Computer Science

Computer science is the study of the theory, experimentation, and engineering that form the basis for the design and use of computers . It is the scientific and practical approach to computation and Its Applications and the systematic study of the feasibility, structure, expression, and mechanization of the methodical procedures (or algorithms ) That underlie the acquisition, representation, processing, storage, communication of, and access To information . An alternate, more succinct definition of computer science is the study of automating algorithmic processes that scale. A computer scientist specializes in the computational systems. [1]

Its fields can be divided into a variety of theoretical and practical disciplines . Some fields, Such As computational complexity theory (explored qui The fundamental properties of computational and intractable problems), are highly abstract, while fields Such As compute EMPHASIZE real-world visual applications. Other fields still focus on challenges in computing. For example, programming language theory considers various approaches to the description of computation, while the study of computer programming Itself investigates various aspects of the use of programming language and complex systems .

History

The earliest foundations of what would become computer science predate the invention of the modern digital computer . Machines for calculating fixed numerical tasks such as abacushave existed since antiquity, aiding in computations. Further, algorithms for performing computations have existed since antiquity, even before the development of sophisticated computing equipment.

Wilhelm Schickard designed and constructed the first working mechanical calculator in 1623. [4] In 1673, Gottfried Leibniz Demonstrated a digital mechanical calculator, called Expired the Stepped Reckoner . [5] The binary number system can be used to calculate the binary number. In 1820, Thomas de Colmar launched the mechanical calculator industry [note 1] when he released his simplified arithmometer , which was the first calculating machine. Charles Babbage began his design of the first automatic mechanical calculator , his Difference Engine, in 1822, which eventually gave him the idea of ​​the first programmable mechanical calculator , his Analytical Engine . [6] He started developing this machine in 1834, and “in less than two years, he had sketched out many of the salient features of the modern computer “. [7] “A crucial step was the adoption of a punched card system derived from the Jacquard loom ” [7] making it infinitely programmable. [Note 2] In 1843, Ada Lovelace wrote, in an of the many notes she included, an algorithm to compute the Bernoulli numbers , which is considered to be the first computer program. [8] Around 1885, Herman Hollerith invented the tabulator , which used punched cards to process statistical information; Eventually his company became part of IBM . In 1937, one hundred Years After Babbage’s not dream, Howard Aiken Convinced IBM, qui Was making all kinds of punched card equipment and Was aussi in the calculator business [9] to Develop His giant programmable calculator, The ASCC / Harvard Mark I , based on Babbage’s Analytical Engine, which itself uses cards and a central computing unit. When the machine was finished, some hailed it as “Babbage’s dream come true”. [10]

During the 1940s, as new and more powerful computing machines were developed, the term computer came to mind rather than their human predecessors. [11] 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. [12] [13] The world’s first computer science degree program, the Cambridge Diploma in Computer Science , Began at the University of Cambridge Computer Laboratory in 1953.

Although many years ago it was impossible to calculate the number of students in the last fifty years. [15] [16] 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 [17] and later the IBM 709 [18] computers, which were widely used during the exploration period of such devices. “Still, working with the IBM [computer] was frustrating […] if you had misplaced the instruction, the program would crash, and you would have to start the whole process over again.” [15] During the late 1950s, the computer science discipline was very much in its developmental stages, and such issues were commonplace. [16]

Time-consuming and cost-effective computing technology . [19] Modern society has seen a significant shift in the users of computer technology, from use only by experts and professionals, to a near-ubiquitous user base. Initially, computers were quite costly, and some degree of human help was needed for efficient use-in part from professional computer operators. As computer adoption became more widespread and affordable, less human assistance was needed for common use.

See also: History of computing and History of informatics

contributions

The German military used the Enigma machine (shown here) during World War II for communications they wanted kept secret. The large-scale decryption of Enigma traffic at Bletchley Park was an important factor that contributed to Allied victory in WWII. [20]

DESPITE icts short history as a formal academic discipline, computer science HAS made a number of Fundamental contributions to science and society -in fact, along with electronics , it is a founding science of the current epoch of human history called Expired the Information Age and a driver of the Revolution Information , seen as the third major leap in human technological progress partner after the Industrial Revolution (1750-1850 CE) and the Agricultural Revolution (8000-5000 BC).

