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Former good articleProgramming language was one of the Engineering and technology good articles, but it has been removed from the list. There are suggestions below for improving the article to meet the good article criteria. Once these issues have been addressed, the article can be renominated. Editors may also seek a reassessment of the decision if they believe there was a mistake.
Article milestones
DateProcessResult
June 21, 2006Featured article candidateNot promoted
June 28, 2006Peer reviewReviewed
July 8, 2006Good article nomineeListed
March 10, 2009Good article reassessmentDelisted
Current status: Delisted good article

Article scope too limited: assuming machines and computers[edit]

Currently this article assumes that programming language is a phenomenon exclusive to machines in general, and computers in particular.

This assumption seems inappropriate, given that there is at least one widely-recognized counterexample: biological programming languages:

See e.g.

dr.ef.tymac (talk) 18:13, 29 April 2017 (UTC)[reply]

Did you read more about it?
Programming biological systems is a metaphor.
The work you cite is not as recent as you think, it is part of an area called Synthetic Biology.
Synthetic biology tries to apply real engineering principles to genetic engineering.
Biological systems, however, are complex systems. They can not be programmed them in the same sense that computers are, because you can not program emergent properties just designing a DNA chain. Not even composing known biological pathways isolated and standardized as Biobricks, as synthetic biology works.
There are however other computing forms, like quantum computing, there is an ongoing research on it. Even a DNA computing, which encodes problems in DNA chains and place them to evolve in a thermo-cycler for PCR and device a way to isolate the chain with the answer. — Preceding unsigned comment added by 201.124.211.115 (talk) 05:10, 11 June 2017 (UTC)[reply]

This article is a total mess![edit]

It repeats many common places, many of them wrong!, but repeated again, and again, in many programming courses given in basic education based on outdated information. Also many "complete idiot's guide", "learn in N days" or "for dummies" like those in the photo with tech books, repeat again and again.

Many people know some programming language and write code. That does not make then an authority in the subject. However many of them feel they are.

This article seems written from notes taken in basic programming courses.

Has discussions like: How many angels can be in the tip of a needle? — Preceding unsigned comment added by 201.124.211.115 (talk) 05:53, 11 June 2017 (UTC)[reply]

yep too much information unrelated to the core subject and which does not help understanding. this needs to moved to relevant topics.

For example, the paragraph in FLOW-MATIC adds nothing to understanding what a computer language is and should be in the topic on Flow-matic, not programming.

there are also too many competing ideas, such as the definition of a programming language that just confuse things. My view is that Wikipedia should focus on commonly accepted facts and theories rather than pet issues insered by Academics to try and give exposure to very minority theories. it is a to help understanding, not a weapon in obscure Academic debates and personal obsessions. 60.241.211.27 (talk) 12:07, 28 July 2021 (UTC)[reply]

What a pedantic message. Kwiky (talk) 19:04, 19 September 2023 (UTC)[reply]

Defining the term "programming language" properly[edit]

Wikipedia currently says a "programming language" is "a formal language that specifies a set of instructions that can be used to produce various kinds of output" which is true-ish, but vague. The phrase "various kinds of output" hints at the relevant characteristic, but still doesn't pin it down. Dictionary.com defines a "programming language" as "a high-level language used to write computer programs, as COBOL or BASIC, or, sometimes, an assembly language." This gibberish dances around it for a moment... but it makes no difference whether it is the highest-level symbolic meta-language or lowest-level machine code. An alternate Dictionary.com definition starts getting closer, "a simple language system designed to facilitate the writing of computer programs" but simplicity has nothing to do with it either and this definition still doesn't capture the essence. The important nugget here is the specification of decision making. A "computer language" is any predefined set of symbols and syntax that allows people to communicate with a computer system. But a "programming language" is a language among the broader set of computer languages that specifically enables a person to specify decision-making rules. CPUs make logical (true/false) decisions. The specification of a logical decision-making process is where the rubber meets the road. As example, HTML is a computer language, but not a programming language. If I want my computer's clock to display upside down, but only on Tuesdays, I can't use HTML to accomplish that. Get it? (HTML is really just a data markup language used to specify the metadata and the semantic structure of a Web document.)

