# Computer programming

> Mediated Wiki article. Canonical URL: https://mediated.wiki/source/Computer_programming
> Markdown URL: https://mediated.wiki/source/Computer_programming.md
> Source: https://en.wikipedia.org/wiki/Computer_programming
> Source revision: 1353833130
> License: Creative Commons Attribution-ShareAlike 4.0 International (https://creativecommons.org/licenses/by-sa/4.0/)

Process to create executable computer programs

Part of a series on Software development Core activities Data modeling Processes Requirements Design Construction Engineering Testing Debugging Deployment Maintenance Paradigms, models Agile Cleanroom Incremental Prototyping Spiral V model Waterfall Methodologies, frameworks ASD DAD DevOps DSDM FDD IID Kanban Lean SD LeSS MDE MSF PSP RAD RUP SAFe Scrum SEMAT TDD TSP UP XP Supporting disciplines Configuration management Deployment management Documentation Project management Quality assurance User experience Practices ATDD BDD CCO CD CI DDD PP SBE Stand-up TDD XP Tools Build automation Compiler Debugger GUI builder IDE Infrastructure as code Profiler Release automation UML modeling Standards, bodies of knowledge CMMI IEEE standards IREB ISO 9001 ISO/IEC standards ITIL OMG PMBOK SWEBOK Glossaries Artificial intelligence Computer science Electrical and electronics engineering Outlines Software development Computer programming Programming languages C C++ C# Java JavaScript Perl Python Rust v t e

**Computer programming** or **coding** is the composition of sequences of instructions, called [programs](/source/Computer_program), that [computers](/source/Computer) can follow to perform tasks.[1][2] It involves designing and implementing [algorithms](/source/Algorithm), step-by-step specifications of procedures, by writing [code](/source/Source_code) in one or more [programming languages](/source/Programming_language). [Programmers](/source/Programmer) typically use [high-level programming languages](/source/High-level_programming_language) that are more easily intelligible to humans than [machine code](/source/Machine_code), which is directly executed by the [central processing unit](/source/Central_processing_unit). Proficient programming usually requires expertise in several different subjects, including knowledge of the [application domain](/source/Domain_(software_engineering)), details of programming languages and generic code [libraries](/source/Library_(computing)), specialized algorithms, and [formal logic](/source/Logic#Formal_logic).

Auxiliary tasks accompanying and related to programming include [analyzing requirements](/source/Requirements_analysis), [testing](/source/Software_testing), [debugging](/source/Debugging_tool) (investigating and fixing problems), implementation of [build systems](/source/Build_automation), and management of derived [artifacts](/source/Artifact_(software_development)), such as programs' [machine code](/source/Machine_code). While these are sometimes considered programming, often the term *[software development](/source/Software_development)* is used for this larger overall process – with the terms *programming*, *implementation*, and *coding* reserved for the writing and editing of code per se. Sometimes software development is known as *[software engineering](/source/Software_engineering)*, especially when it employs [formal methods](/source/Formal_methods) or follows an [engineering design process](/source/Engineering_design_process).

## History

[Ada Lovelace](/source/Ada_Lovelace), whose notes were added to the end of [Luigi Menabrea](/source/Luigi_Menabrea)'s paper included the first [algorithm](/source/Algorithm) designed for processing by [Charles Babbage](/source/Charles_Babbage)'s [Analytical Engine](/source/Analytical_Engine). She is often recognized as history's first computer programmer.

See also: [Computer program § History](/source/Computer_program#History), [Programmer § History](/source/Programmer#History), and [History of programming languages](/source/History_of_programming_languages)

[Programmable devices](/source/Program_(machine)) have existed for centuries. As early as the 9th century, a programmable [music sequencer](/source/Music_sequencer) was invented by the Persian [Banu Musa](/source/Banu_Musa) brothers, who described an automated mechanical [flute](/source/Flute) player in the *[Book of Ingenious Devices](/source/Book_of_Ingenious_Devices)*.[3][4] In 1206, the Arab engineer [Al-Jazari](/source/Al-Jazari) invented a programmable [drum machine](/source/Drum_machine) where a musical mechanical [automaton](/source/Automaton) could be made to play different rhythms and drum patterns, via pegs and [cams](/source/Cam_(mechanism)).[5][6] In 1801, the [Jacquard loom](/source/Jacquard_loom) could produce entirely different weaves by changing the "program" – a series of [pasteboard](/source/Card_stock) cards with holes punched in them.

