Glossary of computer science
|Part of a series on|
Most of the terms listed in Wikipedia glossaries are already defined and explained within Wikipedia itself. However, glossaries like this one are useful for looking up, comparing and reviewing large numbers of terms together. You can help enhance this page by adding new terms or writing definitions for existing ones.
This glossary of computer science terms is a list of definitions about computer science, its sub-disciplines, and related fields.
- Abstract data type – (ADT) is a mathematical model for data types, where a data type is defined by its behavior (semantics) from the point of view of a user of the data, specifically in terms of possible values, possible operations on data of this type, and the behavior of these operations. This contrasts with data structures, which are concrete representations of data, and are the point of view of an implementer, not a user.
- Abstract method – is one with only a signature and no implementation body. It is often used to specify that a subclass must provide an implementation of the method. Abstract methods are used to specify interfaces in some computer languages.
- Abstraction – In software engineering and computer science, abstraction is:
- the process of removing physical, spatial, or temporal details or attributes in the study of objects or systems in order to more closely attend to other details of interest; it is also very similar in nature to the process of generalization;
- the abstract concept-objects which are created by keeping common features or attributes to various concrete objects or systems of study — the result of the process of abstraction.
- Agent architecture – in computer science is a blueprint for software agents and intelligent control systems, depicting the arrangement of components. The architectures implemented by intelligent agents are referred to as cognitive architectures.
- Agent-based model – (ABM) is a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to introduce randomness.
- Aggregate function – In database management an aggregate function is a function where the values of multiple rows are grouped together to form a single value of more significant meaning or measurement such as a set, a bag or a list.
- Agile software development – is an approach to software development under which requirements and solutions evolve through the collaborative effort of self-organizing and cross-functional teams and their customer(s)/end user(s). It advocates adaptive planning, evolutionary development, early delivery, and continual improvement, and it encourages rapid and flexible response to change.
- Algorithm – is an unambiguous specification of how to solve a class of problems. Algorithms can perform calculation, data processing and automated reasoning tasks.
- Algorithm design – refers to a method or mathematical process for problem solving and engineering algorithms. The design of algorithms is part of many solution theories of operation research, such as dynamic programming and divide-and-conquer. Techniques for designing and implementing algorithm designs are also called algorithm design patterns, such as the template method pattern and decorator pattern.
- Algorithmic efficiency – is a property of an algorithm which relates to the number of computational resources used by the algorithm. An algorithm must be analyzed to determine its resource usage, and the efficiency of an algorithm can be measured based on usage of different resources. Algorithmic efficiency can be thought of as analogous to engineering productivity for a repeating or continuous process.
- American Standard Code for Information Interchange – abbreviated from American Standard Code for Information Interchange, is a character encoding standard for electronic communication. ASCII codes represent text in computers, telecommunications equipment, and other devices. Most modern character-encoding schemes are based on ASCII, although they support many additional characters.
- API – application programming interface.
- Application programming interface – (API) is a set of subroutine definitions, communication protocols, and tools for building software. In general terms, it is a set of clearly defined methods of communication among various components. A good API makes it easier to develop a computer program by providing all the building blocks, which are then put together by the programmer.
- Application software – (app or application for short) is computer software designed to perform a group of coordinated functions, tasks, or activities for the benefit of the user. Examples of an application include a word processor, a spreadsheet, an accounting application, a web browser, a media player, an aeronautical flight simulator, a console game or a photo editor. The collective noun application software refers to all applications collectively. This contrasts with system software, which is mainly involved with running the computer.
- Array data structure – or simply an array, is a data structure consisting of a collection of elements (values or variables), each identified by at least one array index or key. An array is stored such that the position of each element can be computed from its index tuple by a mathematical formula. The simplest type of data structure is a linear array, also called one-dimensional array.
- Artifact – is one of many kinds of tangible by-products produced during the development of software. Some artifacts (e.g., use cases, class diagrams, and other Unified Modeling Language (UML) models, requirements and design documents) help describe the function, architecture, and design of software. Other artifacts are concerned with the process of development itself—such as project plans, business cases, and risk assessments.
- Artificial intelligence – (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".
- ASCII – American Standard Code for Information Exchange.
- Assertion – In computer programming, an assertion is a statement that a predicate (Boolean-valued function, i.e. a true–false expression) is always true at that point in code execution. It can help a programmer read the code, help a compiler compile it, or help the program detect its own defects. For the latter, some programs check assertions by actually evaluating the predicate as they run and if it is not in fact true, an assertion failure, the program considers itself to be broken and typically deliberately crashes or throws an assertion failure exception.
- Associative array –
- Automata theory – is the study of abstract machines and automata, as well as the computational problems that can be solved using them. It is a theory in theoretical computer science and discrete mathematics (a subject of study in both mathematics and computer science). The word automata (the plural of automaton) comes from the Greek word αὐτόματα, which means "self-acting".
