knowledge of the receiver. In other words, it is the context in which data is taken.
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Computation is a general term for any type of information processing that can be represented mathematically. This includes phenomena ranging from simple calculations to human thinking.
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computer is a machine which manipulates data according to a list of instructions.
Computers take numerous physical forms. The first devices that resemble modern computers date to the mid-20th century (around 1940 - 1941), although the computer concept and various machines
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Computers take numerous physical forms. The first devices that resemble modern computers date to the mid-20th century (around 1940 - 1941), although the computer concept and various machines
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Computer graphics is a sub-field of computer science and is concerned with digitally synthesizing and manipulating visual content. Although the term often refers to three-dimensional computer graphics, it also encompasses two-dimensional graphics and image processing.
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In theoretical computer science, a computational problem is a mathematical object representing a question that computers might want to solve. For example, "given any number x, determine whether x is prime" is a computational problem.
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As a branch of the theory of computation in computer science, computational complexity theory investigates the problems related to the amounts of resources required for the execution of algorithms (e.g.
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Programming language theory (commonly known as PLT) is a branch of computer science that deals with the design, implementation, analysis, characterization, and classification of programming languages and programming language features.
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Computer programming (often shortened to programming or coding) is the process of writing, testing, and maintaining the source code of computer programs. The source code is written in a programming language.
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A programming language is an artificial language that can be used to control the behavior of a machine, particularly a computer. Programming languages, like natural languagess, are defined by syntactic and semantic rules which describe their structure and meaning respectively.
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Human–computer interaction (HCI), alternatively man–machine interaction (MMI) or computer–human interaction (CHI) is the study of interaction between people (users) and computers.
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public good is a good that is non-rival and non-excludable. This means that consumption of the good by one individual does not reduce the amount of the good available for consumption by others; and no one can be effectively excluded from using that good.
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The history of computer science began long before the modern discipline of computer science that emerged in the twentieth century. The progression, from mechanical inventions and mathematical theories towards the modern concepts and machines, formed a major academic field and the
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computer is a machine which manipulates data according to a list of instructions.
Computers take numerous physical forms. The first devices that resemble modern computers date to the mid-20th century (around 1940 - 1941), although the computer concept and various machines
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Computers take numerous physical forms. The first devices that resemble modern computers date to the mid-20th century (around 1940 - 1941), although the computer concept and various machines
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For the flat slab at the top of a column, see .
An abacus (plurals abacuses or abaci), also called a counting frame, is a calculating tool for performing arithmetical processes, often constructed as a wooden frame with beads
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Wilhelm Schickard (April 22 1592 – October 23 1635) was a German polymath who built one of the first automatic calculators in 1623.
Schickard was born in Herrenberg and educated at the University of Tübingen, receiving his first degree, B.A. in 1609 and M.A. in 1611.
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Schickard was born in Herrenberg and educated at the University of Tübingen, receiving his first degree, B.A. in 1609 and M.A. in 1611.
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Charles Babbage FRS (26 December 1791 – 18 October 1871) was an English mathematician, philosopher, and mechanical engineer who originated the idea of a programmable computer. Parts of his uncompleted mechanisms are on display in the London Science Museum.
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difference engine is a special-purpose mechanical digital calculator, designed to tabulate polynomial functions. Since logarithmic and trigonometric functions can be approximated by polynomials, such a machine is more general than it appears at first.
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Victorian era of the United Kingdom marked the height of the British Industrial Revolution and the apex of the British Empire. Although commonly used to refer to the period of Queen Victoria's rule between 1837 and 1901, scholars debate whether the Victorian period—as defined
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Augusta Ada King, Countess of Lovelace (December 10, 1815 – November 27, 1852), born Augusta Ada Byron, is mainly known for having written a description of Charles Babbage's early mechanical general-purpose computer, the analytical engine.
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International Business Machines Corporation
Public (NYSE: IBM )
Founded 1889, incorporated 1911
Headquarters Armonk, New York, USA
Key people Samuel J.
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Public (NYSE: IBM )
Founded 1889, incorporated 1911
Headquarters Armonk, New York, USA
Key people Samuel J.
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Computation is a general term for any type of information processing that can be represented mathematically. This includes phenomena ranging from simple calculations to human thinking.
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Science (from the Latin scientia, 'knowledge'), in the broadest sense, refers to any systematic knowledge or practice.[1] Examples of the broader use included political science and computer science, which are not incorrectly named, but rather named according to
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society is a grouping of individuals which is characterized by common interests and may have distinctive culture and institutions. Members of a society may be from different ethnic groups.
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Computation is a general term for any type of information processing that can be represented mathematically. This includes phenomena ranging from simple calculations to human thinking.
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Computability theory may refer to:
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- Recursion theory, a branch of mathematical logic, contemporarily called computability theory.
- Computability theory (computer science), locating basic questions of what is computable within the context of theoretical computer science.
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In computability theory the halting problem is a decision problem which can be stated as follows:
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- Given a description of a program and a finite input, decide whether the program finishes running or will run forever, given that input.
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A programming language is an artificial language that can be used to control the behavior of a machine, particularly a computer. Programming languages, like natural languagess, are defined by syntactic and semantic rules which describe their structure and meaning respectively.
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Cryptography (or cryptology; derived from Greek κρυπτός kryptós "hidden," and the verb γράφω gráfo "write" or λεγειν legein
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Enigma cipher machine
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- Enigma machine
- Enigma rotor details
- Cryptanalysis of the Enigma
- Cyclometer
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