[Code-breaking](/source/Code-breaking) algorithms have also existed for centuries. In the 9th century, the [Arab mathematician](/source/Mathematics_in_medieval_Islam) [Al-Kindi](/source/Al-Kindi) described a [cryptographic](/source/Cryptographic) algorithm for deciphering encrypted code, in *A Manuscript on Deciphering Cryptographic Messages*. He gave the first description of [cryptanalysis](/source/Cryptanalysis) by [frequency analysis](/source/Frequency_analysis), the earliest code-breaking algorithm.[7]

The first [computer program](/source/Computer_program) is generally dated to 1843 when mathematician [Ada Lovelace](/source/Ada_Lovelace) published an [algorithm](/source/Algorithm) to calculate a sequence of [Bernoulli numbers](/source/Bernoulli_numbers), intended to be carried out by [Charles Babbage](/source/Charles_Babbage)'s [Analytical Engine](/source/Analytical_Engine).[8] The algorithm, which was conveyed through notes on a translation of Luigi Federico Menabrea's paper on the analytical engine was mainly conceived by Lovelace as can be discerned through her correspondence with Babbage. However, Charles Babbage himself had written a program for the AE in 1837.[9][10] Lovelace was also the first to see a broader application for the analytical engine beyond mathematical calculations.

Data and instructions were once stored on external [punched cards](/source/Punched_card), which were kept in order and arranged in program decks.

In the 1880s, [Herman Hollerith](/source/Herman_Hollerith) invented the concept of storing *data* in machine-readable form.[11] Later a [control panel](/source/Plugboard) (plug board) added to his 1906 Type I Tabulator allowed it to be programmed for different jobs, and by the late 1940s, [unit record equipment](/source/Unit_record_equipment) such as the [IBM 602](/source/IBM_602) and [IBM 604](/source/IBM_604), were programmed by control panels in a similar way, as were the first [electronic computers](/source/Electronic_computer). However, with the concept of the [stored-program computer](/source/Stored-program_computer) introduced in 1949, both programs and data were stored and manipulated in the same way in [computer memory](/source/Computer_memory).[12] Hands-on programming courses that integrate hardware and software have been shown to improve retention and engagement among first-year engineering students.[13]

### Machine language

[Machine code](/source/Machine_code) was the language of early programs, written in the [instruction set](/source/Instruction_set_architecture) of the particular machine, often in [binary](/source/Binary_numeral_system) notation. Soon, [assembly languages](/source/Assembly_language) were developed, allowing programmers to write instructions in a textual format (e.g., ADD X, TOTAL), using abbreviations for operation codes and meaningful names for memory addresses. However, because an assembly language is little more than a different notation for a machine language, two machines with [different instruction sets](/source/Comparison_of_instruction_set_architectures) also have different assembly languages.

Wired [control panel](/source/Plugboard) for an [IBM 402 Accounting Machine](/source/IBM_402_Accounting_Machine). Wires connect pulse streams from the card reader to counters and other internal logic and ultimately to the printer.

### Compiler languages

See also: [Compiler](/source/Compiler)

[High-level languages](/source/High-level_language) made the process of developing a program simpler and more understandable, and less bound to the underlying [hardware](/source/Computer_hardware). The first compiler related tool, the [A-0 System](/source/A-0_System), was developed in 1952[14] by [Grace Hopper](/source/Grace_Hopper), who also coined the term 'compiler'.[15][16] [FORTRAN](/source/FORTRAN), the first widely used high-level language to have a functional implementation, came out in 1957,[17] and many other languages were soon developed—in particular, [COBOL](/source/COBOL) aimed at commercial data processing, and [Lisp](/source/Lisp_(programming_language)) for computer research.

