The ETS® Major Field Test for Computer Science consists of 66 multiple-choice questions. Departmental Roster (PDF) â includes total scores and subscores (if applicable) of all. Download the FREE Major Field Tests Overview Webinar. Download Computer Science Torrent at TorrentFunk. We have 169 Computer Science eBooks torrents for you! Get YouTube Premium. MIT 6.00 Intro to Computer Science & Programming, Fall 2008 MIT OpenCourseWare. It also aims to help students, regardless of their major, to feel justifiably confident.
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Quiz on NI itroduction and History
This quiz is to judge your basic knowledge of computer science
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This exam covers the 40% of the evaluation of the 1st period. Enjoy !
If you are a Computer Science nerd anywhere around the globe who has vast knowledge about random or specific facts on the subject, try out this quiz. It will gauge how much knowledge you really have about Computer Science.
This quiz is equivalent to your final examination about the uses, benefits, and services offered by the Internet and the World Wide Web.This is an 'open notes' quiz. You can research on the Web if...
Be sure to enter your FIRST and LAST name below to get credit for taking the practice quiz.
A quiz for computer science.
Do you think you have the needed IQ for this quiz on Data Science Techniques? Scientists follow a particular pattern or techniques to get things done in the best possible way. Do you think you have the IQ to score beautifully...
It falls under the fold of computer science and it is broad enough to even be a standalone. So, what's up with it? How well do you think you'll perform if you were tested on it.
IB Computer Science Standard Level Paper 1May, 2006
The first book on computer science covers the basics of what a techie needs to know about computers and their operations. Do you think you have what it takes to tackle the final exam? Take up this quick test of computer...
Intro to Computer Science Html Quiz
Covers hardware, software, network, Apple, and Microsoft.
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COMPUTER SCIENCE
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Computer Science Exam 1
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Computer science deals with the theoretical foundations of computation and practical techniques for their application.
Computer science is the study of processes that interact with data and that can be represented as data in the form of programs. It enables the use of algorithms to manipulate, store, and communicatedigitalinformation. A computer scientist studies the theory of computation and the practice of designingsoftware systems.[1]
Computer science is no more about computers than astronomy is about telescopes.
Its fields can be divided into theoretical and practical disciplines. Computational complexity theory is highly abstract, while computer graphics emphasizes real-world applications. Programming language theory considers approaches to the description of computational processes, while computer programming itself involves the use of programming languages and complex systems. Humanâcomputer interaction considers the challenges in making computers useful, usable, and accessible.
History[edit]
Charles Babbage, sometimes referred to as the 'father of computing'.[2]
Ada Lovelace is often credited with publishing the first algorithm intended for processing on a computer.[3]
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 the abacus have existed since antiquity, aiding in computations such as multiplication and division. 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 the Stepped Reckoner.[5] He may be considered the first computer scientist and information theorist, for, among other reasons, documenting the binary number system. In 1820, Thomas de Colmar launched the mechanical calculator industry[note 1] when he released his simplified arithmometer, which was the first calculating machine strong enough and reliable enough to be used daily in an office environment. Charles Babbage started the 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, during the translation of a French article on the Analytical Engine, Ada Lovelace wrote, in one of the many notes she included, an algorithm to compute the Bernoulli numbers, which is considered to be the first published algorithm ever specifically tailored for implementation on a computer.[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 impossible dream, Howard Aiken convinced IBM, which was making all kinds of punched card equipment and was also in the calculator business[9] to develop his giant programmable calculator, the ASCC/Harvard Mark I, based on Babbage's Analytical Engine, which itself used 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 refer to the machines 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. In 1945, IBM founded the Watson Scientific Computing Laboratory at Columbia University in New York City. The renovated fraternity house on Manhattan's West Side was IBM's first laboratory devoted to pure science. The lab is the forerunner of IBM's Research Division, which today operates research facilities around the world.[12] Ultimately, the close relationship between IBM and the university was instrumental in the emergence of a new scientific discipline, with Columbia offering one of the first academic-credit courses in computer science in 1946.[13] Computer science began to be established as a distinct academic discipline in the 1950s and early 1960s.[14][15] The world's first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of CambridgeComputer Laboratory in 1953. The first computer science department in the United States was formed at Purdue University in 1962.[16] Since practical computers became available, many applications of computing have become distinct areas of study in their own rights.
