25:
1546:
can be omitted. Such languages may make it easier for a person without knowledge about the language to understand the code and perhaps also to learn the language. However, the similarity to natural language is usually more cosmetic than genuine. The syntax rules may be just as strict and formal as in
235:
who needs to implement a specific algorithm, especially an unfamiliar one, will often start with a pseudocode description, and then "translate" that description into the target programming language and modify it to interact correctly with the rest of the program. Programmers may also start a project
227:
often use pseudocode in description of algorithms, so that all programmers can understand them, even if they do not all know the same programming languages. In textbooks, there is usually an accompanying introduction explaining the particular conventions in use. The level of detail of the pseudocode
1555:
An alternative to using mathematical pseudocode (involving set theory notation or matrix operations) for documentation of algorithms is to use a formal mathematical programming language that is a mix of non-ASCII mathematical notation and program control structures. Then the code can be parsed and
303:
This flexibility brings both major advantages and drawbacks: on the positive side, no executable programming language "can beat the convenience of inventing new constructs as needed and letting the reader try to deduce their meaning from informal explanations", on the negative, "untested code is
170:. The purpose of using pseudocode is that it is easier for people to understand than conventional programming language code, and that it is an efficient and environment-independent description of the key principles of an algorithm. It is commonly used in textbooks and
263:
rules of any particular language; there is no systematic standard form. Some writers borrow style and syntax from control structures from some conventional programming language, although this is discouraged. Some syntax sources include
157:
reading rather than machine control. Pseudocode typically omits details that are essential for machine implementation of the algorithm, meaning that pseudocode can only be verified by hand. The programming language is
299:
Depending on the writer, pseudocode may therefore vary widely in style, from a near-exact imitation of a real programming language at one extreme, to a description approaching formatted prose at the other.
1675:
An often-repeated definition of pseudocode since at least 2003 is "a detailed yet readable description of what a computer program or algorithm must do, expressed in a formally-styled natural language"
915:
descriptions. This is a compact and often informal notation that can be understood by a wide range of mathematically trained people, and is frequently used as a way to describe mathematical
296:. Variable declarations are typically omitted. Function calls and blocks of code, such as code contained within a loop, are often replaced by a one-line natural language sentence.
972:
1867:
Ulate-Caballero, Bryan
Alexander; Berrocal-Rojas, Allan; Hidalgo-Cespedes, Jeisson (2021-10-25). "Concurrent and Distributed Pseudocode: A Systematic Literature Review".
1685:
Ulate-Caballero, Bryan
Alexander; Berrocal-Rojas, Allan; Hidalgo-Céspedes, Jeisson (2021). "Concurrent and Distributed Pseudocode: A Systematic Literature Review".
181:
exists, as a program in pseudocode is not an executable program; however, certain limited standards exist (such as for academic assessment). Pseudocode resembles
1538:. In these languages, parentheses and other special characters are replaced by prepositions, resulting in quite verbose code. These languages are typically
885:
2020:
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languages include vectorized expressions and matrix operations as non-ASCII formulas, mixed with conventional control structures. Examples are:
1940:
1907:
1884:
1820:
1744:
1702:
1950:
Bellamy, Rachel (1994-06-01). "What Does Pseudo-Code Do? A Psychological
Analysis of the use of Pseudo-Code by Experienced Programmers".
1994:
1514:
Various attempts to bring elements of natural language grammar into computer programming have produced programming languages such as
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1780:
149:) with informal, usually self-explanatory, notation of actions and conditions. Although pseudocode shares features with regular
182:
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46:
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201:(UML) charts can be thought of as a graphical alternative to pseudocode, but need more space on paper. Languages such as
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35:
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Mitchell, Joan L.; Pennebaker, William B.; Fogg, Chad E.; LeGall, Didier J. (1996). "Pseudocode and
Flowcharts".
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1902:. Monographs in Theoretical Computer Science. An EATCS Series. Springer Berlin Heidelberg. pp. 15–46.
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by sketching out the code in pseudocode on paper before writing it in its actual language, as a
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conventional programming, and do not necessarily make development of the programs easier.
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is used for the mathematical equations, for example by means of markup languages, such as
1985:
1830:
Roy, Geoffrey G (2006). "Designing and explaining programs with a literate pseudocode".
82:
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2009:
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251:-like pseudocode and cannot be understood without grasping the details of the code.
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structuring approach, with a process of steps to be followed as a refinement.
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bridge the gap between pseudocode and code written in programming languages.
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The following is a longer example of mathematical-style pseudocode, for the
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may in some cases approach that of formalized general-purpose languages.
186:
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to document algorithms and in planning of software and other algorithms.
