Pseudocode
In computer science, pseudocode is an informal highlevel description of the operating principle of a computer program or other algorithm. It uses the structural conventions of a normal programming language, but is intended for human reading rather than machine reading. Pseudocode typically omits details that are essential for machine understanding of the algorithm, such as variable declarations, systemspecific code and some subroutines. The programming language is augmented with natural language description details, where convenient, or with compact mathematical notation. 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 environmentindependent description of the key principles of an algorithm. It is commonly used in textbooks and scientific publications that are documenting various algorithms, and also in planning of computer program development, for sketching out the structure of the program before the actual coding takes place.
No standard for pseudocode syntax exists, as a program in pseudocode is not an executable program. Pseudocode resembles skeleton programs which can be compiled without errors. Flowcharts, drakoncharts and Unified Modeling Language (UML) charts can be thought of as a graphical alternative to pseudocode, but are more spacious on paper. Languages such as HAGGIS bridge the gap between pseudocode and code written in programming languages.
Contents
Application
Textbooks and scientific publications related to computer science and numerical computation 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 may in some cases approach that of formalized generalpurpose languages.
A programmer 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 by sketching out the code in pseudocode on paper before writing it in its actual language, as a topdown structuring approach, with a process of steps to be followed as a refinement.
Syntax
Pseudocode generally does not actually obey the syntax 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.^{[1]}^{[2]} Some syntax sources include Fortran, Pascal, BASIC, C, C++, Java, Lisp, and ALGOL. Variable declarations are typically omitted. Function calls and blocks of code, such as code contained within a loop, are often replaced by a oneline natural language sentence.
Depending on the writer, pseudocode may therefore vary widely in style, from a nearexact imitation of a real programming language at one extreme, to a description approaching formatted prose at the other.
This is an example of pseudocode (for the mathematical game fizz buzz):
Fortran style pseudocode program fizzbuzz Do i = 1 to 100 set print_number to true If i is divisible by 3 print "Fizz" set print_number to false If i is divisible by 5 print "Buzz" set print_number to false If print_number, print i print a newline end do 
Pascal style pseudocode procedure fizzbuzz For i := 1 to 100 do set print_number to true; If i is divisible by 3 then print "Fizz"; set print_number to false; If i is divisible by 5 then print "Buzz"; set print_number to false; If print_number, print i; print a newline; end 
C style pseudocode: void function fizzbuzz { for (i = 1; i <= 100; i++) { set print_number to true; If i is divisible by 3 { print "Fizz"; set print_number to false; } If i is divisible by 5 { print "Buzz"; set print_number to false; } If print_number, print i; print a newline; } } 
Structured Basic style pseudocode Sub fizzbuzz() For i = 1 to 100 print_number = True If i is divisible by 3 Then Print "Fizz" print_number = False End If If i is divisible by 5 Then Print "Buzz" print_number = False End If If print_number = True Then print i Print a newline Next i End Sub 
Mathematical style pseudocode
In numerical computation, pseudocode often consists of mathematical notation, typically from set and matrix theory, mixed with the control structures of a conventional programming language, and perhaps also natural language 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 algorithms. For example, the sum operator (capitalsigma notation) or the product operator (capitalpi notation) may represent a forloop and a selection structure in one expression:
Return [math]\sum_{k\in S} x_k[/math]
Normally nonASCII typesetting is used for the mathematical equations, for example by means of markup languages, such as TeX or MathML, or proprietary formula editors.
Mathematical style pseudocode is sometimes referred to as pidgin code, for example pidgin ALGOL (the origin of the concept), pidgin Fortran, pidgin BASIC, pidgin Pascal, pidgin C, and pidgin Lisp.
Common mathematical symbols
Type of operation  Symbol  Example 

Assignment  ← or :=  c ← 2πr , c := 2πr

Comparison  =, ≠, <, >, ≤, ≥  
Arithmetic  +, −, ×, /, mod  
Floor/ceiling  ⌊, ⌋, ⌈, ⌉  a ← ⌊b⌋ + ⌈c⌉

Logical  and, or  
Sums, products  Σ Π  h ← Σ_{a∈A} 1/a

Example
Here follows a longer example of mathematicalstyle pseudocode, for the Ford–Fulkerson algorithm:
algorithm fordfulkerson is input: Graph G with flow capacity c, source node s, sink node t output: Flow f such that f is maximal from s to t (Note that f_{(u,v)} is the flow from node u to node v, and c_{(u,v)} is the flow capacity from node u to node v) for each edge (u, v) in G_{E} do f_{(u, v)} ← 0 f_{(v, u)} ← 0 while there exists a path p from s to t in the residual network G_{f} do let c_{f} be the flow capacity of the residual network G_{f} c_{f}(p) ← min{c_{f}(u, v)  (u, v) in p} for each edge (u, v) in p do f_{(u, v)} ← f_{(u, v)} + c_{f}(p) f_{(v, u)} ← −f_{(u, v)} return f
Machine compilation of pseudocode style languages
Natural language grammar in programming languages
Various attempts to bring elements of natural language grammar into computer programming have produced programming languages such as HyperTalk, Lingo, AppleScript, SQL, Inform and to some extent Python. In these languages, parentheses and other special characters are replaced by prepositions, resulting in quite talkative code. These languages are typically dynamically typed, meaning that variable declarations and other boilerplate code 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 conventional programming, and do not necessarily make development of the programs easier.
Mathematical programming languages
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 nonASCII mathematical notation and program control structures. Then the code can be parsed and interpreted by a machine.
Several formal specification languages include set theory notation using special characters. Examples are:
 Z notation
 Vienna Development Method Specification Language (VDMSL).
Some array programming languages include vectorized expressions and matrix operations as nonASCII formulas, mixed with conventional control structures. Examples are:
 A programming language (APL), and its dialects APLX and A+.
 MathCAD.
See also
 Concept programming
 Drakonchart
 Flowchart
 Literate programming
 Program Design Language
 Short Code
 Structured English
References
 Zobel, Justin (2013). "Algorithms". Writing for Computer Science (Second ed.). Springer. ISBN 1852338024. https://archive.org/details/springer_10.10079780857294227.
External links
 A pseudocode standard
 Collected Algorithms of the ACM
 Pseudocode Guidelines, PDF file.
 Pseudocode generation tool from a model tree learn how to generate pseudocode in a second
 Pseudocode interpreter PSEINT for AndroidOS
Original source: https://en.wikipedia.org/wiki/ Pseudocode.
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