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Procedural Programming
Procedural programming is a programming paradigm, derived from structured programming, based upon the concept of the procedure call. Procedures, also known as routines, subroutines, or functions (not to be confused with mathematical functions, but similar to those used in functional programming), simply contain a series of computational steps to be carried out. Any given procedure might be called at any point during a program's execution, including by other procedures or itself. The first major procedural programming languages first appeared circa 1960, including Fortran, ALGOL, COBOL
COBOL
and BASIC.[1] Pascal and C were published closer to the 1970s, while Ada was released in 1980.[1] Go is an example of a more modern procedural language, first published in 2009. Computer processors provide hardware support for procedural programming through a stack register and instructions for calling procedures and returning from them
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Procedural Generation
In computing, procedural generation is a method of creating data algorithmically as opposed to manually. In computer graphics, it is also called random generation and is commonly used to create textures and 3D models. In video games, it is used to automatically create large amounts of content in a game. Advantages of procedural generation include smaller file sizes, larger amounts of content, and randomness for less predictable gameplay.Contents1 Overview 2 Contemporary application2.1 Video games2.1.1 Early history 2.1.2 Modern use2.2 Film3 Games which use procedural generation 4 See also 5 References 6 Further reading 7 External linksOverview[edit] The term procedural refers to the process that computes a particular function. Fractals are geometric patterns which can often be generated procedurally. Commonplace procedural content includes textures and meshes
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Concurrent Constraint Logic Programming
Concurrent constraint logic programming is a version of constraint logic programming aimed primarily at programming concurrent processes rather than (or in addition to) solving constraint satisfaction problems. Goals in constraint logic programming are evaluated concurrently; a concurrent process is therefore programmed as the evaluation of a goal by the interpreter. Syntactically, concurrent constraints logic programs are similar to non-concurrent programs, the only exception being that clauses include guards, which are constraints that may block the applicability of the clause under some conditions. Semantically, concurrent constraint logic programming differs from its non-concurrent versions because a goal evaluation is intended to realize a concurrent process rather than finding a solution to a problem
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Service-oriented Architecture
A service-oriented architecture (SOA) is a style of software design where services are provided to the other components by application components, through a communication protocol over a network
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Natural-language Programming
Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program. Natural languages and natural-language user interfaces include Inform7, a natural programming language for making interactive fiction, Ring[1][2], a general-purpose language, Shakespeare, an esoteric natural programming language in the style of the plays of William Shakespeare, and Wolfram Alpha, a computational knowledge engine, using natural-language input.Contents1 Interpretation 2 Software paradigm 3 Publication value of natural-language programs and documents 4 Contribution of natural-language programs to machine knowledge 5 See also 6 Bibliography 7 References 8 External linksInterpretation[edit] The smallest unit of statement in NLP is a sentence
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Spreadsheet
A spreadsheet is an interactive computer application for organization, analysis and storage of data in tabular form.[1][2][3] Spreadsheets are developed as computerized simulations of paper accounting worksheets.[4] The program operates on data entered in cells of a table. Each cell may contain either numeric or text data, or the results of formulas that automatically calculate and display a value based on the contents of other cells. A spreadsheet may also refer to one such electronic document.[5][6][7] Spreadsheet
Spreadsheet
users can adjust any stored value and observe the effects on calculated values. This makes the spreadsheet useful for "what-if" analysis since many cases can be rapidly investigated without manual recalculation
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Concurrent Logic Programming
Concurrent logic programming is a variant of logic programming in which programs are sets of guarded Horn clauses of the form:H :- G1, …, Gn B1, …, Bn.The conjunction G1, … , Gn is called the guard of the clause, and is the commitment operator. Declaratively, guarded Horn clauses are read as ordinary logical implications:H if G1 and … and Gn or B1 and … and Bn.However, procedurally, when there are several clauses whose heads H match a given goal, then all of the clauses are executed in parallel, checking whether their guards G1, … , Gn hold. If the guards of more than one clause hold, then a committed choice is made to one of the clauses, and execution proceedes with the subgoals B1, …, Bn of the chosen clause. These subgoals can also be executed in parallel
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Literate Programming
Literate programming
Literate programming
is a programming paradigm introduced by Donald Knuth in which a program is given as an explanation of the program logic in a natural language, such as English, interspersed with snippets of macros and traditional source code, from which a compilable source code can be generated.[1] The literate programming paradigm, as conceived by Knuth, represents a move away from writing programs in the manner and order imposed by the computer, and instead enables programmers to develop programs in the order demanded by the logic and flow of their thoughts.[2] Literate programs are written as an uninterrupted exposition of
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Relativistic Programming