- Automated reasoning – is an area of computer science and mathematical logic dedicated to understanding different aspects of reasoning. The study of automated reasoning helps produce computer programs that allow computers to reason completely, or nearly completely, automatically. Although automated reasoning is considered a sub-field of artificial intelligence, it also has connections with theoretical computer science, and even philosophy.
- Bandwidth – is the maximum rate of data transfer across a given path. Bandwidth may be characterized as network bandwidth, data bandwidth, or digital bandwidth.
- Bayesian programming – is a formalism and a methodology for having a technique to specify probabilistic models and solve problems when less than the necessary information is available. Bayes’ Theorem is the central concept behind this programming approach, which states that the probability of something occurring in the future can be inferred by past conditions related to the event.
- Benchmark – is the act of running a computer program, a set of programs, or other operations, in order to assess the relative performance of an object, normally by running a number of standard tests and trials against it. The term benchmark is also commonly utilized for the purposes of elaborately designed benchmarking programs themselves.
- Best, worst and average case – best, worst, and average cases of a given algorithm express what the resource usage is at least, at most and on average, respectively. Usually the resource being considered is running time, i.e. time complexity, but it could also be memory or other resource. Best case is the function which performs the minimum number of steps on input data of n elements. Worst case is the function which performs the maximum number of steps on input data of size n. Average case is the function which performs an average number of steps on input data of n elements.
- Big data – is a term used to refer to data sets that are too large or complex for traditional data-processing application software to adequately deal with. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.
- Big O notation – is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. It is a member of a family of notations invented by Paul Bachmann, Edmund Landau, and others, collectively called Bachmann–Landau notation or asymptotic notation.
- Binary number – In mathematics and digital electronics, a binary number is a number expressed in the base-2 numeral system or binary numeral system, which uses only two symbols: typically 0 (zero) and 1 (one).
- Binary search algorithm – binary search, also known as half-interval search, logarithmic search, or binary chop, is a search algorithm that finds the position of a target value within a sorted array.
- Binary tree – is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. A recursive definition using just set theory notions is that a (non-empty) binary tree is a tuple (L, S, R), where L and R are binary trees or the empty set and S is a singleton set. Some authors allow the binary tree to be the empty set as well.
- Bioinformatics – is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques.
- Bit – (a portmanteau of binary digit) is a basic unit of information used in computing and digital communications. A binary digit can have only one of two values, and may be physically represented with a two-state device. These state values are most commonly represented as either a 0or1.
- Bit rate – In telecommunications and computing, bit rate (bitrate or as a variable R) is the number of bits that are conveyed or processed per unit of time.
- Blacklist – In computing, a blacklist or block list is a basic access control mechanism that allows through all elements (email addresses, users, passwords, URLs, IP addresses, domain names, file hashes, etc.), except those explicitly mentioned. Those items on the list are denied access. The opposite is a whitelist, which means only items on the list are let through whatever gate is being used. A greylist contains items that are temporarily blocked (or temporarily allowed) until an additional step is performed.
- BMP file format – also known as bitmap image file or device independent bitmap (DIB) file format or simply a bitmap, is a raster graphics image file format used to store bitmap digital images, independently of the display device (such as a graphics adapter), especially on Microsoft Windows and OS/2 operating systems.
- Boolean data type – is a data type that has one of two possible values (usually denoted true and false), intended to represent the two truth values of logic and Boolean algebra. It is named after George Boole, who first defined an algebraic system of logic in the mid 19th century. The Boolean data type is primarily associated with conditional statements, which allow different actions by changing control flow depending on whether a programmer-specified Boolean condition evaluates to true or false. It is a special case of a more general logical data type (see probabilistic logic)—logic need not always be Boolean.
- Boolean expression – is used expression in a programming language that produces a Boolean value when evaluated, that is one of true or false. A Boolean expression may be composed of a combination of the Boolean constants true or false, Boolean-typed variables, Boolean-valued operators, and Boolean-valued functions.
- Boolean algebra – In mathematics and mathematical logic, Boolean algebra is the branch of algebra in which the values of the variables are the truth values true and false, usually denoted 1 and 0 respectively. Instead of elementary algebra where the values of the variables are numbers, and the prime operations are addition and multiplication, the main operations of Boolean algebra are the conjunction and denoted as ∧, the disjunction or denoted as ∨, and the negation not denoted as ¬. It is thus a formalism for describing logical relations in the same way that elementary algebra describes numeric relations.
- Byte – is a unit of digital information that most commonly consists of eight bits, representing a binary number. Historically, the byte was the number of bits used to encode a single character of text in a computer and for this reason it is the smallest addressable unit of memory in many computer architectures.
- Booting- is starting up a computer or computer appliance until it can be used. It can be initiated by hardware such as a button press or by software command. After the power is switched on, the computer is relatively dumb and can read only part of its storage called read-only memory. There, a small program is stored called firmware. It does power-on self-tests and, most importantly, allows accessing other types of memory like a hard disk and main memory. The firmware loads bigger programs into the computer's main memory and runs it.