These compiled languages allow the programmer to write programs in terms that are syntactically richer, and more capable of [abstracting](/source/Abstraction_(computer_science)) the code, making it easy to target varying machine instruction sets via compilation declarations and [heuristics](/source/Heuristic_(computer_science)). Compilers harnessed the power of computers to make programming easier[17] by allowing programmers to specify calculations by entering a formula using [infix notation](/source/Infix_notation).

### Source code entry

See also: [Computer programming in the punched card era](/source/Computer_programming_in_the_punched_card_era)

Programs were mostly entered using punched cards or [paper tape](/source/Paper_tape). By the late 1960s, [data storage devices](/source/Data_storage_device) and [computer terminals](/source/Computer_terminal) became inexpensive enough that programs could be created by typing directly into the computers. [Text editors](/source/Text_editor) were also developed that allowed changes and corrections to be made much more easily than with [punched cards](/source/Punched_card_sorter).

## Modern programming

### Quality requirements

Main article: [Software quality](/source/Software_quality)

Whatever the approach to development may be, the final program must satisfy some fundamental properties. The following properties are among the most important:[18] [19]

- [Reliability](/source/Reliability_engineering#Software_reliability): how often the results of a program are correct. This depends on conceptual correctness of algorithms and minimization of programming mistakes, such as mistakes in resource management (e.g., [buffer overflows](/source/Buffer_overflow) and [race conditions](/source/Race_condition)) and logic errors (such as division by zero or [off-by-one errors](/source/Off-by-one_error)).

- [Robustness](/source/Robustness_(computer_science)): how well a program anticipates problems due to errors (not bugs). This includes situations such as incorrect, inappropriate or corrupt data, unavailability of needed resources such as memory, operating system services, and network connections, user error, and unexpected power outages.

- [Usability](/source/Usability): the [ergonomics](/source/Ergonomics) of a program: the ease with which a person can use the program for its intended purpose or in some cases even unanticipated purposes. Such issues can make or break its success even regardless of other issues. This involves a wide range of textual, graphical, and sometimes hardware elements that improve the clarity, intuitiveness, cohesiveness, and completeness of a program's user interface.

- [Portability](/source/Software_portability): the range of [computer hardware](/source/Computer_hardware) and [operating system](/source/Operating_system) platforms on which the source code of a program can be [compiled](/source/Compiled)/[interpreted](/source/Interpreter_(computing)) and run. This depends on differences in the programming facilities provided by the different platforms, including hardware and operating system resources, expected behavior of the hardware and operating system, and availability of platform-specific compilers (and sometimes libraries) for the language of the source code.

- [Maintainability](/source/Maintainability): the ease with which a program can be modified by its present or future developers in order to make improvements or to customize, fix [bugs](/source/Software_bug) and [security holes](/source/Vulnerability_(computing)), or adapt it to new environments. Good practices[20] during initial development make the difference in this regard. This quality may not be directly apparent to the end user but it can significantly affect the fate of a program over the long term.

- [Efficiency](/source/Algorithmic_efficiency)/[performance](/source/Performance_engineering): Measure of system resources a program consumes (processor time, memory space, slow devices such as disks, network bandwidth and to some extent even user interaction): the less, the better. This also includes careful management of resources, for example cleaning up [temporary files](/source/Temporary_file) and eliminating [memory leaks](/source/Memory_leak). This is often discussed under the shadow of a chosen programming language. Although the language certainly affects performance, even slower languages, such as [Python](/source/Python_(programming_language)), can execute programs instantly from a human perspective. Speed, resource usage, and performance are important for programs that [bottleneck](/source/Bottleneck_(software)) the system, but efficient use of programmer time is also important and is related to cost: more hardware may be cheaper.

Using [automated tests](/source/Test_automation) and [fitness functions](/source/Fitness_function) can help to maintain some of the aforementioned attributes.[21]

### Readability of source code

In computer programming, [readability](/source/Readability) refers to the ease with which a human reader can comprehend the purpose, [control flow](/source/Control_flow), and operation of [source code](/source/Source_code). It affects the aspects of quality above, including portability, usability and most importantly maintainability.