Shall I take a crack at rewriting the first paragraph on the "programming language" page and I'll let you all have a look? I won't spend too much time on it unless the community wants me to, so let me know what you think. — Preceding unsigned comment added by Dlampton (talk • contribs) 00:39, 8 January 2018 (UTC)[reply]

Broken refs[edit]

@Squoop: you used some ref names that don't exist in the Abstractions section. Could you please fill those in? -- Fyrael (talk) 21:58, 10 October 2022 (UTC)[reply]

@Fyrael Fixed :D Squoop (talk) 00:19, 11 October 2022 (UTC)[reply]

"Semantics" is singular[edit]

A recent edit by Sumanbalayar corrected if computational semantics is defined to if a computational semantics is defined, but it was reverted by Girth Summit. Using "semantics" as singular is standard in the field, for example:

I favor Sumanbalayar's version of this sentence. Freoh (talk) 16:20, 5 January 2023 (UTC)[reply]

Fine to reinstate it if you like; it looked like a well-meaning but incorrect tweak to me, but you seem to know what you're talking about. Girth Summit (blether) 16:51, 5 January 2023 (UTC)[reply]
 Done. Freoh (talk) 17:01, 5 January 2023 (UTC)[reply]
Don't know if you noticed, but there were quite a few other tweaks I reverted in that edit - feel free to review them and reinstate if you think I erred. Girth Summit (blether) 17:33, 5 January 2023 (UTC)[reply]

Standard examples[edit]

It would be helpful if there were a small set of "standard" tasks and all pages on programming languages showed how to do them all (e.g., compute prime numbers, compute the squares of the numbers 1 to 10, print "Hello, world!"). Where should I suggest this? LachlanA (talk) 01:00, 21 January 2023 (UTC)[reply]

Proprietary section needs better citations[edit]

Oracle asserting something shouldn't be taken a evidence, needs better sources. FallingPineapple (talk) 02:05, 7 June 2023 (UTC)[reply]

Needs article-wide cleanup?[edit]

I think this article needs a thorough cleanup.

I feel like the article as a whole fails to provide accurate and useful information about programming languages.

I tried to improve the introduction but I'm sure my improvements still have issues...

Could a cleanup tag/tags be added? I'm not an experienced Wikipedian so I'm not sure what needs to be done. Squoop (talk) 01:19, 28 October 2023 (UTC)[reply]

Source code example's usage of method[edit]

The source code example https://en.wikipedia.org/wiki/Programming_language#/media/File:C_Hello_World_Program.png mentions that sayHello is a function and in between brackets 'method'. This is not a method, a method is associated with an object/class, C has no classes. 2A02:8389:2200:9F90:B5B9:15B4:D8AA:5901 (talk) 09:54, 5 December 2023 (UTC)[reply]

Edit request[edit]

Extended content

Programming languages are often placed into four main categories: imperative, functional, logic, and object oriented.[1]

  • Imperative languages are designed to implement an algorithm in a specified order; they include visual programming languages such as .NET for generating graphical user interfaces. Scripting languages, which are partly or fully interpreted rather than compiled, are sometimes considered a separate category but meet the definition of imperative languages.[2]
  • Functional programming languages work by successively applying functions to the given parameters. Although appreciated by many researchers for their simplicity and elegance, problems with efficiency have prevented them from being widely adopted.[3]
  • Logic languages are designed so that the software, rather than the programmer, decides what order in which the instructions are executed.[4]
  • Object-oriented programming—whose characteristic features are data abstraction, inheritance, and dynamic dispatch—is supported by most popular imperative languages and some functional languages.[2]

Although markup languages are not programming languages, some have extensions that support limited programming. Additionally, there are special-purpose languages that are not easily compared to other programming languages.[5]

References

  1. ^ Sebesta 2012, p. 21.
  2. ^ a b Sebesta 2012, pp. 21–22.
  3. ^ Sebesta 2012, p. 12.
  4. ^ Sebesta 2012, p. 22.
  5. ^ Sebesta 2012, pp. 22–23.

