Computer science (also called computing science) is the study of the theoretical foundations ofinformation andcomputation and their implementation and application incomputer systems. One well known subject classification system for computer science is theACM Computing Classification System devised by theAssociation for Computing Machinery.

Computer science can be described as all of the following:

• Academic discipline
• Science
  • Applied science

• Coding theory – Useful in networking, programming, system development, and other areas where computers communicate with each other.
• Game theory – Useful in artificial intelligence andcybernetics.
• Discrete mathematics – Study of discrete structures. Used in digital computer systems.
• Graph theory – Foundations for data structures and searching algorithms.
• Mathematical logic –Boolean logic and other ways ofmodeling logical queries; the uses and limitations of formal proof methods.
• Number theory – Theory of theintegers. Used incryptography as well as a test domain inartificial intelligence.

• Algorithms – Sequential and parallel computational procedures for solving a wide range of problems.
• Data structures – The organization and manipulation of data.

Outline of artificial intelligence

• Artificial intelligence – The implementation and study of systems that exhibit an autonomous intelligence or behavior of their own.
• Automated reasoning – Solving engines, such as used inProlog, which produce steps to a result given a query on a fact and rule database, andautomated theorem provers that aim to provemathematical theorems with some assistance from a programmer.
• Computer vision – Algorithms for identifying three-dimensional objects from a two-dimensional picture.
• Soft computing, the use of inexact solutions for otherwise extremely difficult problems:
  • Machine learning – Development of models that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and draw inferences from patterns in data.
  • Evolutionary computing – Biologically inspired algorithms.
• Natural language processing – Building systems and algorithms that analyze, understand, and generate natural (human) languages.
• Robotics – Algorithms for controlling the behavior of robots.

• Networking – Algorithms and protocols for reliably communicating data across different shared or dedicated media, often includingerror correction.
• Computer security – Practical aspects of securing computer systems and computer networks.
• Cryptography – Applies results from complexity, probability, algebra, and number theory to invent andbreak codes, and analyze the security ofcryptographic protocols.

• Computer architecture – The design, organization, optimization, and verification of a computer system, mostly aboutCPUs andMemory subsystems (and the bus connecting them).
• Operating systems – Systems for managing computer programs and providing the basis of a usable system.

• Computer graphics – Algorithms both for generating visual images synthetically, and for integrating or altering visual and spatial information sampled from the real world.
• Image processing – Determining information from an image through computation.
• Information visualization – Methods for representing and displaying abstract data to facilitate human interaction for exploration and understanding.

• Parallel computing – The theory and practice of simultaneous computation; data safety in any multitasking or multithreaded environment.
• Concurrency (computer science) – Computing using multiple concurrent threads of execution, devising algorithms for solving problems on various processors to achieve maximal speed-up compared to sequential execution.
• Distributed computing – 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.

Outline of databases

• Relational databases – theset theoretic and algorithmic foundation of databases.
• Structured Storage – non-relational databases such asNoSQL databases.
• Data mining – Study of algorithms for searching and processing information in documents and databases; closely related toinformation retrieval.

• Compiler theory – Theory ofcompiler design, based onAutomata theory.
• Programming language pragmatics – Taxonomy of programming languages, their strength, and weaknesses. Variousprogramming paradigms, such asobject-oriented programming.
• Programming language theory – Theory of programming language design
• Formal semantics – rigorous mathematical study of the meaning of programs.
• Type theory – Formal analysis of the types of data, and the use of these types to understand properties of programs — especially program safety.

• Computational science – constructingmathematical models andquantitative analysis techniques and using computers to analyze and solvescientific problems.
• Numerical analysis – Approximate numerical solution of mathematical problems such asroot-finding,integration, thesolution of ordinary differential equations; the approximation ofspecial functions.
• Symbolic computation – Manipulation and solution of expressions in symbolic form, also known asComputer algebra.
• Computational physics – Numerical simulations of large non-analytic systems
• Computational chemistry – Computational modelling of theoretical chemistry in order to determine chemical structures and properties
• Bioinformatics andComputational biology – The use of computer science to maintain, analyze, storebiological data and to assist in solving biological problems such asProtein folding, function prediction andPhylogeny.
• Computational neuroscience – Computational modelling ofneurophysiology.
• Computational linguistics
• Computational logic – Use of logic to perform or reason about computation
• Computational engineering – Field of algorithmic training

Outline of software engineering

• Formal methods – Mathematical approaches for describing and reasoning about software design.
• Software engineering – The principles and practice of designing, developing, and testing programs, as well as proper engineering practices.
• Algorithm design – Using ideas from algorithm theory to creatively design solutions to real tasks.
• Computer programming – The practice of using a programming language to implement algorithms.
• Human–computer interaction – The study and design of computer interfaces that people use.
• Reverse engineering – The application of the scientific method to the understanding of arbitrary existing software.

• Automata theory – Different logical structures for solving problems.
• Computability theory – What is calculable with the current models of computers. Proofs developed byAlan Turing and others provide insight into the possibilities of what may be computed and what may not.
  • List of unsolved problems in computer science
• Computational complexity theory – Fundamental bounds (especially time and storage space) on classes of computations.
• Quantum computing theory – Explores computational models involvingquantum superposition of bits.

• History of computer science
• List of pioneers in computer science
• History of Artificial Intelligence
• History of operating systems

• Computer Scientist
• Programmer (Software developer)
• Teacher/Professor
• Software engineer
• Software architect
• Software tester
• Hardware engineer
• Data analyst
• Interaction designer
• Network administrator
• Data scientist

• Data structure
• Data type
• Associative array andHash table
• Array
• List
• Tree
• String
• Matrix (computer science)
• Database

• Imperative programming/Procedural programming
• Functional programming
• Logic programming
• Declarative Programming
• Event-Driven Programming
• Object oriented programming
  • Class
  • Inheritance
  • Object

• Abstraction
• Big O notation
• Closure
• Compiler
• Cognitive science

• List of Computer Scientists
• Glossary of Computer Science

• Outlines of computing and engineering
• Outlines
• Computer science
• Computing-related lists

• Articles with short description
• Short description is different from Wikidata
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