These contributions include:

  • The start of the ” digital revolution “, which includes the current Information Age and the Internet . [21]
  • A formal definition of computation and computability , and proof that there are computationally unsolvable and intractable problems. [22]
  • The concept of a programming language , a tool for the precise expression of methodological information at various levels of abstraction. [23]
  • In cryptography , breaking the Enigma code was an important factor contributing to the Allied victory in World War II. [20]
  • Scientific computing enabled practical evaluation of processes and situations of great complexity. It aussi enabled advanced study of the mind, and mapping of the human genome can est devenu with the Human Genome Project . [21] Distributed computing projects such as Folding @ home explores protein folding .
  • Algorithmic trading has increased the efficiency and liquidity of financial markets by using artificial intelligence , machine learning , and other statistical and numerical techniques on a large scale. [24] High frequency algorithmic trading can also exacerbate volatility . [25]
  • Computer graphics and computer-generated imagery have become ubiquitous in modern entertainment , especially in television , cinema , advertising , animation and video games . Even films that feature no explicit CGI are usually “filmed” now on digital cameras , or edited or post-processed using a digital video editor. [26] [27]
  • Simulation of various processes, including computational fluid dynamics , physical, electrical, and electronic systems and circuits, 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 ]
  • Artificial intelligence is becoming increasingly important as it gets more efficient and complex. There are many applications of AI, such as robotic vacuum cleaners . It is also present in video games and on the modern battlefield in drones, anti-missile systems, and squad support robots .
  • Human-Computer Interaction combines novel algorithms with design strategies that enable rapid human performance, low error rates, ease in learning, and high satisfaction. Researchers use ethnographic observation and automated data collection. Key innovations include direct manipulation , selectable web links, touchscreen designs, mobile applications, and virtual reality .

Etymology

ALTHOUGH first Proposed in 1956, [16] the term “computer science” appears in a 1959 paper in Communications of the ACM , [28] in qui Louis Fein Argues for the establishment of a Graduate School in Computer Science Analogous to the establishment of Harvard Business school in 1921, [29] justifying the name by arguing that, like management science , the subject is applied and interdisciplinary in nature, while having the typical characteristics of an academic discipline. [28] His efforts, and those of others such as numerical analyst George Forsythe , were rewarded: Starting with Purdue in 1962. [30] 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. [31] Certain departments of major universities prefer the term computing science , to emphasize precisely that difference. Danish scientist Peter Naur suggéré the term datalogy , [32] to Reflect the fact que la 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. An alternative term, also proposed by Naur, is data science ; This is now used for a distinct field of data analysis, including statistics and databases.

Also, in the early days of computing, a number of terms for the practitioners of the field of computing were proposed in the Communications of the ACM – turingineer , turologist , flow-charts-man , applied meta-mathematician , and applied epistemologist . [33] Three months later in the same journal, comptologist was suggested , followed next year by hypologist . [34] The term computics has also been suggested. [35] In Europe, terms derived from contracted translations of the term “automatic information” (eg “informazione automatica” in Italian) or “Information and mathematics” are Often used, eg computer (French) Informatik (German), informatica (Italian, Dutch ), Informática (Spanish, Portuguese), informatika ( Slavic languages and Hungarian ) or pliroforiki ( πληροφορική , which means informatics) in Greek . Similar words have been adopted in the UK (as in the School of Informatics of the University of Edinburgh ). [36] “In the U.

A folkloric quotation, often attributed to-but not least formulated by Edsger Dijkstra , states that “computer science is no more about computers than astronomy is about telescopes.” [Note 3] The design and deployment of computers and computer systems is considered the province of disciplines other than computer science. For example, the study of computer hardware is often 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 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. [12] Early computer science was strongly influenced by the work of mathematicians such as Kurt Gödel and Alan Turing , and there continued to be a useful interchange of ideas between the two fields in areas such as mathematical logic , category theory , domain theory , and Algebra . [16]

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. [38] David Parnas , a computations of the computations of the computations and the computations To achieve practical goals, making the complementary disciplines. [39]

The academic, political, and financial aspects of computer science tends to depend 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.