- Callback – also known as a "call-after" function, is any executable code that is passed as an argument to other code that is expected to call back (execute) the argument at a given time. This execution may be immediate as in a synchronous callback, or it might happen at a later time as in an asynchronous callback.
- Central processing unit – (CPU) is the electronic circuitry within a computer that carries out the instructions of a computer program by performing the basic arithmetic, logic, controlling and input/output (I/O) operations specified by the instructions. The computer industry has used the term "central processing unit" at least since the early 1960s. Traditionally, the term "CPU" refers to a processor, more specifically to its processing unit and control unit (CU), distinguishing these core elements of a computer from external components such as main memory and I/O circuitry.
- Character – In computer and machine-based telecommunications terminology, a character is a unit of information that roughly corresponds to a grapheme, grapheme-like unit, or symbol, such as in an alphabet or syllabary in the written form of a natural language.
- Cipher – In cryptography, a cipher (or cypher) is an algorithm for performing encryption or decryption—a series of well-defined steps that can be followed as a procedure.
- Class – In object-oriented programming, a class is an extensible program-code-template for creating objects, providing initial values for state (member variables) and implementations of behavior (member functions or methods). In many languages, the class name is used as the name for the class (the template itself), the name for the default constructor of the class (a subroutine that creates objects), and as the type of objects generated by instantiating the class; these distinct concepts are easily conflated.
- Class-based programming – or more commonly class-orientation, is a style of Object-oriented programming (OOP) in which inheritance occurs via defining classes of objects, instead of inheritance occurring via the objects alone (compare prototype-based programming).
- Class-orientation – is a style of Object-oriented programming (OOP) in which inheritance occurs via defining classes of objects, instead of inheritance occurring via the objects alone (compare prototype-based programming).
- Client – is a piece of computer hardware or software that accesses a service made available by a server. The server is often (but not always) on another computer system, in which case the client accesses the service by way of a network. The term applies to the role that programs or devices play in the client–server model.
- Cleanroom software engineering – is a software development process intended to produce software with a certifiable level of reliability. The cleanroom process was originally developed by Harlan Mills and several of his colleagues including Alan Hevner at IBM. The focus of the cleanroom process is on defect prevention, rather than defect removal.
- Closure – In programming languages, a closure (also lexical closure or function closure) is a technique for implementing lexically scoped name binding in a language with first-class functions. Operationally, a closure is a record storing a function[a] together with an environment.
- Cloud computing – is shared pools of configurable computer system resources and higher-level services that can be rapidly provisioned with minimal management effort, often over the Internet. Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a public utility.
- Code library – is a collection of non-volatile resources used by computer programs, often for software development. These may include configuration data, documentation, help data, message templates, pre-written code and subroutines, classes, values or type specifications. In IBM's OS/360 and its successors they are referred to as partitioned data sets.
- Coding – Computer programming is the process of designing and building an executable computer program for accomplishing a specific computing task. Programming involves tasks such as analysis, generating algorithms, profiling algorithms' accuracy and resource consumption, and the implementation of algorithms in a chosen programming language (commonly referred to as coding). The source code of a program is written in one or more programming languages. The purpose of programming is to find a sequence of instructions that will automate the performance of a task for solving a given problem. The process of programming thus often requires expertise in several different subjects, including knowledge of the application domain, specialized algorithms, and formal logic.
- Coding theory – is the study of the properties of codes and their respective fitness for specific applications. Codes are used for data compression, cryptography, error detection and correction, data transmission and data storage. Codes are studied by various scientific disciplines—such as information theory, electrical engineering, mathematics, linguistics, and computer science—for the purpose of designing efficient and reliable data transmission methods. This typically involves the removal of redundancy and the correction or detection of errors in the transmitted data.
- Cognitive science – is the interdisciplinary, scientific study of the mind and its processes. It examines the nature, the tasks, and the functions of cognition (in a broad sense). Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology.
- Comma-separated values – (CSV) file is a delimited text file that uses a comma to separate values. A CSV file stores tabular data (numbers and text) in plain text. Each line of the file is a data record. Each record consists of one or more fields, separated by commas. The use of the comma as a field separator is the source of the name for this file format.
- Compiler – is a computer program that transforms computer code written in one programming language (the source language) into another programming language (the target language). Compilers are a type of translator that support digital devices, primarily computers. The name compiler is primarily used for programs that translate source code from a high-level programming language to a lower level language (e.g., assembly language, object code, or machine code) to create an executable program.
- Compiler theory –
- Computability theory – also known as recursion theory, is a branch of mathematical logic, of computer science, and of the theory of computation that originated in the 1930s with the study of computable functions and Turing degrees. The field has since expanded to include the study of generalized computability and definability. In these areas, recursion theory overlaps with proof theory and effective descriptive set theory.
- Computation – is any type of calculation that includes both arithmetical and non-arithmetical steps and follows a well-defined model, for example an algorithm. The study of computation is paramount to the discipline of computer science.