927:) may represent a for-loop and a selection structure in one expression:
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include set theory notation using special characters. Examples are:
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Avoid syntactic elements from the target programming language
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Pseudocode is also used in standardization. For example, the
16:
Description of an algorithm that resembles a computer program
1717:
999:
Mathematical style pseudocode is sometimes referred to as
1762:
Invitation to
Computer Science, 8th Edition by Schneider/
1990:
166:
description details, where convenient, or with compact
1666:, p. 23, Pseudocode Programs and Their Semantics.
1869:
2021 XLVII Latin
American Computing Conference (CLEI)
1687:
2021 XLVII Latin
American Computing Conference (CLEI)
937:
1838:(1). Association for Computing Machinery (ACM): 1.
1766:, "Keep statements language independent" as quoted
49:. Unsourced material may be challenged and removed.
966:
1510:Natural language grammar in programming languages
1505:Machine compilation of pseudocode style languages
259:Pseudocode generally does not actually obey the
1927:. New York, NY: Springer US. pp. 105–116.
1542:, meaning that variable declarations and other
1832:Journal on Educational Resources in Computing
1349:be the flow capacity of the residual network
8:
1896:"Abstract State Machines for the Classroom"
1252:is the flow capacity from node u to node v)
958:
942:
936:
886:Category:Articles with example pseudocode
109:Learn how and when to remove this message
1248:is the flow from node u to node v, and c
1052:
306:
1656:
1663:
7:
1809:Zobel, Justin (2013). "Algorithms".
129:is a description of the steps in an
47:adding citations to reliable sources
967:{\displaystyle \sum _{k\in S}x_{k}}
247:standards make heavy use of formal
1958:(2). Informa UK Limited: 225–246.
1779:Lamport, Leslie (2 January 2009).
1551:Mathematical programming languages
308:An example of pseudocode (for the
14:
1900:Logics of Specification Languages
1739:. Pearson Education. p. 54.
919:. For example, the sum operator (
177:No broad standard for pseudocode
1781:"The PlusCal Algorithm Language"
1575:Specification Language (VDM-SL).
23:
2021:Algorithm description languages
1925:MPEG Video Compression Standard
899:, pseudocode often consists of
34:needs additional citations for
1877:10.1109/clei53233.2021.9640222
1768:in this stackexchange question
1695:10.1109/CLEI53233.2021.9640222
133:using a mix of conventions of
1:
1815:(Second ed.). Springer.
1010:(the origin of the concept),
891:Mathematical style pseudocode
1812:Writing for Computer Science
1049:Common mathematical symbols
923:) or the product operator (
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1964:10.1207/s15327051hci0902_3
1952:Human-Computer Interaction
1556:interpreted by a machine.
1216:, source node
883:
318:
199:Unified Modelling Language
1894:Reisig, Wolfgang (2007).
1573:Vienna Development Method
1590:(APL), and its dialects
1220:, sink node
1193:Ford–Fulkerson algorithm
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521:
323:
1933:10.1007/0-306-46983-9_6
1871:. IEEE. pp. 1–10.
1844:10.1145/1217862.1217863
1635:Program Design Language
1561:specification languages
217:scientific publications
172:scientific publications
1588:A programming language
1099:=, ≠, <, >, ≤, ≥
968:
921:capital-sigma notation
2000:Pseudocode Guidelines
1986:A pseudocode standard
1534:, and to some extent
1328:the residual network
969:
901:mathematical notation
897:numerical computation
225:numerical computation
168:mathematical notation
153:, it is intended for
151:programming languages
135:programming languages
1991:Collected Algorithms
1786:. Microsoft Research
1718:Mitchell et al. 1996
1630:Literate programming
1313:there exists a path
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304:usually incorrect".
143:conditional operator
43:improve this article
1615:Concept programming
1212:with flow capacity
925:capital-pi notation
316:
139:assignment operator
1645:Structured English
964:
953:
307:
1942:978-0-412-08771-4
1909:978-3-540-74107-7
1886:978-1-6654-9503-5
1822:978-1-85233-802-2
1746:978-0-7356-1967-8
1704:978-1-6654-9503-5
1689:. pp. 1–10.
1581:array programming
1540:dynamically typed
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1056:Type of operation
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183:skeleton programs
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842:"Buzz"
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1664:Reisig 2007
1524:AppleScript
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1001:pidgin code
982:typesetting
219:related to
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99:August 2016
2010:Categories
1915:2023-10-05
1651:References
1640:Short Code
1568:Z notation
1402:}
1231:such that
1119:⌊, ⌋, ⌈, ⌉
1106:Arithmetic
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1067:Assignment
917:algorithms
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191:Flowcharts
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1972:0737-0024
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1199:algorithm
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