Philosophy

A number of computer scientists have argued for the distinction of three separate paradigms in computer science. Peter Wegner argued that these are paradigms of science, technology, and mathematics. [40] Peter Denning’sworking group argued that they are theory, abstraction (modeling), and design. [41] Amnon H. Eden describes them as the “rationalist paradigm” (which treats computer science as a branch of mathematics, which is prevalent in theoretical computer science, and mainly employs deductive reasoning ) found in engineering approaches, Most prominently in software engineering ), and the “scientific paradigm” (Which approaches computer-related artifacts from the empirical perspective of natural sciences , identifiable in some branches of artificial intelligence ). [42]

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 computing systems in hardware and software. [43] [44] CSAB , formerly called Expired Computing Sciences Accreditation Board -which is made up of Representatives of the Association for Computing Machinery (ACM) and the IEEE Computer Society (IEEE CS) [45] -identifies oven That It considers areas 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, computational computing, human-computer interaction, computer graphics, operating systems, and numerical and symbolic computation. Being important areas of computer science. [43]

Theoretical computer science

Theoretical Computer Science is mathematical and abstract in spirit, but it derives its motivation from practical and everyday computation. Its aim is to understand the nature of computations and, as a consequence of this understanding, to provide more efficient methodologies. All papers introducing or studying mathematical, logic and formal concepts and methods are welcome, provided that their motivation is clearly drawn from the field of computing .

Theory of computation

According to Peter Denning , the fundamental question underlying computer science is, “What can be (efficiently) automated?” [12] Theory of computations is focused on answering fundamental questions about what can be computed and what amount of resources are required to perform those computations. In an attempt 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 multitude of computational problems.

The famous P = NP? Problem, one of the Millennium Prize Problems , [46] is an open problem in the theory of computation.

Information and coding theory

Information theory is related to the quantification of information. This was developed by Claude Shannon to find fundamental limits on signal processing operations such as compressing data and reliably storing and communicating data. [47] Coding theory is the study of the properties of codes (systems for converting information from one form to another) and their fitness for a specific application. Codes are used for data compression , cryptography , error detection and 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

Algorithms and data structures is the study of commonly used computational methods and their computational efficiency.

Programming language theory

Programming language theory is a branch of computer science that deals with the design, implementation, analysis, characterization and classification of programming languages and their individual features . It falls within the discipline of computer science, both depending on and affecting mathematics , software engineering , and linguistics . It is an active research area, with numerous dedicated academic journals.

Formal methods

Formal methods are a Particular kind of mathematically technology based for the specification , development and verification of software and hardware systems. The use of formal methods for software and hardware design is motivated by the expectation that, in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design. They form an important theoretical underpinning for software engineering, especially where safety is involved. Formal methods are a useful adjunct to software testing. For industrial use, tool support is required. HOWEVER, the high cost of using formal methods means clustering That They Are usually only used in the development of high-integrity and life-critical systems , Where safety or security is of Utmost importance. Formal methods for the application of a fairly broad variety of theoretical computer science fundamentals, in particular logic calculi, formal languages , automata theory , and program semantics , but also type systems and algebraic data types in software and hardware specification and verification.

Applied computer science

Applied computer science and computer science.

Artificial Intelligence

Artificial Intelligence (AI) aims to or is required to synthesize the goal-orientated processes, such as solving, decision-making, environmental adaptation, learning and communication. From its origins in cybernetics and in the Dartmouth Conference (1956), artificial intelligence research has been necessarily cross-disciplinary, drawing on areas of expertise such as applied mathematics , symbolic logic , semiotics , electrical engineering , philosophy of mind , neurophysiology , and social Intelligence . AI is associated with the popular mind with robotic development , field goal the hand of Practical Application has-been as an embedded component in areas of software development , qui require computational understanding. The starting-point in the late 1940s was Alan Turing’s question “Can computers think?”, And the question remains effectively unanswered though the Turing test is still used to assess computer output on the scale of human intelligence. This paper examines the role of computer systems in the design and implementation of real-world applications. The starting-point in the late 1940s was Alan Turing’squestion “Can computers think?”, And the question remains effectively unanswered though the Turing test is still used to assess computer output on the scale of human intelligence. This paper examines the role of computer systems in the design and implementation of real-world applications. The starting-point in the late 1940s was Alan Turing’s question “Can computers think?”, And the question remains effectively unanswered though the Turing testis still used to assess computer output on the scale of human intelligence. This paper examines the role of computer systems in the design and implementation of real-world applications.

