• Systems science

Computer science

"Computer science is no more about computers than astronomy is about telescopes."

- attributed to Edsger Dijkstra

"Computer science is not as old as physics; it lags by a couple of hundred years. However, this does not mean that there is significantly less on the computer scientist's plate than on the physicist's: younger it may be, but it has had a far more intense upbringing!"

- Richard Feynman

Computer scientists study what programs can and cannot do (see computability and artificial intelligence), how programs should efficiently perform specific tasks (see algorithms), how programs should store and retrieve specific kinds of information (see data structures and data bases), and how programs and people should communicate with each other (see human-computer interaction and user interfaces).

Computer science has roots in electrical engineering, mathematics and linguistics. In the last third of the 20th century computer science has become recognized as a distinct discipline and has developed its own methods and terminology.

The first computer science department in the United States was founded at Purdue University in 1962. The University of Cambridge in England, among others, taught CS prior to this, however at the time, CS was seen as a branch of mathematics, and not a separate department. Cambridge claims to have the world's oldest taught qualification in computing. Most universities today have specific departments devoted to computer science.

The highest honor in computer science is the Turing Award.

Table of contents

1 Related fields 2 Major fields of importance for computer science 2.1 Mathematical foundations 2.2 Theoretical computer science 2.3 Hardware 2.4 Computer systems organization 2.5 Software 2.6 Data and information systems 2.7 Computing methodologies 2.8 Computer applications 2.9 Computing milieux 3 History 4 Prominent pioneers in computer science 5 See also 6 External links

Related fields

Computer science is closely related to several other fields. These fields overlap considerably, though important differences exist

• Information science is the study of data and information, including how to interpret, analyze, store, and retrieve it. Information science started as the foundation of scientific analysis of communication and databases.
• Computer programming or software development is the act of writing program code.
• Lexicography and specialized lexicography focus on the study of lexicographic reference works and include the study of electronic and Internet-based dictionaries.
• Linguistics is the study of languages, converging with computer science in such areas as programming language design and natural language processing.
• Software engineering emphasizes analysis, design, construction, and testing of useful software. Software engineering can include development methodologies (such as the waterfall model and extreme programming) and software project management.
• Information systems (IS) is the application of computing to support the operations of an organization: operating, installing, and maintaining the computers, software, and data.
  • Management information systems (MIS) is a subfield of information systems, that emphasizes financial and personnel management.
• Mathematics shares many techniques and topics with computer science, but is more general. In some sense, CS is the mathematics of computing.
• Logic is a formal system of reasoning, and studies principles that lay at the very basis of computing/reasoning machines, whether it be the hardware (digital logic) or software (verification, AI etc.) levels. The subfield of logic called computability logic provides a systematic answer to the fundamental questions about what and how can be computed.
• Computer engineering is the analysis, design, and construction of computer hardware.
• Information security is the analysis and implementation of information system security, including cryptography.

Mathematical foundations

• Boolean algebra
• Discrete mathematics
• Graph theory
• Information theory
• Symbolic logic
• Probability and Statistics

• Algorithmic information theory
• Computability theory
• Cryptography
• Formal semantics
• Theory of computation (or theoretical computer science)
  • analysis of algorithms and problem complexity
  • logics and meanings of programs
  • Mathematical logic and Formal languages
• Type theory

• Control structures and Microprogramming
• Arithmetic and Logic structures
• Memory structures
• input/output and Data communications
• Logic Design
• Integrated circuits
  • VLSI design
• Performance and reliability

• Computer architecture
• Computer networks
  • Distributed computing
• Performance of systems
• Computer system implementation

• Computer program and Computer programming
  • Parallel Programming
  • Program specification
  • Program verification
• Programming techniques
• Software engineering
  • Optimization
  • Software metrics
  • Configuration management and Software Configuration Management (SCM)
  • Structured programming
  • Object orientation
  • Design patterns
• Programming languages
• Operating Systems
• Compilers
  • Lexical analysis
  • Parsing

• Data structures
• Data storage representations
• Data encryption
• Data compression
• Data recovery
• Coding and Information theory
• Files
  • File formats
• Information systems
  • Databases
  • Information Storage and retrieval
  • Information Interfaces and Presentation

• Symbolic and Algebraic manipulation
• Artificial intelligence
• Computer graphics
• Image processing and computer vision
• Pattern recognition
  • Speech recognition
• Simulation and Modeling
• Document and text processing
• Digital signal processing

• Administrative data processing
  • Enterprise resource planning
  • Customer relationship management
• Mathematical software
  • Numerical analysis
  • Automated theorem proving
  • Computer algebra systems
• Physical science and Engineering
  • Computational chemistry
  • Computational physics
• Life and medical sciences
  • Bioinformatics
  • Computational Biology
  • Medical informatics
• Social and behavioral sciences
• Arts and Humanities
• Computer-aided engineering
• Robotics
• Human-computer interaction
  • Speech synthesis
  • Usability engineering

Computing milieux

• Computer industry
• History of computing hardware
• Computers and education
• Computers and society
  • Computer supported cooperative work
• Legal aspects of computing
  • Free software and Open Source
• Management of computing and Information systems
• Personal computing
• Computer and information security

• History of computing
• Origins of computer terms
• Early programming projects
• Computer science departments
• Timeline of algorithms

• Charles Babbage, Designed and built a prototype for a mechanical calculator; designed, but never built, the more powerful Analytical Engine.
• John Backus Invention of FORTRAN (Formula Translation), the first practical high-level programming language and the Backus-Naur form for describing formal language syntax.
• James W. Cooley and John W. Tukey The Fast Fourier Transform and its impact on scientific research.
• Ole-Johan Dahl and Kristen Nygaard, inventors of the proto-object oriented language SIMULA.
• Edsger Dijkstra for algorithms, Goto considered harmful, rigor, and pedagogy.
• C.A.R Hoare for the development of the formal language Communicating Sequential Processes (CSP) and Quicksort.
• Admiral Grace Murray Hopper, for doing pioneer work in the 1940s, one of the first to recognize the necessity for higher level programming languages, or what she termed automatic programming. She wrote the A-O compiler. Her ideas heavily influenced the COBOL language.
• Kenneth Iverson Inventor of APL, for his contribution to interactive computing.
• William Kahan for the IEEE floating-point standard. (Perhaps this reference should b
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