Source code in integrated development environment

Readability is important because programmers spend the majority of their time reading, trying to understand, reusing, and modifying existing source code, rather than writing new source code. Unreadable code often leads to bugs, inefficiencies, and [duplicated code](/source/Code_duplication). A study found that a few simple readability transformations made code shorter and drastically reduced the time to understand it.[22]

Following a consistent [programming style](/source/Programming_style) often helps readability. However, readability is more than just programming style. Many factors, having little or nothing to do with the ability of the computer to efficiently compile and execute the code, contribute to readability.[23] Some of these factors include:

- Different [indent styles](/source/Indent_style) (whitespace)

- [Comments](/source/Comment_(computer_programming))

- [Decomposition](/source/Decomposition_(computer_science))

- [Naming conventions](/source/Naming_conventions_(programming)) for objects (such as variables, classes, functions, procedures, etc.)

The [presentation](/source/Separation_of_presentation_and_content) aspects of this (such as indents, line breaks, color highlighting, and so on) are often handled by the [source code editor](/source/Source_code_editor), but the content aspects reflect the programmer's talent and skills.

Various [visual programming languages](/source/Visual_programming_language) have also been developed with the intent to resolve readability concerns by adopting non-traditional approaches to code structure and display. [Integrated development environments](/source/Integrated_development_environment) (IDEs) aim to integrate all such help. Techniques like [Code refactoring](/source/Code_refactoring) can enhance readability.

### Algorithmic complexity

The academic field and the engineering practice of computer programming are concerned with discovering and implementing the most efficient algorithms for a given class of problems. For this purpose, algorithms are classified into *orders* using [Big O notation](/source/Big_O_notation), which expresses resource use—such as execution time or memory consumption—in terms of the size of an input. Expert programmers are familiar with a variety of well-established algorithms and their respective complexities and use this knowledge to choose algorithms that are best suited to the circumstances.

### Methodologies

The first step in most formal software development processes is [requirements analysis](/source/Requirements_analysis), followed by testing to determine value modeling, implementation, and failure elimination (debugging). There exist a lot of different approaches for each of those tasks. One approach popular for requirements analysis is [Use Case](/source/Use_Case) analysis. Many programmers use forms of [Agile software development](/source/Agile_software_development) where the various stages of formal software development are more integrated together into short cycles that take a few weeks rather than years. There are many approaches to the Software development process.

Popular modeling techniques include Object-Oriented Analysis and Design ([OOAD](/source/OOAD)) and Model-Driven Architecture ([MDA](/source/Model-Driven_Architecture)). The Unified Modeling Language ([UML](/source/Unified_Modeling_Language)) is a notation used for both the OOAD and MDA.

A similar technique used for database design is Entity-Relationship Modeling ([ER Modeling](/source/Entity-Relationship_Model)).

Implementation techniques include imperative languages ([object-oriented](/source/Object-oriented_programming) or [procedural](/source/Procedural_programming)), [functional languages](/source/Functional_programming), and [logic programming](/source/Logic_programming) languages.

### Measuring language usage

It is very difficult to determine what are the most popular modern programming languages. Methods of measuring programming language popularity include: counting the number of job advertisements that mention the language,[24] the number of books sold and courses teaching the language (this overestimates the importance of newer languages), and estimates of the number of existing lines of code written in the language (this underestimates the number of users of business languages such as COBOL).

Some languages are popular for writing particular kinds of applications, while other languages are used to write many different kinds of applications. For example, [COBOL](/source/COBOL) is still prevalent in corporate data centers[25] often on large [mainframe computers](/source/Mainframe_computer), [Fortran](/source/Fortran) in engineering applications, [scripting languages](/source/Scripting_language) in [Web](/source/World_Wide_Web) development, and [C](/source/C_(programming_language)) in [embedded software](/source/Embedded_software). Many applications use a mix of several languages in their construction and use. New languages are generally designed around the syntax of a prior language with new functionality added, (for example [C++](/source/C%2B%2B) adds object-orientation to C, and [Java](/source/Java_(programming_language)) adds memory management and [bytecode](/source/Bytecode) to C++, but as a result, loses efficiency and the ability for low-level manipulation).