Computer architecture and engineering

Computer architecture, or digital computer organization, is the conceptual design and fundamental operational structure of a computer system. It focuses broadly on the way by which the central processing unit performs internally and accesses addresses in memory. [48] The use of computers as a source of computing and computing.

Computer performance analysis

Computer performance analysis is the study of work flowing through computers with the general goals of Improving throughput , controlling response time , using resources Efficiently, Eliminating bottlenecks , and Predicting performance under Anticipated peak loads. [49]

Computer graphics and visualization

Computer graphics is the study of digital visual contents, and involves synthesis and manipulation of image data. The study is related to the computer science of computer science, including computer vision , image processing , and computational geometry , and is heavily applied in the fields of special effects and video games .

Computer security and 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. Algorithms are based on their computational complexity.

Computational science

Computational science (or scientific computing ) is the field of study concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyze 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.

Computer networks

This branch of computer science aims to manage networks between computers worldwide.

Concurrent, parallel and distributed systems

Main articles: Concurrency (computer science) and Distributed computing

The computations are simultaneously and potentially interacting with each other. A number of mathematical models have been developed for general computing 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 among themselves to achieve a common goal.

Databases

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 modelsand query languages .

Human-computer interaction

Research that develops theories, principles, and guidelines for user interface designers, so they can create satisfactory user experiences with desktop, laptop, and mobile devices.

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. Software engineering deals with the organizing and analyzing of software-it does not just deal with the creation or manufacture of new software, but its internal maintenance and arrangement. Both computer applications and software engineers are projected to be among the fastest growing occupations from 2008 to 2018.

The great insights of computer science

The Philosopher of Computing Bill Rapaport noted three Great Insights of Computer Science : [50]

  • Gottfried Wilhelm Leibniz ‘s, George Boole ‘ s, Alan Turing ‘s, Claude Shannon ‘ s, and Samuel Morse ‘s insight: there are only two objects that a.
All the information about any computable problem can be represented using only 0 and 1 (or any other bistable pair that can flip-flop between two easily distinguishable states, such as “on / off”, “magnetized / de-magnetized” -voltage / low-voltage “, etc.).
See also: Digital physics
  • Alan Turing ‘s insight: there are only five actions that a computer has to perform in order to do “anything”.
Every algorithm can be expressed in a language for a computer consisting of only five basic instructions:

  • Move left one location;
  • Move right one location;
  • Read symbol at current location;
  • Print 0 at current location;
  • Print 1 at current location.
See also: Turing machine
  • Corrado Böhm and Giuseppe Jacopini ‘s insight: there are only three ways of combining these actions that are needed in order for a computer to do anything.
Only three rules are needed to combine any set of basic instructions into more complex ones:

  • Sequence : first do this, then do that;
  • Selection : IF such-and-such is the case, THEN do this, ELSE do that;
  • Repetition : WHILE such-and-such is the case DO this.
Note que le three rules of Boehm’s and Jacopini’s insight can be further Top simplified with the use of goto (qui means clustering it is more elementary than structured programming ).
See also: Elementary function arithmetic § Friedman’s grand conjecture

Academia

Further information: List of computer science conferences and Category: Computer science journals

Conferences are important events for computer science research. During these conferences, researchers from the public and private sectors present their recent work and meet. Unlike in most other academic fields, in computer science, the prestige of conference papers is greater than that of journal publications. [51] [52] One proposed explanation for this rapid development of this relatively new field requires rapid review and distribution of results, a task better handled by conferences than by journals. [53]

Education

Since computer science is a relatively new field, it is not as widely taught in schools and universities as other academic subjects. For example, in 2014, Code.org estimated that only 10 percent of high schools in the United States offered computer science education. [54] A 2010 report by Association for Computing Machinery (ACM) and Computer Science Teachers Association (CSTA) revealed that only 14 out of 50 states have adopted significant education standards for high school computer science. [55] However, computer science education is growing. [56] Some countries, such as Israel, New Zealand and South Korea, have already included computer science in their respective national secondary education curriculum. [57] [58] Several countries are following suit. [59]