Sebesta, Robert W. (2012). Concepts of Programming Languages (10 ed.). Addison-Wesley. ISBN 978-0-13-139531-2.

@Buidhe paid @Buidhe I'm personally fine with the changes above, I think going ahead and making these changes are fine, however, I'd like you to comply with PAID and disclose your employer/client/affiliationn on your user page for future reference :) Sohom (talk) 16:18, 13 January 2024 (UTC)[reply]
Sohom Thanks, now done. Buidhe paid (talk) 02:29, 14 January 2024 (UTC)[reply]
 Already done Shadow311 (talk) 16:03, 18 January 2024 (UTC)[reply]

Please add the following text at the end of the "elements" section:

Extended content

Concurrency[edit]

See also: Concurrent computing

In computing, multiple instructions can be executed simultaneously. Many programming languages support instruction-level and subprogram-level concurrency.[1] By the twenty-first century, additional processing power on computers was increasingly coming from the use of additional processors, which requires programmers to design software that makes use of multiple processors simultaneously to achieve improved performance.[2] Interpreted languages such as Python and Ruby do not support the concurrent use of multiple processors.[3] Other programming languages do support managing data shared between different threads by controlling the order of execution of key instructions via the use of semaphores, controlling access to shared data via monitor, or enabling message passing between threads.[4]

References

  1. ^ Sebesta 2012, p. 576.
  2. ^ Sebesta 2012, p. 579.
  3. ^ Sebesta 2012, p. 585.
  4. ^ Sebesta 2012, pp. 585–586.

Buidhe paid (talk) 17:48, 23 January 2024 (UTC)[reply]

 Done Both. Sohom (talk) 18:06, 23 January 2024 (UTC)[reply]

Please add the following text just before the "Concurrency" section:

Extended content

Exception handling[edit]

Main article: Exception handling

Many programming languages include exception handlers, a section of code triggered by runtime errors that can deal with them in two main ways:[1]

  • Termination: shutting down and handing over control to the operating system. This option is considered the simplest.
  • Resumption: resuming the program near where the exception occurred. This can trigger a repeat of the exception, unless the exception handler is able to modify values to prevent the exception from reoccurring.

Some programming languages support dedicating a block of code to run regardless of whether an exception occurs before the code is reached; this is called finalization.[2]

There is a tradeoff between increased ability to handle exceptions and reduced performance.[3] For example, even though array index errors are common[4] C does not check them for performance reasons.[3] Although programmers can write code to catch user-defined exceptions, this can clutter a program. Standard libraries in some languages, such as C, use their return values to indicate an exception.[5] Some languages and their compilers have the option of turning on and off error handling capability, either temporarily or permanently.[6]

References

  1. ^ Sebesta 2012, pp. 630, 634.
  2. ^ Sebesta 2012, p. 635.
  3. ^ a b Sebesta 2012, p. 631.
  4. ^ Sebesta 2012, p. 261.
  5. ^ Sebesta 2012, p. 632.
  6. ^ Sebesta 2012, pp. 631, 635–636.

Thanks Buidhe paid (talk) 19:27, 23 January 2024 (UTC)[reply]

 Done, Sohom (talk) 08:40, 24 January 2024 (UTC)[reply]

Edit request 2[edit]

Please change the content of the "Type system" section, after the hatnote, to:

Extended content

A data type is a set of allowable values and operations that can be performed on these values.[1] Each programming language's type system defines which data types exist, the type of an expression, and how type equivalence and type compatibility function in the language.[2]

According to type theory, a language is fully typed if the specification of every operation defines types of data to which the operation is applicable.[3] In contrast, an untyped language, such as most assembly languages, allows any operation to be performed on any data, generally sequences of bits of various lengths.[3] In practice, while few languages are fully typed, most offer a degree of typing.[3]