Relativistic programming (RP) is a style of concurrent programming where instead of trying to avoid conflicts between readers and writers (or writers and writers in some cases) the algorithm is designed to tolerate them and get a correct result regardless of the order of events. Also, relativistic programming algorithms are designed to work without the presences of a global order of events. That is, there may be some cases where one thread sees two events in a different order than another thread (hence the term relativistic because in Einstein's theory of special relativity[citation needed] the order of events is not always the same to different viewers). Relativistic programming provides advantages in performance compared to other concurrency paradigms because it does not require one thread to wait for another nearly as often
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Tacit Programming
Tacit programming, also called point-free style, is a programming paradigm in which function definitions do not identify the arguments (or "points") on which they operate. Instead the definitions merely compose other functions, among which are combinators that manipulate the arguments. Tacit programming is of theoretical interest, because the strict use of composition results in programs that are well adapted for equational reasoning.[1] It is also the natural style of certain programming languages, including APL and its derivatives,[2] and concatenative languages such as Forth
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Value-level Programming
Value-level programming refers to one of the two contrasting programming paradigms identified by John Backus
John Backus
in his work on programs as mathematical objects, the other being function-level programming. Backus originally used the term object-level programming but that term is now prone to confusion with object-oriented programming. Value-level programs are those that describe how to combine various values (i.e., numbers, symbols, strings, etc.) to form other values until the final result values are obtained
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Function-level Programming
In computer science, function-level programming refers to one of the two contrasting programming paradigms identified by John Backus
John Backus
in his work on programs as mathematical objects, the other being value-level programming. In his 1977 Turing award
Turing award
lecture, Backus set forth what he considered to be the need to switch to a different philosophy in programming language design:[1]Programming languages appear to be in trouble. Each successive language incorporates, with a little cleaning up, all the features of its predecessors plus a few more. [...] Each new language claims new and fashionable features... but the plain fact is that few languages make programming sufficiently cheaper or more reliable to justify the cost of producing and learning to use them.He designed FP to be the first programming language to specifically support the function-level programming style. A function-level program is variable-free (cf
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Time-driven Programming
Time-driven programming is a computer programming paradigm, where the control flow of the computer program is driven by a clock and is often used in Real-time computing. A program is divided into a set of tasks (i.e., processes or threads), each of which has a periodic activation pattern. The activation patterns are stored in a dispatch table ordered by time. The Least-Common-Multiple (LCM) of all period-times determines the length of the dispatch table. The scheduler of the program dispatches tasks by consulting the next entry in the dispatch table. After processing all entries, it continues by looping back to the beginning of the table. The programming paradigm is mostly used for safety critical programs, since the behaviour of the program is highly deterministic. No external events are allowed to affect the control-flow of the program, the same pattern (i.e., described by the dispatch table) will be repeated time after time
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Action Language
In computer science, an action language is a language for specifying state transition systems, and is commonly used to create formal models of the effects of actions on the world.[1] Action languages are commonly used in the artificial intelligence and robotics domains, where they describe how actions affect the states of systems over time, and may be used for automated planning. Action languages fall into two classes: action description languages and action query languages. Examples of the former include STRIPS, PDDL, Language A (a generalization of STRIPS; the propositional part of Pednault's ADL), Language B (an extension of A adding indirect effects, distinguishing static and dynamic laws) and Language C (which adds indirect effects also, and does not assume that every fluent is automatically "inertial"). There are also the Action Query Languages P, Q and R
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Language-oriented Programming
Language-oriented programming (LOP) is a style of computer programming in which, rather than solving problems in general-purpose programming languages, the programmer creates one or more domain-specific languages for the problem first, and solves the problem in those languages. This concept is described in detail in the paper by Martin Ward entitled "Language Oriented Programming",[1] published in Software - Concepts and Tools, Vol.15, No.4, pp 147-161, 1994.[2]Contents1 Concept 2 See also 3 References 4 External linksConcept[edit] The concept of language-oriented programming takes the approach to capture requirements in the user's terms, and then to try to create an implementation language as isomorphic as possible to the user's descriptions, so that the mapping between requirements and implementation is as direct as possible
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Dynamic Programming Language
Dynamic programming
Dynamic programming
language, in computer science, is a class of high-level programming languages which, at runtime, execute many common programming behaviors that static programming languages perform during compilation. These behaviors could include extension of the program, by adding new code, by extending objects and definitions, or by modifying the type system. Although similar behaviours can be emulated in nearly any language, with varying degrees of difficulty, complexity and performance costs, dynamic languages provide direct tools to make use of them
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