- Computational biology –
- Computational chemistry – is a branch of chemistry that uses computer simulation to assist in solving chemical problems. It uses methods of theoretical chemistry, incorporated into efficient computer programs, to calculate the structures and properties of molecules and solids.
- Computational complexity theory – focuses on classifying computational problems according to their inherent difficulty, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm.
- Computational model – is a mathematical model in computational science that requires extensive computational resources to study the behavior of a complex system by computer simulation.
- Computational neuroscience – (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
- Computational physics –
- Computational science – (also scientific computing or scientific computation (SC)) is a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems. It is an area of science which spans many disciplines, but at its core it involves the development of models and simulations to understand natural systems.
- Computational steering –
- Computer – is a device that can be instructed to carry out sequences of arithmetic or logical operations automatically via computer programming. Modern computers have the ability to follow generalized sets of operations, called programs. These programs enable computers to perform an extremely wide range of tasks.
- Computer architecture – In computer engineering, computer architecture is a set of rules and methods that describe the functionality, organization, and implementation of computer systems. Some definitions of architecture define it as describing the capabilities and programming model of a computer but not a particular implementation. In other definitions computer architecture involves instruction set architecture design, microarchitecture design, logic design, and implementation.
- Computer data storage – often called storage or memory, is a technology consisting of computer components and recording media that are used to retain digital data. It is a core function and fundamental component of computers.:15–16
- Computer ethics – is a part of practical philosophy concerned with how computing professionals should make decisions regarding professional and social conduct.
- Computer graphics – are pictures and films created using computers. Usually, the term refers to computer-generated image data created with the help of specialized graphical hardware and software. It is a vast and recently developed area of computer science.
- Computer network – or data network, is a digital telecommunications network which allows nodes to share resources. In computer networks, computing devices exchange data with each other using connections (data links) between nodes. These data links are established over cable media such as wires or optic cables, or wireless media such as WiFi.
- Computer programming – is the process of designing and building an executable computer program for accomplishing a specific computing task. Programming involves tasks such as analysis, generating algorithms, profiling algorithms' accuracy and resource consumption, and the implementation of algorithms in a chosen programming language (commonly referred to as coding). The source code of a program is written in one or more programming languages. The purpose of programming is to find a sequence of instructions that will automate the performance of a task for solving a given problem. The process of programming thus often requires expertise in several different subjects, including knowledge of the application domain, specialized algorithms, and formal logic.
- Computer science – is the theory, experimentation, and engineering that form the basis for the design and use of computers. It involves the study of algorithms that process, store, and communicate digital information. A computer scientist specializes in the theory of computation and the design of computational systems.
- Computer scientist – is a person who has acquired the knowledge of computer science, the study of the theoretical foundations of information and computation and their application.
- Computer security –
- Computer vision –
- Concatenation –
- Concurrency –
- Continuation-passing style –
- Conditional –
- Control flow –
- Creative Commons –
- Cryptography –
- CSV – comma-separated values.
- Cyberbullying –
- Cyberspace –
- Data center – or data centre, is a dedicated space used to house computer systems and associated components, such as telecommunications and storage systems. It generally includes redundant or backup components and infrastructure for power supply, data communications connections, environmental controls (e.g. air conditioning, fire suppression) and various security devices.
- Database – is an organized collection of data, generally stored and accessed electronically from a computer system. Where databases are more complex they are often developed using formal design and modeling techniques.
- Data mining –
- Data science – is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining. Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, information science, and computer science.
- Data structure – is a data organization, management and storage format that enables efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.
- Data type – or simply type is an attribute of data which tells the compiler or interpreter how the programmer intends to use the data. Most programming languages support common data types of real, integer and boolean. A data type constrains the values that an expression, such as a variable or a function, might take. This data type defines the operations that can be done on the data, the meaning of the data, and the way values of that type can be stored. A type of value from which an expression may take its value.
- Debugging – is the process of finding and resolving defects or problems within a computer program that prevent correct operation of computer software or a system. Debugging tactics can involve interactive debugging, control flow analysis, unit testing, integration testing, log file analysis, monitoring at the application or system level, memory dumps, and profiling.
- Declaration – In computer programming, a declaration is a language construct that specifies properties of an identifier: it declares what a word (identifier) "means". Declarations are most commonly used for functions, variables, constants, and classes, but can also be used for other entities such as enumerations and type definitions. Beyond the name (the identifier itself) and the kind of entity (function, variable, etc.), declarations typically specify the data type (for variables and constants), or the type signature (for functions); types may also include dimensions, such as for arrays. A declaration is used to announce the existence of the entity to the compiler; this is important in those strongly typed languages that require functions, variables, and constants, and their types to be specified with a declaration before use, and is used in forward declaration. The term "declaration" is frequently contrasted with the term "definition", but meaning and usage varies significantly between languages.