### Debugging

Main article: [Debugging](/source/Debugging)

The first known actual bug causing a problem in a computer was a moth, trapped inside a Harvard mainframe, recorded in a log book entry dated September 9, 1947.[26] "Bug" was already a common term for a software defect when this insect was found.

Debugging is a very important task in the software development process since having defects in a program can have significant consequences for its users. Some languages are more prone to some kinds of faults because their specification does not require compilers to perform as much checking as other languages. Use of a [static code analysis](/source/Static_code_analysis) tool can help detect some possible problems. Normally the first step in debugging is to attempt to reproduce the problem. This can be a non-trivial task, for example as with parallel processes or some unusual software bugs. Also, specific user environment and usage history can make it difficult to reproduce the problem.

After the bug is reproduced, the input of the program may need to be simplified to make it easier to debug. For example, when a bug in a compiler can make it crash when [parsing](/source/Parsing) some large source file, a simplification of the test case that results in only few lines from the original source file can be sufficient to reproduce the same crash. Trial-and-error/divide-and-conquer is needed: the programmer will try to remove some parts of the original test case and check if the problem still exists. When debugging the problem in a GUI, the programmer can try to skip some user interaction from the original problem description and check if the remaining actions are sufficient for bugs to appear. Scripting and [breakpointing](/source/Breakpoint) are also part of this process.

Debugging is often done with [IDEs](/source/Integrated_development_environment). Standalone debuggers like [GDB](/source/GDB) are also used, and these often provide less of a visual environment, usually using a [command line](/source/Command_line). Some text editors such as [Emacs](/source/Emacs) allow GDB to be invoked through them, to provide a visual environment. One study found that teaching structured languages such as Pascal improved novice programmers’ debugging accuracy and overall comprehension.[27]

## Programming languages

Main articles: [Programming language](/source/Programming_language) and [List of programming languages](/source/List_of_programming_languages)

See also: [Computer program § Languages](/source/Computer_program#Languages), and [List of open-source programming languages](/source/List_of_open-source_programming_languages)

Different programming languages support different styles of programming (called *[programming paradigms](/source/Programming_paradigm)*). The choice of language used is subject to many considerations, such as company policy, suitability to task, availability of third-party packages, or individual preference. Ideally, the programming language best suited for the task at hand will be selected. Trade-offs from this ideal involve finding enough programmers who know the language to build a team, the availability of compilers for that language, and the efficiency with which programs written in a given language execute. Languages form an approximate spectrum from "low-level" to "high-level"; "low-level" languages are typically more machine-oriented and faster to execute, whereas "high-level" languages are more abstract and easier to use but execute less quickly. It is usually easier to code in "high-level" languages than in "low-level" ones. Programming languages are essential for software development. They are the building blocks for all software, from the simplest applications to the most sophisticated ones.

[Allen Downey](/source/Allen_Downey), in his book *How To Think Like A Computer Scientist*, writes:

- The details look different in different languages, but a few basic instructions appear in just about every language: - Input: Gather data from the keyboard, a file, or some other device. - Output: Display data on the screen or send data to a file or other device. - Arithmetic: Perform basic arithmetical operations like addition and multiplication. - Conditional Execution: Check for certain conditions and execute the appropriate sequence of statements. - Repetition: Perform some action repeatedly, usually with some variation.

Many computer languages provide a mechanism to call functions provided by [shared libraries](/source/Shared_library). Provided the functions in a library follow the appropriate run-time conventions (e.g., method of passing [arguments](/source/Argument_(computer_science))), then these functions may be written in any other language. Annual rankings by IEEE Spectrum analyze programming language popularity using metrics such as job postings, search trends, and developer activity.[28]

## Learning to program

See also: [Computing education](/source/Computing_education) and [List of computer books](/source/List_of_computer_books)

Learning to program has a long history related to professional standards and practices, academic initiatives and curriculum, and commercial books and materials for students, self-taught learners, hobbyists, and others who desire to create or customize software for personal use. Since the 1960s, learning to program has taken on the characteristics of a *popular movement*, with the rise of academic disciplines, inspirational leaders, collective identities, and strategies to grow the movement and make institutionalize change.[29] Through these social ideals and educational agendas, learning to code has become important not just for scientists and engineers, but for millions of citizens who have come to believe that creating software is beneficial to society and its members. Computer science education participation has expanded significantly in recent years, with millions of students gaining introductory programming experience through schools and online platforms.[30]