Because different types (such as integers and floats) represent values differently, unexpected results will occur if one type is used when another is expected. Type checking will flag this error, usually at compile time (runtime type checking is more costly).[4] With strong typing, type errors can always be detected unless variables are explicitly cast to a different type. Weak typing occurs when languages allow implicit casting—for example, to enable operations between variables of different types without the programmer making an explicit type conversion. The more cases in which this type coercion is allowed, the fewer type errors can be detected.[5]

Commonly supported types[edit]

See also: Primitive data type

Early programming languages often supported only built-in, numeric types such as the integer (signed and unsigned) and floating point (to support operations on real numbers that are not integers). Most programming languages support multiple sizes of floats (often called float and double) and integers depending on the size and precision required by the programmer. Storing an integer in a type that is too small to represent it leads to integer overflow. The most common way of representing negative numbers with signed types is twos complement, although ones complement is also used. [6] Other common types include boolean—which is either true or false—and character—traditionally one byte, sufficient to represent all ASCII characters.[7]

Arrays are a data type whose elements, in many languages, must consist of a single type of fixed length. Other languages define arrays as references to data stored elsewhere and support elements of varying types.[8] Depending on the programming language, sequences of multiple characters, called strings, may be supported as arrays of characters or their own primitive type.[9] Strings may be of fixed or variable length, which enables greater flexibility at the cost of increased storage space and more complexity.[10] Other data types that may be supported include lists,[11] associative (unordered) arrays accessed via keys,[12] records in which data is mapped to names in an ordered structure,[13] and tuples—similar to records but without names for data fields.[14] Pointers store memory addresses, typically referencing locations on the heap where other data is stored.[15]

The simplest user-defined type is an ordinal type whose values can be mapped onto the set of positive integers.[16] Since the mid-1980s, most programming languages also support abstract data types, in which the representation of the data and operations are hidden from the user, who can only access an interface.[17] The benefits of data abstraction can include increased reliability, reduced complexity, less potential for name collision, and allowing the underlying data structure to be changed without the client needing to alter its code.[18]

Static and dynamic typing[edit]

In static typing, all expressions have their types determined before a program executes, typically at compile-time.[3] Most widely used, statically typed programming languages require the types of variables to be specified explicitly. In some languages, types are implicit; one form of this is when the compiler can infer types based on context. The downside of implicit typing is the potential for errors to go undetected.[19] Complete type inference has traditionally been associated with functional languages such as Haskell and ML.[20]

With dynamic typing, the type is not attached to the variable but only the value encoded in it. A single variable can be reused for a value of a different type. Although this provides more flexibility to the programmer, it is at the cost of lower reliability and less ability for the programming language to check for errors.[21] Some languages allow variables of a union type to which any type of value can be assigned, in an exception to their usual static typing rules.[22]

References

  1. ^ Sebesta 2012, p. 244.
  2. ^ Sebesta 2012, p. 245.
  3. ^ a b c d Andrew Cooke. "Introduction To Computer Languages". Archived from the original on 15 August 2012. Retrieved 13 July 2012.
  4. ^ Sebesta 2012, pp. 15, 408–409.
  5. ^ Sebesta 2012, pp. 303–304.
  6. ^ Sebesta 2012, pp. 246–247.
  7. ^ Sebesta 2012, p. 249.
  8. ^ Sebesta 2012, p. 260.
  9. ^ Sebesta 2012, p. 250.
  10. ^ Sebesta 2012, p. 254.
  11. ^ Sebesta 2012, pp. 281–282.
  12. ^ Sebesta 2012, pp. 272–273.
  13. ^ Sebesta 2012, pp. 276–277.
  14. ^ Sebesta 2012, p. 280.
  15. ^ Sebesta 2012, pp. 289–290.
  16. ^ Sebesta 2012, p. 255.
  17. ^ Sebesta 2012, pp. 244–245.
  18. ^ Sebesta 2012, p. 477.
  19. ^ Sebesta 2012, p. 211.
  20. ^ Leivant, Daniel (1983). Polymorphic type inference. ACM SIGACT-SIGPLAN symposium on Principles of programming languages. Austin, Texas: ACM Press. pp. 88–98. doi:10.1145/567067.567077. ISBN 978-0-89791-090-3.
  21. ^ Sebesta 2012, pp. 212–213.
  22. ^ Sebesta 2012, pp. 284–285.