- Digital data – in information theory and information systems, is the discrete, discontinuous representation of information or works. Numbers and letters are commonly used representations.
- Digital signal processing – (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency.
- Discrete event simulation –
- Disk storage –
- Distributed computing –
- Divide and conquer algorithm –
- DNS – Domain Name System.
- Documentation –
- Domain Name System –
- Double-precision floating-point format –
- Download –
- Edge device –
- Encryption –
- Event –
- Event-driven programming –
- Evolutionary computing –
- Executable –
- External documentation –
- Exception handling –
- Executable module –
- Expression –
- External library –
- Fault-tolerant computer system –
- Feasibility study –
- Filename extension –
- Filter (software) –
- Floating point arithmetic –
- For loop –
- Formal methods –
- Formal verification –
- Functional programming –
- Game theory –
- Garbage in, garbage out –
- GIGO – Garbage in, garbage out.
- GIF – Graphics Interchange Format.
- Gigabyte –
- Global variable –
- Graph theory –
- Hard problem – Computational complexity theory focuses on classifying computational problems according to their inherent difficulty, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm.
- Hash function – is any function that can be used to map data of arbitrary size to data of a fixed size. The values returned by a hash function are called hash values, hash codes, digests, or simply hashes. Hash functions are often used in combination with a hash table, a common data structure used in computer software for rapid data lookup. Hash functions accelerate table or database lookup by detecting duplicated records in a large file.
- Hash table – In computing, a hash table (hash map) is a data structure that implements an associative array abstract data type, a structure that can map keys to values. A hash table uses a hash function to compute an index into an array of buckets or slots, from which the desired value can be found.
- Heap – is a specialized tree-based data structure which is essentially an almost complete tree that satisfies the heap property: if P is a parent node of C, then the key (the value) of P is either greater than or equal to (in a max heap) or less than or equal to (in a min heap) the key of C. The node at the "top" of the heap (with no parents) is called the root node.
- Heapsort – is a comparison-based sorting algorithm. Heapsort can be thought of as an improved selection sort: like that algorithm, it divides its input into a sorted and an unsorted region, and it iteratively shrinks the unsorted region by extracting the largest element and moving that to the sorted region. The improvement consists of the use of a heap data structure rather than a linear-time search to find the maximum.
- Human-computer interaction – (HCI) researches the design and use of computer technology, focused on the interfaces between people (users) and computers. Researchers in the field of HCI both observe the ways in which humans interact with computers and design technologies that let humans interact with computers in novel ways. As a field of research, human–computer interaction is situated at the intersection of computer science, behavioral sciences, design, media studies, and several other fields of study.
- IDE – integrated development environment.
- Image processing –
- Imperative programming –
- Incremental build model –
- Information space analysis –
- Information visualization –
- Inheritance –
- Input/output –
- Insertion sort –
- Instruction cycle –
- Integer –
- Integrated development environment –
- Integration testing –
- Intellectual property –
- Intelligent agent –
- Interface –
- Internal documentation –
- Internet –
- Internet bot –
- Interpreter –
- Invariant –
- Iteration –
- Java –
- Library (computing) –
- Linear search –
- Linked list –
- Linker –
- List –
- Loader –
- Logic error –
- Logic programming –
- Machine learning –
- Machine vision –
- Mathematical logic –
- Matrix –
- Memory –
- Merge sort –
- Method –
- Methodology –
- Object –
- Object code –
- Object-oriented analysis and design –
- Object oriented programming –
- Open-source software –
- Operating system –
- Optical fiber –
- Pair programming –
- Parallel computing –
- Parameter –
- Peripheral –
- Postcondition –
- Precondition –
- Primary storage –
- Primitive data type –
- Priority queue –
- Procedural programming –
- Program lifecycle phase –
- Programming language –
- Programming language implementation –
- Programming language theory –
- Prolog –
- Python –
- R programming language –
- Radix –
- Recursion –
- Reference counting –
- Relational database –
- Reliability engineering –
- Regression testing –
- Requirements analysis –
- Robotics –
- Round-off error –
- Router –
- Routing table –
- Run time –
- Run time error –
- Search algorithm –
- Secondary storage –
- Selection sort –
- Semantics –
- Sequence –
- Set –
- Soft computing –
- Software –
- Software agent –
- Software construction –
- Software deployment –
- Software design –
- Software development –
- Software development process –
- Software engineering –
- Software maintenance –
- Software prototyping –
- Software requirements specification –
- Software testing –
- Sorting algorithm –
- Source code –
- Spiral model –
- Stack –
- Storage –
- String –
- Structured storage –
- Subroutine –
- Symbolic computation –
- Syntax –
- Syntax error –
- System console –
- Technical documentation –
- Third-generation programming language –
- Top-down and bottom-up design –
- Tree –
- Type theory –
- Upload –
- Uniform Resource Locator –
- URL – Uniform Resource Locator.
- User agent –
- User interface –
- User interface design –
- WAV – Waveform Audio File Format.