### Context

In 1957, there were approximately 15,000 computer programmers employed in the U.S., a figure that accounts for 80% of the world's active developers. In 2014, there were approximately 18.5 million professional programmers in the world, of which 11 million can be considered professional and 7.5 million student or hobbyists.[31] Before the rise of the commercial Internet in the mid-1990s, most programmers learned about software construction through books, magazines, user groups, and informal instruction methods, with academic coursework and corporate training playing important roles for professional workers.[32]

The first book containing specific instructions about how to program a computer may have been [Maurice Wilkes](/source/Maurice_Wilkes), [David Wheeler](/source/David_Wheeler_(computer_scientist)), and [Stanley Gill's](/source/Stanley_Gill) *Preparation of Programs for an Electronic Digital Computer* (1951). The book offered a selection of common subroutines for handling basic operations on the EDSAC, one of the world's first stored-program computers.

When high-level languages arrived, they were introduced by numerous books and materials that explained language keywords, managing program flow, working with data, and other concepts. These languages included [FLOW-MATIC](/source/FLOW-MATIC), COBOL, FORTRAN, [ALGOL](/source/ALGOL), [Pascal](/source/Pascal_(programming_language)), [BASIC](/source/BASIC), and C. An example of an early programming primer from these years is [Marshal H. Wrubel's](/source/Marshal_Henry_Wrubel) *A Primer of Programming for Digital Computers* (1959), which included step-by-step instructions for filling out coding sheets, creating punched cards, and using the keywords in IBM's early FORTRAN system.[33] [Daniel McCracken's](/source/Daniel_McCracken) *A Guide to FORTRAN Programming* (1961) presented FORTRAN to a larger audience, including students and office workers.

In 1961, [Alan Perlis](/source/Alan_Perlis) suggested that all university freshmen at Carnegie Technical Institute take a course in computer programming.[34] His advice was published in the popular technical journal *Computers and Automation*, which became a regular source of information for professional programmers.

Programmers soon had a range of learning texts at their disposal. *Programmer's references* listed keywords and functions related to a language, often in alphabetical order, as well as technical information about compilers and related systems. An early example was IBM's *Programmers' Reference Manual: the FORTRAN Automatic Coding System for the IBM 704 EDPM* (1956).

Over time, the genre of *programmer's guides* emerged, which presented the features of a language in tutorial or step by step format. Many early primers started with a program known as ["Hello, World"](/source/Helloworld), which presented the shortest program a developer could create in a given system. Programmer's guides then went on to discuss core topics like declaring variables, data types, formulas, flow control, user-defined functions, manipulating data, and other topics.

Early and influential programmer's guides included [John G. Kemeny](/source/John_G._Kemeny) and [Thomas E. Kurtz's](/source/Thomas_E._Kurtz) *BASIC Programming* (1967), Kathleen Jensen and [Niklaus Wirth's](/source/Niklaus_Wirth) *The Pascal User Manual and Report* (1971), and [Brian W. Kernighan](/source/Brian_W._Kernighan) and [Dennis Ritchie's](/source/Dennis_Ritchie) *The C Programming Language* (1978). Similar books for popular audiences (but with a much lighter tone) included [Bob Albrecht's](/source/Bob_Albrecht) *My Computer Loves Me When I Speak BASIC* (1972), Al Kelley and Ira Pohl's *A Book on C* (1984), and [Dan Gookin's](/source/Dan_Gookin) *C for Dummies* (1994).