Edit request 3[edit]

Also, please add the following sentence to the end of the "proprietary languages" section: "Open source programming languages are particularly helpful for open science applications, enhancing the capacity for replication and code sharing."[1]

References

  1. ^ Abdelaziz, Abdullah I.; Hanson, Kent A.; Gaber, Charles E.; Lee, Todd A. (2023). "Optimizing large real‐world data analysis with parquet files in R: A step‐by‐step tutorial". Pharmacoepidemiology and Drug Safety. doi:10.1002/pds.5728.

Thanks Buidhe paid (talk) 02:23, 25 January 2024 (UTC)[reply]

 Done Encoded Talk to me! 13:31, 9 February 2024 (UTC)[reply]

Edit request 4[edit]

Please:

Extended content

One of the most important influences on programming language design has been computer architecture. Imperative languages, the most commonly used type, were designed to perform well on von Neumann architecture, the most common computer architecture.[1] In von Neumann architecture, the memory stores both data and instructions, while the CPU that performs instructions on data is separate, and data must be piped back and forth to the CPU. The central elements in these languages are variables, assignment, and iteration, which is more efficient than recursion on these machines.[2]

Many programming languages have been designed from scratch, altered to meet new needs, and combined with other languages. Many have eventually fallen into disuse.[citation needed] The birth of programming languages in the 1950s was stimulated by the desire to make a universal programming language suitable for all machines and uses, avoiding the need to write code for different computers.[3] By the early 1960s, the idea of a universal language was rejected due to the differing requirements of the variety of purposes for which code was written.[4]

Tradeoffs[edit]

Desirable qualities of programming languages include readability, writability, and reliability.[5] These features can reduce the cost of training programmers in a language, the amount of time needed to write and maintain programs in the language, the cost of compiling the code, and increase runtime performance.[6]

  • Although early programming languages often prioritized efficiency over readability, the latter has grown in importance since the 1970s. Having multiple operations to achieve the same result can be detrimental to readability, as is overloading operators, so that the same operator can have multiple meanings.[7] Another feature important to readability is orthogonality, limiting the number of constructs that a programmer has to learn.[8] A syntax structure that is easily understood and special words that are immediately obvious also supports readability.[9]
  • Writability is the ease of use for writing code to solve the desired problem. Along with the same features essential for readability,[10] abstraction—interfaces that enable hiding details from the client—and expressivity—enabling more concise programs—additionally help the programmer write code.[11] The earliest programming languages were tied very closely to the underlying hardware of the computer, but over time support for abstraction has increased, allowing programmers express ideas that are more remote from simple translation into underlying hardware instructions. Because programmers are less tied to the complexity of the computer, their programs can do more computing with less effort from the programmer.[12] Most programming languages come with a standard library of commonly used functions.[13]
  • Reliability means that a program performs as specified in a wide range of circumstances.[14] Type checking, exception handling, and restricted aliasing (multiple variable names accessing the same region of memory) all can improve a program's reliability.[15]

Programming language design often involves tradeoffs.[16] For example, features to improve reliability typically come at the cost of performance.[17] Increased expressivity due to a large number of operators makes writing code easier but comes at the cost of readability.[17]

Natural-language programming has been proposed as a way to eliminate the need for a specialized language for programming. However, this goal remains distant and its benefits are open to debate. Edsger W. Dijkstra took the position that the use of a formal language is essential to prevent the introduction of meaningless constructs.[18] Alan Perlis was similarly dismissive of the idea.[19]

Specification[edit]

Main article: Programming language specification

The specification of a programming language is an artifact that the language users and the implementors can use to agree upon whether a piece of source code is a valid program in that language, and if so what its behavior shall be.

