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Literate programming
Literate programming (LP) is a programming paradigm introduced in 1984 by Donald Knuth in which a computer program is given as an explanation of how it works in a natural language, such as English, interspersed (embedded) with snippets of macros and traditional source code, from which compilable source code can be generated. The approach is used in scientific computing and in data science routinely for reproducible research and open access purposes. Literate programming tools are used by millions of programmers today.
The literate programming paradigm, as conceived by Donald Knuth, represents a move away from writing computer programs in the manner and order imposed by the compiler, and instead gives programmers macros to develop programs in the order demanded by the logic and flow of their thoughts. Literate programs are written as an exposition of logic in more natural language in which macros are used to hide abstractions and traditional source code, more like the text of an essay.
Literate programming tools are used to obtain two representations from a source file: one understandable by a compiler or interpreter, the "tangled" code, and another for viewing as formatted documentation, which is said to be "woven" from the literate source. While the first generation of literate programming tools were computer language-specific, the later ones are language-agnostic and exist beyond the individual programming languages.
Literate programming was first introduced in 1984 by Donald Knuth, who intended it to create programs that were suitable literature for human beings. He implemented it at Stanford University as a part of his research on algorithms and digital typography. The implementation was called "WEB" since he believed that it was one of the few three-letter words of English that had not yet been applied to computing. However, it resembles the complicated nature of software delicately pieced together from simple materials. The practice of literate programming has seen an important resurgence in the 2010s with the use of computational notebooks, especially in data science.
Literate programming is writing out the program logic in a human language with included (separated by a primitive markup) code snippets and macros. Macros in a literate source file are simply title-like or explanatory phrases in a human language that describe human abstractions created while solving the programming problem, and hiding chunks of code or lower-level macros. These macros are similar to the algorithms in pseudocode typically used in teaching computer science. These arbitrary explanatory phrases become precise new operators, created on the fly by the programmer, forming a meta-language on top of the underlying programming language.
A preprocessor is used to substitute arbitrary hierarchies, or rather "interconnected 'webs' of macros", to produce the compilable source code with one command ("tangle"), and documentation with another ("weave"). The preprocessor also provides an ability to write out the content of the macros and to add to already created macros in any place in the text of the literate program source file, thereby disposing of the need to keep in mind the restrictions imposed by traditional programming languages or to interrupt the flow of thought.
According to Knuth, literate programming provides higher-quality programs, since it forces programmers to explicitly state the thoughts behind the program, making poorly thought-out design decisions more obvious. Knuth also claims that literate programming provides a first-rate documentation system, which is not an add-on, but is grown naturally in the process of exposition of one's thoughts during a program's creation. The resulting documentation allows the author to restart their own thought processes at any later time, and allows other programmers to understand the construction of the program more easily. This differs from traditional documentation, in which a programmer is presented with source code that follows a compiler-imposed order, and must decipher the thought process behind the program from the code and its associated comments. The meta-language capabilities of literate programming are also claimed to facilitate thinking, giving a higher "bird's eye view" of the code and increasing the number of concepts the mind can successfully retain and process. Applicability of the concept to programming on a large scale, that of commercial-grade programs, is proven by an edition of TeX code as a literate program.
Knuth also claims that literate programming can lead to easy porting of software to multiple environments, and even cites the implementation of TeX as an example.
Hub AI
Literate programming AI simulator
(@Literate programming_simulator)
Literate programming
Literate programming (LP) is a programming paradigm introduced in 1984 by Donald Knuth in which a computer program is given as an explanation of how it works in a natural language, such as English, interspersed (embedded) with snippets of macros and traditional source code, from which compilable source code can be generated. The approach is used in scientific computing and in data science routinely for reproducible research and open access purposes. Literate programming tools are used by millions of programmers today.
The literate programming paradigm, as conceived by Donald Knuth, represents a move away from writing computer programs in the manner and order imposed by the compiler, and instead gives programmers macros to develop programs in the order demanded by the logic and flow of their thoughts. Literate programs are written as an exposition of logic in more natural language in which macros are used to hide abstractions and traditional source code, more like the text of an essay.
Literate programming tools are used to obtain two representations from a source file: one understandable by a compiler or interpreter, the "tangled" code, and another for viewing as formatted documentation, which is said to be "woven" from the literate source. While the first generation of literate programming tools were computer language-specific, the later ones are language-agnostic and exist beyond the individual programming languages.
Literate programming was first introduced in 1984 by Donald Knuth, who intended it to create programs that were suitable literature for human beings. He implemented it at Stanford University as a part of his research on algorithms and digital typography. The implementation was called "WEB" since he believed that it was one of the few three-letter words of English that had not yet been applied to computing. However, it resembles the complicated nature of software delicately pieced together from simple materials. The practice of literate programming has seen an important resurgence in the 2010s with the use of computational notebooks, especially in data science.
Literate programming is writing out the program logic in a human language with included (separated by a primitive markup) code snippets and macros. Macros in a literate source file are simply title-like or explanatory phrases in a human language that describe human abstractions created while solving the programming problem, and hiding chunks of code or lower-level macros. These macros are similar to the algorithms in pseudocode typically used in teaching computer science. These arbitrary explanatory phrases become precise new operators, created on the fly by the programmer, forming a meta-language on top of the underlying programming language.
A preprocessor is used to substitute arbitrary hierarchies, or rather "interconnected 'webs' of macros", to produce the compilable source code with one command ("tangle"), and documentation with another ("weave"). The preprocessor also provides an ability to write out the content of the macros and to add to already created macros in any place in the text of the literate program source file, thereby disposing of the need to keep in mind the restrictions imposed by traditional programming languages or to interrupt the flow of thought.
According to Knuth, literate programming provides higher-quality programs, since it forces programmers to explicitly state the thoughts behind the program, making poorly thought-out design decisions more obvious. Knuth also claims that literate programming provides a first-rate documentation system, which is not an add-on, but is grown naturally in the process of exposition of one's thoughts during a program's creation. The resulting documentation allows the author to restart their own thought processes at any later time, and allows other programmers to understand the construction of the program more easily. This differs from traditional documentation, in which a programmer is presented with source code that follows a compiler-imposed order, and must decipher the thought process behind the program from the code and its associated comments. The meta-language capabilities of literate programming are also claimed to facilitate thinking, giving a higher "bird's eye view" of the code and increasing the number of concepts the mind can successfully retain and process. Applicability of the concept to programming on a large scale, that of commercial-grade programs, is proven by an edition of TeX code as a literate program.
Knuth also claims that literate programming can lead to easy porting of software to multiple environments, and even cites the implementation of TeX as an example.