Beyond language-specific primers, there were numerous books and academic journals that introduced professional programming practices. Many were designed for university courses in computer science, software engineering, or related disciplines. [Donald Knuth's](/source/Donald_Knuth) *[The Art of Computer Programming](/source/The_Art_of_Computer_Programming)* (1968 and later), presented hundreds of computational algorithms and their analysis. *The Elements of Programming Style* (1974), by Brian W. Kernighan and [P. J. Plauger](/source/P._J._Plauger), concerned itself with programming *style*, the idea that programs should be written not only to satisfy the compiler but human readers. [Jon Bentley's](/source/Jon_Bentley_(computer_scientist)) *Programming Pearls* (1986) offered practical advice about the art and craft of programming in professional and academic contexts. Texts specifically designed for students included Doug Cooper and Michael Clancy's *Oh Pascal!* (1982), [Alfred Aho's](/source/Alfred_Aho) *Data Structures and Algorithms* (1983), and Daniel Watt's *Learning with Logo* (1983).

### Technical publishers

As personal computers became mass-market products, thousands of trade books and magazines sought to teach professional, hobbyist, and casual users to write computer programs. A sample of these learning resources includes *BASIC Computer Games, Microcomputer Edition* (1978), by [David Ahl](/source/David_Ahl); *Programming the Z80* (1979), by [Rodnay Zaks](/source/Rodnay_Zaks); *Programmer's CP/M Handbook* (1983), by [Andy Johnson-Laird](/source/Andy_Johnson-Laird); *C Primer Plus* (1984), by [Mitchell Waite](/source/Mitchell_Waite) and The Waite Group; *The Peter Norton Programmer's Guide to the IBM PC* (1985), by [Peter Norton](/source/Peter_Norton); *Advanced MS-DOS* (1986), by Ray Duncan; *[Learn BASIC Now](/source/Learn_BASIC_Now)* (1989), by [Michael Halvorson](/source/Michael_Halvorson) and David Rygymr; *Programming Windows* (1992 and later), by [Charles Petzold](/source/Charles_Petzold); *Code Complete: A Practical Handbook for Software Construction* (1993), by [Steve McConnell](/source/Steve_McConnell); and *Tricks of the Game-Programming Gurus* (1994), by [André LaMothe](/source/Andre_LaMothe).

The PC software industry spurred the creation of numerous book publishers that offered programming primers and tutorials, as well as books for advanced software developers.[35] These publishers included [Addison-Wesley](/source/Addison-Wesley), [IDG](/source/IDG), [Macmillan Inc.](/source/Macmillan_Inc.), [McGraw-Hill](/source/McGraw-Hill), [Microsoft Press](/source/Microsoft_Press), [O'Reilly Media](/source/O'Reilly_Media), [Prentice Hall](/source/Prentice_Hall), Sybex, Ventana Press, Waite Group Press, [Wiley](/source/Wiley_(publisher)), [Wrox Press](/source/Wrox_Press), and [Ziff-Davis](/source/Ziff-Davis).

[Computer magazines](/source/Computer_magazine) and journals also provided learning content for professional and hobbyist programmers. A partial list of these resources includes *[Amiga World](/source/Amiga_World)*, *[Byte (magazine)](/source/Byte_(magazine))*, *[Communications of the ACM](/source/Communications_of_the_ACM)*, *[Computer (magazine)](/source/Computer_(magazine))*, *[Compute!](/source/Compute!)*, *Computer Language (magazine)*, *[Computers and Electronics](/source/Computers_and_Electronics)*, *[Dr. Dobb's Journal](/source/Dr._Dobb's_Journal)*, *[IEEE Software](/source/IEEE_Software)*, *[Macworld](/source/Macworld)*, *[PC Magazine](/source/PC_Magazine)*, *[PC/Computing](/source/PC%2FComputing)*, and *[UnixWorld](/source/UnixWorld)*.