A programming language specification can take several forms, including the following:

Implementation[edit]

Main article: Programming language implementation

An implementation of a programming language is the conversion of a program into machine code that can be executed by the hardware. The machine code then can be executed with the help of the operating system.[23] The most common form of interpretation in production code is by a compiler, which translates the source code via an intermediate-level language into machine code, known as an executable. Once the program is compiled, it will run more quickly than with other implementation methods.[24] Some compilers are able to provide further optimization to reduce memory or computation usage when the executable runs, but increasing compilation time.[25]

Another implementation method is to run the program with an interpreter, which translates each line of software into machine code just before it executes. Although it can make debugging easier, the downside of interpretation is that it runs 10 to 100 times slower than a compiled executable.[26] Hybrid interpretation methods provide some of the benefits of compilation and some of the benefits of interpretation via partial compilation. One form this takes is just-in-time compilation, in which the software is compiled ahead of time into an intermediate language, and then into machine code immediately before execution.[27]

References

  1. ^ Sebesta 2012, p. 18.
  2. ^ Sebesta 2012, p. 19.
  3. ^ Nofre, Priestley & Alberts 2014, p. 55.
  4. ^ Nofre, Priestley & Alberts 2014, p. 60.
  5. ^ Sebesta 2012, p. 8.
  6. ^ Sebesta 2012, pp. 16–17.
  7. ^ Sebesta 2012, pp. 8–9.
  8. ^ Sebesta 2012, pp. 9–10.
  9. ^ Sebesta 2012, pp. 12–13.
  10. ^ Sebesta 2012, p. 13.
  11. ^ Sebesta 2012, pp. 14–15.
  12. ^ Frederick P. Brooks, Jr.: The Mythical Man-Month, Addison-Wesley, 1982, pp. 93–94
  13. ^ Busbee, Kenneth Leroy; Braunschweig, Dave (15 December 2018). "Standard Libraries". Programming Fundamentals – A Modular Structured Approach. Retrieved 27 January 2024.
  14. ^ Sebesta 2012, p. 15.
  15. ^ Sebesta 2012, pp. 8, 16.
  16. ^ Sebesta 2012, pp. 18, 23.
  17. ^ a b Sebesta 2012, p. 23.
  18. ^ Dijkstra, Edsger W. On the foolishness of "natural language programming." Archived 20 January 2008 at the Wayback Machine EWD667.
  19. ^ Perlis, Alan (September 1982). "Epigrams on Programming". SIGPLAN Notices Vol. 17, No. 9. pp. 7–13. Archived from the original on 17 January 1999.
  20. ^ Milner, R.; M. Tofte; R. Harper; D. MacQueen (1997). The Definition of Standard ML (Revised). MIT Press. ISBN 978-0-262-63181-5.
  21. ^ Kelsey, Richard; William Clinger; Jonathan Rees (February 1998). "Section 7.2 Formal semantics". Revised5 Report on the Algorithmic Language Scheme. Archived from the original on 6 July 2006.
  22. ^ ANSI – Programming Language Rexx, X3-274.1996
  23. ^ Sebesta 2012, pp. 23–24.
  24. ^ Sebesta 2012, pp. 25–27.
  25. ^ Sebesta 2012, p. 27.
  26. ^ Sebesta 2012, p. 28.
  27. ^ Sebesta 2012, pp. 29–30.

Please add the following source to the "further reading" section:

Thank you Buidhe paid (talk) 04:37, 27 January 2024 (UTC)[reply]

Edit request 5[edit]

Please change the content of the article lead (beginning below "use dmy dates" template) to:

Extended content
The source code for a computer program in C. The gray lines are comments that explain the program to humans. When compiled and run, it will give the output "Hello, world!".

A programming language is a system of notation for writing computer programs.[1]

Programming languages are described in terms of their syntax (form) and semantics (meaning), usually defined by a formal language. Most languages have a type system consisting of different data types (such as integers and strings) and catch type errors where one type is given where another is expected. Many support user-defined types including abstract data types, often used for object-oriented programming. Implementation in the form of a compiler or interpreter allows programs to be translated into machine code and executed.