- Waterfall model –
- Waveform Audio File Format –
- Web crawler –
- Wi-Fi –
- "Abstract Methods and Classes". oracle.com. Oracle Java Documentation. Retrieved 11 December 2014.
- Colburn, Timothy; Shute, Gary (2007-06-05). "Abstraction in Computer Science". Minds and Machines. 17 (2): 169–184. doi:10.1007/s11023-007-9061-7. ISSN 0924-6495.
- Kramer, Jeff (2007-04-01). "Is abstraction the key to computing?". Communications of the ACM. 50 (4): 36–42. CiteSeerX 10.1.1.120.6776. doi:10.1145/1232743.1232745. ISSN 0001-0782.
- Comparison of Agent Architectures Archived August 27, 2008, at the Wayback Machine.
- Collier, Ken W. (2011). Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing. Pearson Education. pp. 121 ff. ISBN 9780321669544.
What is a self-organizing team?
- "What is Agile Software Development?". Agile Alliance. 8 June 2013. Retrieved 4 April 2015.
- Goodrich, Michael T.; Tamassia, Roberto (2002), Algorithm Design: Foundations, Analysis, and Internet Examples, John Wiley & Sons, Inc., ISBN 978-0-471-38365-9
- "Application software". PC Magazine. Ziff Davis.
- Black, Paul E. (13 November 2008). "array". Dictionary of Algorithms and Data Structures. National Institute of Standards and Technology. Retrieved 22 August 2010.
- Bjoern Andres; Ullrich Koethe; Thorben Kroeger; Hamprecht (2010). "Runtime-Flexible Multi-dimensional Arrays and Views for C++98 and C++0x". arXiv:1008.2909 [cs.DS].
- Garcia, Ronald; Lumsdaine, Andrew (2005). "MultiArray: a C++ library for generic programming with arrays". Software: Practice and Experience. 35 (2): 159–188. doi:10.1002/spe.630. ISSN 0038-0644.
Definition of AI as the study of intelligent agents:
- Poole, Mackworth & Goebel 1998, p. 1, which provides the version that is used in this article. Note that they use the term "computational intelligence" as a synonym for artificial intelligence.
- Russell & Norvig (2003) (who prefer the term "rational agent") and write "The whole-agent view is now widely accepted in the field" (Russell & Norvig 2003, p. 55).
- Nilsson 1998
- Legg & Hutter 2007.
- Russell & Norvig 2009, p. 2.
- Douglas Comer, Computer Networks and Internets, page 99 ff, Prentice Hall 2008.
- Fred Halsall, to data+communications and computer networks, page 108, Addison-Wesley, 1985.
- Cisco Networking Academy Program: CCNA 1 and 2 companion guide, Volym 1–2, Cisco Academy 2003
- Behrouz A. Forouzan, Data communications and networking, McGraw-Hill, 2007
- "Bayesian versus Frequentist Probability". deepai.org.
- Fleming, Philip J.; Wallace, John J. (1986-03-01). "How not to lie with statistics: the correct way to summarize benchmark results". Communications of the ACM. 29 (3): 218–221. doi:10.1145/5666.5673. ISSN 0001-0782. Retrieved 2017-06-09.
- Breur, Tom (July 2016). "Statistical Power Analysis and the contemporary "crisis" in social sciences". Journal of Marketing Analytics. 4 (2–3): 61–65. doi:10.1057/s41270-016-0001-3. ISSN 2050-3318.
- Bachmann, Paul (1894). Analytische Zahlentheorie [Analytic Number Theory] (in German). 2. Leipzig: Teubner.
- Landau, Edmund (1909). Handbuch der Lehre von der Verteilung der Primzahlen [Handbook on the theory of the distribution of the primes] (in German). Leipzig: B. G. Teubner. p. 883.
- Williams, Jr., Louis F. (22 April 1976). A modification to the half-interval search (binary search) method. Proceedings of the 14th ACM Southeast Conference. ACM. pp. 95–101. doi:10.1145/503561.503582. Archived from the original on 12 March 2017. Retrieved 29 June 2018.
- Knuth 1998, §6.2.1 ("Searching an ordered table"), subsection "Binary search".
- Butterfield & Ngondi 2016, p. 46.
- Cormen et al. 2009, p. 39.
- Weisstein, Eric W. "Binary search". MathWorld.
- Rowan Garnier; John Taylor (2009). Discrete Mathematics: Proofs, Structures and Applications, Third Edition. CRC Press. p. 620. ISBN 978-1-4398-1280-8.
- Steven S Skiena (2009). The Algorithm Design Manual. Springer Science & Business Media. p. 77. ISBN 978-1-84800-070-4.
- Mackenzie, Charles E. (1980). Coded Character Sets, History and Development. The Systems Programming Series (1 ed.). Addison-Wesley Publishing Company, Inc. p. x. ISBN 978-0-201-14460-4. LCCN 77-90165. Archived from the original on 18 November 2016. Retrieved 22 May 2016. 