In most countries, there is a significant gender gap in computer science education. For example, in the US about 20% of computer science degrees in 2012 were conferred to women. [60] This gender gap also exists in other Western countries. [61] However, in some parts of the world, the gap is small or nonexistent. In 2011, about half of all computer science degrees in Malaysia were conferred to women. [62] In 2001, women made up 54.5% of computer science graduates in Guyana . [61]

See also

  • Academic genealogy of computer scientists
  • Association for Computing Machinery
  • Computer Science Teachers Association
  • Informatics and Engineering informatics
  • List of academic computer science departments
  • List of computer scientists
  • List of publications in computer science
  • List of pioneers in computer science
  • List of unsolved problems in computer science
  • Outline of software engineering
  • Technology transfer in computer science
  • Turing Award

Notes

  1. Jump up^ In 1851
  2. Jump up^ “The introduction of punched cards into the new engine was important not only as a form of control of the drums, but because of the danger of introducing errors In setting the machine by hand; it was important also because it served to crystallize Babbage’s feeling that he had invented something really new, much more than a sophisticated calculating machine. ” Bruce Collier, 1970
  3. Jump up^ See the entry “Computer science” on Wikiquote for this history of this quotation.

References

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  2. Jump up^ “Charles Babbage Institute: Who Was Charles Babbage?” . Www.cbi.umn.edu . Retrieved 2016-12-28 .
  3. Jump up^ “Ada Lovelace | Babbage Engine | Computer History Museum” . Www.computerhistory.org . Retrieved 2016-12-28 .
  4. Jump up^ “Wilhelm Schickard – Ein Computerpionier” (PDF) .
  5. Jump up^ “A Brief History of Computing” .
  6. Jump up^ “Science Museum-Introduction to Babbage” . Archived from the original on 2006-09-08 . Retrieved 2006-09-24 .
  7. ^ Jump up to:a bAnthony Hyman (1982). Charles Babbage, pioneer of the computer .
  8. Jump up^ “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 ” . Archived from the original on February 10, 2006 . Retrieved 2006-05-04 .
  9. Jump up^“In this sense Aiken needed IBM,Bernard Cohen, p.44 (2000)
  10. Jump up^Brian Randell, p. 187, 1975
  11. Jump up^TheAssociation for Computing Machinery(ACM) was founded in 1947.
  12. ^ Jump up to:a b cDenning, Peter J. (2000). “Computer Science: The Discipline”(PDF) . Encyclopedia of Computer Science . Archived from the original(PDF) on 2006-05-25.
  13. Jump up^ “Some EDSAC statistics” . Cl.cam.ac.uk . Retrieved 2011-11-19 .
  14. Jump up^ “Computer science pioneer Samuel D. Conte dies at 85” . Purdue Computer Science. July 1, 2002 . Retrieved December 12, 2014 .
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  18. Jump up^ “IBM 709: a powerful new data processing system” (PDF) . Computer History Museum . Retrieved December 12, 2014 .
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  20. ^ Jump up to:a bDavid Kahn , The Codebreakers , 1967, ISBN 0-684-83130-9 .
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  22. Jump up^Constable, RL (March 2000). “Computer Science: Achievements and Challenges circa 2000” (PDF) .
  23. Jump up^ Abelson, H .; GJ 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 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.
  24. Jump up^ “Black box traders are on the market” . The Telegraph . August 26, 2006. Archived from the original on June 21, 2008.
  25. Jump up^“The Impact of High Frequency Trading on an Electronic Market”. Papers.ssrn.com. SSRN  1686004  . Doi : 10.2139 / ssrn.1686004 .
  26. Jump up^Maly, Timy. “How Digital Filmmakers Produced a Gorgeous Sci-Fi Movie on a Budget Kickstarter” . Wired . Retrieved November 24, 2015 .
  27. Jump up^Matthau, Charles. “How Tech Has Shaped Film Making: The Movie vs. Digital Debate Is Put To Rest” . Wired . Retrieved November 24, 2015 .