Computer architecture has strongly influenced the design of programming languages, with the most common type (imperative languages—which implement operations in a specified order) developed to perform well on the popular von Neumann architecture. While early programming languages were closely tied to the hardware, over time, they have developed more abstraction to hide implementation details for greater simplicity.

Thousands of programming languages—often classified as imperative, functional, logic, or object-oriented—have been developed for a wide variety of uses. Many aspects of programming language design involve tradeoffs—for example, exception handling reduces errors at a performance cost—such that efforts to develop a universal programming language have failed. Programming language theory is the subfield of computer science that studies the design, implementation, analysis, characterization, and classification of programming languages.

References

  1. ^ Aaby, Anthony (2004). Introduction to Programming Languages. Archived from the original on 8 November 2012. Retrieved 29 September 2012.

Thanks Buidhe paid (talk) 08:57, 27 January 2024 (UTC)[reply]

 Done. Thanks for improving the lead. ― novov (t c) 05:01, 5 March 2024 (UTC)[reply]

Edit request 6[edit]

Please replace the content of the "History" section, after the hatnote, with:

Extended content

Early developments[edit]

The first programmable computers were invented at the end of the 1940s, and with them, the first programming languages.[1] The earliest computers were programmed in first-generation programming languages (1GLs), machine language (simple instructions that could be directly executed by the processor). This code was very difficult to debug and was not portable between different computer systems.[2] In order to improve the ease of programming, assembly languages (or second-generation programming languages—2GLs) were invented, diverging from the machine language to make programs easier to understand for humans, although they did not increase portability.[3]

Initially, hardware resources were scare and expensive, while human resources were cheaper. Therefore, cumbersome languages that were time-consuming to use, but were closer to the hardware for higher efficiency were favored.[4] The introduction of high-level programming languages (third-generation programming languages—3GLs)—revolutionized programming. These languages abstracted away the details of the hardware, instead being designed to express algorithms that could be understood more easily by humans. For example, arithmetic expressions could now be written in symbolic notation and later translated into machine code that the hardware could execute.[3] In 1957, Fortran (FORmula TRANslation) was invented. Often considered the first compiled high-level programming language,[3][5] Fortran has remained in use into the twenty-first century.[6]

1960s and 1970s[edit]

Two people using an IBM 704 mainframe—the first hardware to support floating-point arithmetic—in 1957. Fortran was designed for this machine.[7][6]

Around 1960, the first mainframes—general purpose computers—were developed, although they could only be operated by professionals and the cost was extreme. The data and instructions were input by punch cards, meaning that no input could be added while the program was running. The languages developed at this time therefore are designed for minimal interaction.[8] After the invention of the microprocessor, computers in the 1970s became dramatically cheaper.[9] New computers also allowed more user interaction, which was supported by newer programming languages.[10]

Lisp, implemented in 1958, was the first functional programming language. Unlike Fortran, it supports recursion and conditional expressions,[11] and it also introduced dynamic memory management on a heap and automatic garbage collection.[12] For the next decades, Lisp dominated artificial intelligence applications.[13] In 1978, another functional language, ML, introduced inferred types and polymorphic parameters.[10][14]

After ALGOL (ALGOrithmic Language) was released in 1958 and 1960,[15] it became the standard in computing literature for describing algorithms. Although its commercial success was limited, most popular imperative languages—including C, Pascal, Ada, C++, Java, and C#—are directly or indirectly descended from ALGOL 60.[16][6] Among its innovations adopted by later programming languages included greater portability and the first use of context-free, BNF grammar.[17] Simula, the first language to support object-oriented programming (including subtypes, dynamic dispatch, and inheritance), also descends from ALGOL and achieved commercial success.[18] C, another ALGOL descendant, has sustained popularity into the twenty-first century. C allows access to lower-level machine operations more than other contemporary languages. Its power and efficiency, generated in part with flexible pointer operations, comes at the cost of making it more difficult to write correct code.[10]

Prolog, designed in 1972, was the first logic programming language, communicating with a computer using formal logic notation.[19][20] With logic programming, the programmer specifies a desired result and allows the interpreter to decide how to achieve it.[21][20]