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.[17][18] 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[19] and later the IBM 709[20] computers, which were widely used during the exploration period of such devices. 'Still, working with the IBM [computer] was frustrating [â¦] 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'.[17] During the late 1950s, the computer science discipline was very much in its developmental stages, and such issues were commonplace.[18]
Time has seen significant improvements in the usability and effectiveness of computing technology.[21] Modern society has seen a significant shift in the users of computer technology, from usage only by experts and professionals, to a near-ubiquitous user base. Initially, computers were quite costly, and some degree of humanitarian aid was needed for efficient useâin part from professional computer operators. As computer adoption became more widespread and affordable, less human assistance was needed for common usage.
Contributions[edit]
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.[22]
Despite its short history as a formal academic discipline, computer science has made a number of fundamental contributions to science and societyâin fact, along with electronics, it is a founding science of the current epoch of human history called the Information Age and a driver of the information revolution, seen as the third major leap in human technological progress after the Industrial Revolution (1750â1850 CE) and the Agricultural Revolution (8000â5000 BC).
These contributions include:
Etymology[edit]Computer Science Major Field Test Download Torrent Download
Although first proposed in 1956,[18] the term 'computer science' appears in a 1959 article in Communications of the ACM,[30]in which Louis Fein argues for the creation of a Graduate School in Computer Sciences analogous to the creation of Harvard Business School in 1921,[31] justifying the name by arguing that, like management science, the subject is applied and interdisciplinary in nature, while having the characteristics typical of an academic discipline.[30]His efforts, and those of others such as numerical analystGeorge Forsythe, were rewarded: universities went on to create such departments, starting with Purdue in 1962.[32] 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.[33] Certain departments of major universities prefer the term computing science, to emphasize precisely that difference. Danish scientist Peter Naur suggested the term datalogy,[34] 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. An alternative term, also proposed by Naur, is data science; this is now used for a multi-disciplinary 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 suggested in the Communications of the ACMâturingineer, turologist, flow-charts-man, applied meta-mathematician, and applied epistemologist.[35] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.[36] The term computics has also been suggested.[37]In Europe, terms derived from contracted translations of the expression 'automatic information' (e.g. 'informazione automatica' in Italian) or 'information and mathematics' are often used, e.g. informatique (French), Informatik (German), informatica (Italian, Dutch), informática (Spanish, Portuguese), informatika (Slavic languages and Hungarian) or pliroforiki (ÏληÏοÏοÏική, which means informatics) in Greek. Similar words have also been adopted in the UK (as in the School of Informatics of the University of Edinburgh).[38]'In the U.S., however, informatics is linked with applied computing, or computing in the context of another domain.'[39]
A folkloric quotation, often attributed toâbut almost certainly not first formulated byâEdsger 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 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 also often intersects other disciplines, such as philosophy, cognitive science, linguistics, mathematics, physics, biology, statistics, and logic.
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.[14] Early computer science was strongly influenced by the work of mathematicians such as Kurt Gödel, Alan Turing, Rózsa Péter and Alonzo Church 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.[18]
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.[40]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.[41]
The academic, political, and funding aspects of computer science tend to depend on whether a department formed with a mathematical emphasis or with an engineering emphasis. Computer science departments with a mathematics emphasis and with a numerical orientation consider alignment with computational science. Both types of departments tend to make efforts to bridge the field educationally if not across all research.
Philosophy[edit]
A number of computer scientists have argued for the distinction of three separate paradigms in computer science. Peter Wegner argued that those paradigms are science, technology, and mathematics.[42]Peter Denning's working group argued that they are theory, abstraction (modeling), and design.[43] Amnon H. Eden described 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), the 'technocratic paradigm' (which might be 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).[44]
Fields[edit]
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.[45][46]CSAB, formerly called Computing Sciences Accreditation Boardâwhich is made up of representatives of the Association for Computing Machinery (ACM), and the IEEE Computer Society (IEEE CS)[47]âidentifies 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, humanâcomputer interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.[45]
Theoretical computer science[edit]
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 computation and, as a consequence of this understanding, provide more efficient methodologies. All studies related to mathematical, logic and formal concepts and methods could be considered as theoretical computer science, provided that the motivation is clearly drawn from the field of computing.