- Gupta, Prakash C (2006). Data Communications and Computer Networks. PHI Learning. ISBN 9788120328464. Retrieved 10 July 2011.
- James D. Murray; William vanRyper (April 1996). "Encyclopedia of Graphics File Formats" (Second ed.). O'Reilly. bmp. ISBN 1-56592-161-5. Retrieved 2014-03-07.
- James D. Murray; William vanRyper (April 1996). "Encyclopedia of Graphics File Formats" (Second ed.). O'Reilly. os2bmp. ISBN 1-56592-161-5. Retrieved 2014-03-07.
- Gries, David; Schneider, Fred B. (1993), "Chapter 2. Boolean Expressions", A Logical Approach to Discrete Math, Monographs in Computer Science, Springer, p. 25ff, ISBN 9780387941158.
- Blaauw, Gerrit Anne; Brooks, Jr., Frederick Phillips; Buchholz, Werner (1962), "4: Natural Data Units", in Buchholz, Werner, Planning a Computer System – Project Stretch (PDF), McGraw-Hill Book Company, Inc. / The Maple Press Company, York, PA., pp. 39–40, LCCN 61-10466, archived (PDF) from the original on 2017-04-03, retrieved 2017-04-03,
[…] Terms used here to describe the structure imposed by the machine design, in addition to bit, are listed below.
Byte denotes a group of bits used to encode a character, or the number of bits transmitted in parallel to and from input-output units. A term other than character is used here because a given character may be represented in different applications by more than one code, and different codes may use different numbers of bits (i.e., different byte sizes). In input-output transmission the grouping of bits may be completely arbitrary and have no relation to actual characters. (The term is coined from bite, but respelled to avoid accidental mutation to bit.)
A word consists of the number of data bits transmitted in parallel from or to memory in one memory cycle. Word size is thus defined as a structural property of the memory. (The term catena was coined for this purpose by the designers of the Bull GAMMA 60 computer.)
Block refers to the number of words transmitted to or from an input-output unit in response to a single input-output instruction. Block size is a structural property of an input-output unit; it may have been fixed by the design or left to be varied by the program. […]
- Bemer, Robert William (1959), "A proposal for a generalized card code of 256 characters", Communications of the ACM, 2 (9): 19–23, doi:10.1145/368424.368435
- "What is a callback function?". Stack Overflow. Retrieved 2018-05-16.
- Weik, Martin H. (1961). "A Third Survey of Domestic Electronic Digital Computing Systems". Ballistic Research Laboratory.
- Kuck, David (1978). Computers and Computations, Vol 1. John Wiley & Sons, Inc. p. 12. ISBN 0471027162.
- "Definition of CHARACTER". www.merriam-webster.com. Retrieved 1 April 2018.
- Gamma et al. 1995, p. 14.
- Bruce 2002, 2.1 Objects, classes, and object types, https://books.google.com/books?id=9NGWq3K1RwUC&pg=PA18.
- Sadoski, Darleen. Client/Server Software Architectures – An Overview, Software Technology Roadmap, 1997-08-02. Retrieved on 2008-09-16.
- Mills, H.; M. Dyer; R. Linger (September 1987). "Cleanroom Software Engineering". IEEE Software. 4 (5): 19&ndash, 25. doi:10.1109/MS.1987.231413.
- Sussman and Steele. "Scheme: An interpreter for extended lambda calculus". "... a data structure containing a lambda expression, and an environment to be used when that lambda expression is applied to arguments." (Wikisource)
- Shaun Bebbington (2014). "What is coding". Retrieved 2014-03-03.
- Shaun Bebbington (2014). "What is programming". Retrieved 2014-03-03.
- Cognitive science is an interdisciplinary field of researchers from Linguistics, psychology, neuroscience, philosophy, computer science, and anthropology that seek to understand the mind. How We Learn: Ask the Cognitive Scientist
- Thagard, Paul, Cognitive Science, The Stanford Encyclopedia of Philosophy (Fall 2008 Edition), Edward N. Zalta (ed.).
- PC Mag Staff (28 February 2017). "Encyclopedia: Definition of Compiler". PCMag.com. Retrieved 28 February 2017.
- Computation from the Free Merriam-Webster Dictionary
- "Computation: Definition and Synonyms from Answers.com". Answers.com. Archived from the original on 22 February 2009. Retrieved 26 April 2017.
- Melnik, Roderick, ed. (2015). Mathematical and Computational Modeling: With Applications in Natural and Social Sciences, Engineering, and the Arts. Wiley. ISBN 978-1-118-85398-6.
- Trappenberg, Thomas P. (2002). Fundamentals of Computational Neuroscience. United States: Oxford University Press Inc. p. 1. ISBN 978-0-19-851582-1.
- What is computational neuroscience? Patricia S. Churchland, Christof Koch, Terrence J. Sejnowski. in Computational Neuroscience pp.46-55. Edited by Eric L. Schwartz. 1993. MIT Press "Archived copy". Archived from the original on 2011-06-04. Retrieved 2009-06-11.