1980s to present[edit]

A small selection of programming language textbooks

During the 1980s, the invention of the personal computer transformed the roles for which programming languages were used.[22] New languages introduced in the 1980s included C++, a superset of C that can compile C programs but also supports classes and inheritance.[23] Ada and other new languages introduced support for concurrency.[24] The Japanese government invested heavily into the so-called fifth-generation languages that added support for concurrency to logic programming constructs, but these languages were outperformed by other concurrency-supporting languages.[25][26]

Due to the rapid growth of the Internet and the World Wide Web in the 1990s, new programming languages were introduced to support Web pages and networking.[27] Java, based on C++ and designed for increased portability across systems and security, enjoyed large-scale success because these features are essential for many Internet applications.[28][29] Another development was that of dynamically typed scripting languages—Python, JavaScript, PHP, and Ruby—designed to quickly produce small programs that coordinate existing applications. Due to their integration with HTML, they have also been used for building web pages hosted on servers.[30][31]

During the 2000s, there was a slowdown in the development of new programming languages that achieved widespread popularity.[32] One innovation was service-oriented programming, designed to exploit distributed systems whose components are connected by a network. Services are similar to objects in object-oriented programming, but run on a separate process.[33] C# and F# cross-pollinated ideas between imperative and functional programming.[34] After 2010, several new languages—Rust, Go, and Swift—competed for the performance-critical software for which C had historically been used.[35]

References

  1. ^ Gabbrielli & Martini 2023, p. 519.
  2. ^ Gabbrielli & Martini 2023, pp. 520–521.
  3. ^ a b c Gabbrielli & Martini 2023, p. 521.
  4. ^ Gabbrielli & Martini 2023, p. 522.
  5. ^ Sebesta 2012, p. 42.
  6. ^ a b c Gabbrielli & Martini 2023, p. 524.
  7. ^ Sebesta 2012, pp. 42–44.
  8. ^ Gabbrielli & Martini 2023, pp. 523–524.
  9. ^ Gabbrielli & Martini 2023, p. 527.
  10. ^ a b c Gabbrielli & Martini 2023, p. 528.
  11. ^ Sebesta 2012, pp. 47–48.
  12. ^ Gabbrielli & Martini 2023, p. 526.
  13. ^ Sebesta 2012, p. 50.
  14. ^ Sebesta 2012, pp. 701–703.
  15. ^ Gabbrielli & Martini 2023, pp. 524–525.
  16. ^ Sebesta 2012, pp. 56–57.
  17. ^ Gabbrielli & Martini 2023, p. 525.
  18. ^ Gabbrielli & Martini 2023, pp. 526–527.
  19. ^ Gabbrielli & Martini 2023, p. 531.
  20. ^ a b Sebesta 2012, p. 79.
  21. ^ Gabbrielli & Martini 2023, p. 530.
  22. ^ Gabbrielli & Martini 2023, pp. 532–533.
  23. ^ Gabbrielli & Martini 2023, p. 534.
  24. ^ Gabbrielli & Martini 2023, pp. 534–535.
  25. ^ Gabbrielli & Martini 2023, p. 535.
  26. ^ Sebesta 2012, p. 736.
  27. ^ Gabbrielli & Martini 2023, p. 536.
  28. ^ Gabbrielli & Martini 2023, pp. 536–537.
  29. ^ Sebesta 2012, pp. 91–92.
  30. ^ Gabbrielli & Martini 2023, pp. 538–539.
  31. ^ Sebesta 2012, pp. 97–99.
  32. ^ Gabbrielli & Martini 2023, p. 542.
  33. ^ Gabbrielli & Martini 2023, pp. 474–475, 477, 542.
  34. ^ Gabbrielli & Martini 2023, pp. 542–543.
  35. ^ Gabbrielli & Martini 2023, p. 544.

Also, add the following source to the "further reading" section:

Reasons: add references, improve summary style, remove unsourced text, fix some MOS:CURRENT issues Buidhe paid (talk) 20:08, 28 January 2024 (UTC)[reply]

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