Data structures and algorithms[edit]
Data structures and algorithms are the study of commonly used computational methods and their computational efficiency.
Theory of computation[edit]
According to Peter Denning, the fundamental question underlying computer science is, 'What can be (efficiently) automated?'[14] 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 multitude of computational problems.
The famous P = NP? problem, one of the Millennium Prize Problems,[48] is an open problem in the theory of computation.
Information and coding theory[edit]
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 on reliably storing and communicating data.[49]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.
Programming language theory[edit]
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[edit]
Formal methods are a particular kind of mathematically based technique 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, as 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 or security is involved. Formal methods are a useful adjunct to software testing since they help avoid errors and can also give a framework for testing. For industrial use, tool support is required. However, the high cost of using formal methods means 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 are best described as 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 to problems in software and hardware specification and verification.
Computer systems[edit]Computer architecture and computer engineering[edit]
Computer architecture, or digital computer organization, is the conceptual design and fundamental operational structure of a computer system. It focuses largely on the way by which the central processing unit performs internally and accesses addresses in memory.[50] The field often involves disciplines of computer engineering and electrical engineering, selecting and interconnecting hardware components to create computers that meet functional, performance, and cost goals.
Computer performance analysis[edit]
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.[51]Benchmarks provide a method of comparing the performance of various subsystems across different chip/system architectures.
Concurrent, parallel and distributed systems[edit]
Concurrency is a property of systems in which several computations are executing simultaneously, and potentially interacting with each other. A number of mathematical models have been developed for general concurrent computation including Petri nets, process calculi and the Parallel Random Access Machine model. A distributed system extends the idea of concurrency onto multiple computers connected through a network. Computers within the same distributed system have their own private memory, and information is often exchanged among themselves to achieve a common goal.
Computer Science Major Field Test Download Torrent FreeComputer networks[edit]
This branch of computer science aims to manage networks between computers worldwide.
Computer security and cryptography[edit]
Computer security is a branch of computer technology with an objective of protecting information from unauthorized access, disruption, or modification while maintaining the accessibility and usability of the system for its intended users. Cryptography is the practice and study of hiding (encryption) and therefore deciphering (decryption) information. Modern cryptography is largely related to computer science, for many encryption and decryption algorithms are based on their computational complexity.
Databases[edit]
A database is intended to organize, store, and retrieve large amounts of data easily. Digital databases are managed using database management systems to store, create, maintain, and search data, through database models and query languages.
Computer applications[edit]Computer graphics and visualization[edit]
Computer graphics is the study of digital visual contents and involves the synthesis and manipulation of image data. The study is connected to many other fields in computer science, including computer vision, image processing, and computational geometry, and is heavily applied in the fields of special effects and video games.
Humanâcomputer interaction[edit]
Research that develops theories, principles, and guidelines for user interface designers, so they can create satisfactory user experiences with desktop, laptop, and mobile devices.
Scientific computing[edit]
Scientific computing (or computational science) 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.
Artificial intelligence[edit]
Artificial intelligence (AI) aims to or is required to synthesize goal-orientated processes such as problem-solving, decision-making, environmental adaptation, learning, and communication found in humans and animals. 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 in the popular mind with robotic development, but the main field of practical application has been as an embedded component in areas of software development, which require computational understanding. The starting point in the late 1940s was Alan Turing's question 'Can computers think?', and the question remains effectively unanswered, although the Turing test is still used to assess computer output on the scale of human intelligence. But the automation of evaluative and predictive tasks has been increasingly successful as a substitute for human monitoring and intervention in domains of computer application involving complex real-world data.
Software engineering[edit]
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 softwareâit doesn't just deal with the creation or manufacture of new software, but its internal maintenance and arrangement.
Discoveries[edit]
The philosopher of computing Bill Rapaport noted three Great Insights of Computer Science:[52]
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