- Press, The MIT. "Theoretical Neuroscience". The MIT Press. Retrieved 2018-05-24.
- Gerstner, W.; Kistler, W.; Naud, R.; Paninski, L. (2014). Neuronal Dynamics. Cambridge, UK: Cambridge University Press. ISBN 9781107447615.
- Clements, Alan. Principles of Computer Hardware (Fourth ed.). p. 1.
Architecture describes the internal organization of a computer in an abstract way; that is, it defines the capabilities of the computer and its programming model. You can have two computers that have been constructed in different ways with different technologies but with the same architecture.
- Hennessy, John; Patterson, David. Computer Architecture: A Quantitative Approach (Fifth ed.). p. 11.
This task has many aspects, including instruction set design, functional organization, logic design,and implementation.
- Patterson, David A.; Hennessy, John L. (2005). Computer Organization and Design: The Hardware/Software Interface (3rd ed.). Amsterdam: Morgan Kaufmann Publishers. ISBN 1-55860-604-1. OCLC 56213091.
- Bynum, Terrell Ward. "A Very Short History of Computer Ethics". Southern Connecticut Wein University. Archived from the original on 2008-04-18. Retrieved 2011-01-05.
- Shaun Bebbington (2014). "What is coding". Retrieved 2014-03-03.
- Shaun Bebbington (2014). "What is programming". Retrieved 2014-03-03.
- "WordNet Search—3.1". Wordnetweb.princeton.edu. Retrieved 14 May 2012.
- Orsucci, Franco F.; Sala, Nicoletta (2008). Reflexing Interfaces: The Complex Coevolution of Information Technology Ecosystems, Information Science Reference. p. 335.
- James Glanz (September 22, 2012). "Power, Pollution and the Internet". The New York Times. Retrieved 2012-09-25.
- Sparsh, Mittal,. "Power Management Techniques for Data Centers: A Survey".
- Dhar, V. (2013). "Data science and prediction". Communications of the ACM. 56 (12): 64. doi:10.1145/2500499.
- Jeff Leek (2013-12-12). "The key word in "Data Science" is not Data, it is Science". Simply Statistics.
- Hayashi, Chikio (1998-01-01). "What is Data Science? Fundamental Concepts and a Heuristic Example". In Hayashi, Chikio; Yajima, Keiji; Bock, Hans-Hermann; Ohsumi, Noboru; Tanaka, Yutaka; Baba, Yasumasa. Data Science, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer Japan. pp. 40–51. doi:10.1007/978-4-431-65950-1_3. ISBN 9784431702085.
- Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford (2009). Introduction to Algorithms, Third Edition (3rd ed.). The MIT Press. ISBN 978-0262033848.
- Black, Paul E. (15 December 2004). "data structure". In Pieterse, Vreda; Black, Paul E. Dictionary of Algorithms and Data Structures [online]. National Institute of Standards and Technology. Retrieved 2018-11-06.
- "Data structure". Encyclopaedia Britannica. 17 April 2017. Retrieved 2018-11-06.
- Wegner, Peter; Reilly, Edwin D. (2003-08-29). Encyclopedia of Computer Science. Chichester, UK: John Wiley and Sons. pp. 507–512. ISBN 978-0470864128.
- type at the Free On-line Dictionary of Computing
- Shaffer, C. A. (2011). Data Structures & Algorithm Analysis in C++ (3rd ed.). Mineola, NY: Dover. 1.2. ISBN 978-0-486-48582-9.
- "A declaration specifies the interpretation and attributes of a set of identifiers. A definition of an identifier is a declaration for that identifier that:
- for an object [variable or constant], causes storage to be reserved for that object;
- for a function, includes the function body;
- for an enumeration constant, is the (only) declaration of the identifier;
- for a typedef name, is the first (or only) declaration of the identifier."
- Mike Banahan. "2.5. Declaration of variables". http://publications.gbdirect.co.uk/c_book/: GBdirect. Retrieved 2011-06-08.
[A] declaration [...] introduces just the name and type of something but allocates no storage[...].
- CORMEN, THOMAS H. (2009). INTRODUCTION TO ALGORITHMS. United States of America: The MIT Press Cambridge, Massachusetts London, England. pp. 151–152. ISBN 978-0-262-03384-8.
- Black (ed.), Paul E. (2004-12-14). Entry for heap in Dictionary of Algorithms and Data Structures. Online version. U.S. National Institute of Standards and Technology, 14 December 2004. Retrieved on 2017-10-08 from https://xlinux.nist.gov/dads/HTML/heap.html.
- Skiena, Steven (2008). "Searching and Sorting". The Algorithm Design Manual. Springer. p. 109. doi:10.1007/978-1-84800-070-4_4. ISBN 978-1-84800-069-8.
[H]eapsort is nothing but an implementation of selection sort using the right data structure.