Computer Science

Computer science or computing science (abbreviated CS or compsci) designates the scientific and mathematical approach in information technology and computing. A computer scientist is a person who does work at a professional level in computer science and/or has attained a degree in computer science or a related field.

Its subfields can be divided into practical techniques for its implementation and application in computer systems and purely theoretical areas. Some, such as computational complexity theory, which studies fundamental properties of computational problems, are highly abstract, while others, such as computer graphics, emphasize real-world applications. Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to description of computations, while the study of computer programming itself investigates various aspects of the use of programming languages and complex systems, and human-computer interaction focuses on the challenges in making computers and computations useful, usable, and universally accessible to humans.

Contents  

1 History

1.1 Major achievements

2 Philosophy

2.1 Name of the field

3 Areas of computer science

3.1 Theoretical computer science

3.1.1 Theory of computation

3.1.2 Information and coding theory

3.1.3 Algorithms and data structures

3.1.4 Programming language theory

3.1.5 Formal methods

3.1.6 Concurrent, parallel and distributed systems

3.1.7 Databases and information retrieval

3.2 Applied computer science

3.2.1 Artificial intelligence

3.2.2 Computer architecture and engineering

3.2.3 Computer graphics and visualization

3.2.4 Computer security and cryptography

3.2.5 Computational science

3.2.6 Health Informatics

3.2.7 Information science

3.2.8 Software engineering

4 Academia

4.1 Conferences

4.2 Journals

5 Education

History

Main article: History of computer science

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. Wilhelm Schickard designed the first mechanical calculator in 1623, but did not complete its construction.[3] Blaise Pascal designed and constructed the first working mechanical calculator, the Pascaline, in 1642. Charles Babbage designed a difference engine and then a general-purpose Analytical Engine in Victorian times,[4] for which Ada Lovelace wrote a manual. Because of this work she is regarded today as the world's first programmer.[5] Around 1900, punched card machines were introduced.

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.[6] 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.[7][8] The world's first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of Cambridge Computer Laboratory in 1953. The first computer science degree program in the United States was formed at Purdue University in 1962.[9] Since practical computers became available, many applications of computing have become distinct areas of study in their own right.

Although many initially believed it was impossible that computers themselves could actually be a scientific field of study, in the late fifties it gradually became accepted among the greater academic population.[10] It is the now well-known IBM brand that formed part of the computer science revolution during this time. IBM (short for International Business Machines) released the IBM 704 and later the IBM 709 computers, which were widely used during the exploration period of such devices. "Still, working with the IBM [computer] was frustrating...if you had misplaced as much as one letter in one instruction, the program would crash, and you would have to start the whole process over again".[10] During the late 1950s, the computer science discipline was very much in its developmental stages, and such issues were commonplace.

Time has seen significant improvements in the usability and effectiveness of computer science technology. Modern society has seen a significant shift from computers being used solely by experts or professionals to a more widespread user base. Initially, computers were quite costly, and for their most-effective use, some degree of human aid was needed, in part by professional computer operators. However, as computers became widespread and far more affordable, less human assistance was needed, although residues of the original assistance still remained.

Major achievements

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

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

The start of the "digital revolution," which includes the current Information Age and the Internet.[12]

A formal definition of computation and computability, and proof that there are computationally unsolvable and intractable problems.

The concept of a programming language, a tool for the precise expression of methodological information at various levels of abstraction.

In cryptography, breaking the Enigma machine was an important factor contributing to the Allied victory in World War II.

Scientific computing enabled practical evaluation of processes and situations of great complexity, as well as experimentation entirely by software. It also enabled advanced study of the mind, and mapping of the human genome became possible with the Human Genome Project.[Distributed computing projects such as Folding@home explore 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.

Image synthesis, including video by computing individual video frames.[citation needed]

Simulation of various processes, including computational fluid dynamics, physical, electrical, and electronic systems and circuits, as well as societies and social situations (notably war games) along with their habitats, among many others. Modern computers enable optimization of such designs as complete aircraft. Notable in electrical and electronic circuit design are SPICE as well as software for physical realization of new (or modified) designs. The latter includes essential design software for integrated circuits.[citation needed]

Name of the field

The term "computer science" was first coined by the numerical analyst George Forsythe in 1961.[19] Despite its name, a significant amount of computer science does not involve the study of computers themselves. Because of this, several alternative names have been proposed. Certain departments of major universities prefer the term computing science, to emphasize precisely that difference. Danish scientist Peter Naur suggested the term datalogy, to reflect the fact that the scientific discipline revolves around data and data treatment, while not necessarily involving computers. The first scientific institution to use the term was the Department of Datalogy at the University of Copenhagen, founded in 1969, with Peter Naur being the first professor in datalogy. The term is used mainly in the Scandinavian countries. Also, in the early days of computing, a number of terms for the practitioners of the field of computing were suggested in the Communications of the ACM – turingineer, turologist, flow-charts-man, applied meta-mathematician, and applied epistemologist.[20] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.[21] The term computics has also been suggested.[22] In Europe, terms derived from "information" are often used, e.g. informatique (French), Informatik (German), informatica (Italy), informática (Spain, Portugal) or informatika (Slavic languages) are also used and have also been adopted in the UK (as in the School of Informatics of the University of Edinburgh).[23]

Renowned computer scientist Edsger Dijkstra once stated: "Computer science is no more about computers than astronomy is about telescopes."[24] 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, 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.[7] 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.[25]

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.

Areas of computer science

As a discipline, computer science spans a range of topics from theoretical studies of algorithms and the limits of computation to the practical issues of implementing computing systems in hardware and software.[26][27] CSAB, formerly called Computing Sciences Accreditation Board – which is made up of representatives of the Association for Computing Machinery (ACM), and the IEEE Computer Society (IEEE-CS)[28] – identifies four areas that it considers crucial to the discipline of computer science: theory of computation, algorithms and data structures, programming methodology and languages, and computer elements and architecture. In addition to these four areas, CSAB also identifies fields such as software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, computer-human interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.[26]

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Theoretical computer science

Main article: Theoretical computer science

The broader field of theoretical computer science encompasses both the classical theory of computation and a wide range of other topics that focus on the more abstract, logical, and mathematical aspects of computing.

Theory of computation

Main article: Theory of computation

According to Peter J. Denning, the fundamental question underlying computer science is, "What can be (efficiently) automated?"The study of the theory of computation is focused on answering fundamental questions about what can be computed and what amount of resources are required to perform those computations. In an effort to answer the first question, computability theory examines which computational problems are solvable on various theoretical models of computation. The second question is addressed by computational complexity theory, which studies the time and space costs associated with different approaches to solving a multitude of computational problems.

The famous "P=NP?" problem, one of the Millennium Prize Problems,[29] is an open problem in the theory of computation. P = NP ? GNITIRW-TERCES

Automata theory Computability theory Computational complexity theory Cryptography Quantum computing theory

Information and coding theory

Main articles: Information theory and Coding theory

Information theory is related to the quantification of information.This was developed by Claude E. Shannon to find fundamental limits on signal processing operations such as compressing data and on reliably storing and communicating data. Coding theory is the study of the properties of codes (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