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  32. Jump up^Peter Naur (1966). “The science of datalogy”. Communications of the ACM . 9 (7): 485. doi : 10.1145 / 365719.366510 .
  33. Jump up^Weiss, EA; Corley, Henry PT “Communications of the ACM”. Communications of the ACM . 1 (4): 6. doi : 10.1145 / 368796.368802 .
  34. Jump up^Communications of the ACM 2 (1): p.4
  35. Jump up^IEEE Computer 28 (12): p.136
  36. Jump up^ Mounier-Kuhn,Computer Science in France, from the Second World War to the Calculation Plan. The Emergence of a Science, Paris, PUPS, 2010, ch. 3 & 4.
  37. Jump up^[1]
  38. Jump up^Tedre, M. (2011). “Computing as a Science: A Survey of Competing Viewpoints”. Minds and Machines . 21 (3): 361-387. Doi : 10.1007 / s11023-011-9240-4 .
  39. Jump up^Parnas, DL (1998). “Software engineering programs are not computer science programs”. Annals of Software Engineering . 6 : 19-37. Doi :10.1023 / A: 1018949113292 . , P. 19: “Rather than processing 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,
  40. Jump up^Wegner, P. (October 13-15, 1976). Research paradigms in computer science-Proceedings of the 2nd International Conference on Software Engineering . San Francisco, California, United States: IEEE Computer Society Press, Los Alamitos, CA.
  41. Jump up^Denning, PJ; Comer, DE; Gries, D .; Mulder, MC; Tucker, A .; Turner, AJ; Young, PR (Jan 1989). “Computing as a discipline”. Communications of the ACM . 32 : 9-23. Doi : 10.1145 / 63238.63239 .
  42. Jump up^Eden, AH (2007). “Three Paradigms of Computer Science” (PDF) . Minds and Machines . 17 (2): 135-167. Doi : 10.1007 / s11023-007-9060-8 .
  43. ^ Jump up to:a bComputing Sciences Accreditation Board (May 28, 1997). “Computer Science as a Profession” . Archived from the original on 2008-06-17 . Retrieved 2010-05-23 .
  44. Jump up^Committee on the Fundamentals of Computer Science: Challenges and Opportunities, National Research Council (2004). Computer Science: Reflections on the Field . National Academies Press. ISBN  978-0-309-09301-9 .
  45. Jump up^ “CSAB Leading Computer Education” . CSAB. 2011-08-03 . Retrieved 2011-11-19 .
  46. Jump up^Clay Mathematics InstituteP = NPArchivedOctober 14, 2013, at theWayback Machine.
  47. Jump up^ Collins, Graham (October 14, 2002). “Claude E. Shannon: Founder of Information Theory” . Scientific American . Retrieved December 12, 2014.
  48. Jump up^ Thisted, Ronald (April 7, 1997). “Computer Architecture” (PDF) . The University of Chicago.
  49. Jump up^Wescott, Bob (2013). The Every Computer Performance Book, Chapter 3: Useful laws . CreateSpace . ISBN  1482657759 .
  50. Jump up^ “What Is Computation?” . Buffalo.edu .
  51. Jump up^Meyer, Bertrand (April 2009). “Viewpoint: Research evaluation for computer science”. Communications of the ACM . 25 (4): 31-34. Doi :10.1145 / 1498765.1498780 .
  52. Jump up^Patterson, David (August 1999). “Evaluating Computer Scientists and Engineers for Promotion and Tenure” . Computing Research Association.
  53. Jump up^Fortnow, Lance (August 2009). “Viewpoint: Time for Computer Science to Grow Up” . Communications of the ACM . 52 (8): 33-35. Doi : 10.1145 / 1536616.1536631 .
  54. Jump up^ “Computer Science: Not Just An Elective Anymore” . Education Week . February 25, 2014.
  55. Jump up^ “Running On Empty” (PDF) . October 2010.
  56. Jump up^ “How to Teach Computational Thinking Stephen Wolfram Blog” . Blog.stephenwolfram.com . Retrieved 2016-09-16 .
  57. Jump up^ “A is for algorithm” . The Economist . April 26, 2014.
  58. Jump up^ “Computing at School International comparisons” (PDF) . Retrieved 20 July 2015 .
  59. Jump up^ “Adding Coding to the Curriculum” . New York Times . March 23, 2014.
  60. Jump up^ “IT gender gap: Where are the female programmers?” . Retrieved 20 July 2015 .
  61. ^ Jump up to:a b“IT gender gap: Where are the female programmers?” .
  62. Jump up^ “what is gender science” (PDF) . Retrieved 20 July 2015 .
  63. Learn to solve the Rubix Cube with the easiest method, memorizing only six algorithms.

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