### Digital learning / online resources

See also: [List of online integrated development environments](/source/Online_integrated_development_environment) and [List of educational software for computer programming](/source/List_of_educational_software#Computer_science)

Between 2000 and 2010, computer book and magazine publishers declined significantly as providers of programming instruction, as programmers moved to Internet resources to expand their access to information. This shift brought forward new digital products and mechanisms to learn programming skills. During the transition, digital books from publishers transferred information that had traditionally been delivered in print to new and expanding audiences.[36]

Important Internet resources for learning to code included blogs, books,[37] wikis, videos, online databases, journals,[38][39] subscription sites, conference papers.[40] and custom websites focused on coding skills. In recent years, platforms like [LeetCode](https://leetcode.com/), [HackerRank](https://www.hackerrank.com/), and [freeCodeCamp](https://www.freecodecamp.org/) have become popular for learning programming, practicing coding challenges, and preparing for technical interviews. New commercial resources included [YouTube](/source/YouTube) videos, Lynda.com tutorials (later [LinkedIn Learning](/source/LinkedIn_Learning)), [Khan Academy](/source/Khan_Academy), [Codecademy](/source/Codecademy), [GitHub](/source/GitHub), [W3Schools](/source/W3Schools), [Codewars](/source/Codewars), and numerous [coding bootcamps](/source/Coding_bootcamp).

Most software development systems and [game engines](/source/Game_engine) included rich online help resources, including [integrated development environments](/source/Integrated_development_environment) (IDEs), [context-sensitive help](/source/Context-sensitive_help), [APIs](/source/API), and other digital resources. Commercial [software development kits](/source/Software_development_kit) (SDKs) also provided a collection of software development tools and documentation in one installable package.

Commercial and non-profit organizations published learning websites for developers, created blogs, and established news feeds and social media resources about programming. Corporations like [Apple](/source/Apple_Inc.), [Microsoft](/source/Microsoft), [Oracle](/source/Oracle_Corporation), [Google](/source/Google), and [Amazon](/source/Amazon_(company)) built corporate websites providing support for programmers, including resources like the [Microsoft Developer Network](/source/Microsoft_Developer_Network) (MSDN). Contemporary movements like Hour of Code ([Code.org](/source/Code.org)) show how learning to program has become associated with digital learning strategies, education agendas, and corporate philanthropy.

## Programmers

Main articles: [Programmer](/source/Programmer) and [Software engineer](/source/Software_engineer)

Computer programmers are those who write computer software. Their jobs usually involve:

- Prototyping

- Coding

- Debugging

- [Documentation](/source/Documentation)

- [Integration](/source/System_integration)

- [Maintenance](/source/Software_maintenance)

- Requirements analysis

- [Software architecture](/source/Software_architecture)

- Software testing

- [Specification](/source/Specification)

Although programming has been presented in the media as a somewhat mathematical subject, some research shows that good programmers have strong skills in natural human languages, and that learning to code is similar to learning a foreign language.[41][42]

## See also

- [Computer programming portal](https://en.wikipedia.org/wiki/Portal:Computer_programming)

Main article: [Outline of computer programming](/source/Outline_of_computer_programming)

- [Code smell](/source/Code_smell)

- [Computer networking](/source/Computer_network)

- [Competitive programming](/source/Competitive_programming)

- [List of software programming journals](/source/List_of_software_programming_journals)

- [List of free and open-source software packages for programming](/source/List_of_free_and_open-source_software_packages#Programming_language_support)

- [Lists of programming software development tools](/source/Lists_of_programming_software_development_tools)

- [Programming best practices](/source/Programming_best_practices)

- [Systems programming](/source/Systems_programming)

- [Wikibooks computer programming resources](https://en.wikibooks.org/wiki/Category:Subject:Computer_programming)

## References

1. **[^](#cite_ref-1)** Bebbington, Shaun (2014). ["What is coding"](https://yearofcodes.tumblr.com/what-is-coding). *Tumblr*. [Archived](https://web.archive.org/web/20200429195646/https://yearofcodes.tumblr.com/what-is-coding) from the original on April 29, 2020. Retrieved March 3, 2014.

1. **[^](#cite_ref-2)** Bebbington, Shaun (2014). ["What is programming"](https://yearofcodes.tumblr.com/what-is-programming). *Tumblr*. [Archived](https://web.archive.org/web/20200429195958/https://yearofcodes.tumblr.com/what-is-programming) from the original on April 29, 2020. Retrieved March 3, 2014.

1. **[^](#cite_ref-Koetsier_3-0)** Koetsier, Teun (2001). "On the prehistory of programmable machines: musical automata, looms, calculators". *Mechanism and Machine Theory*. **36** (5). Elsevier: 589–603. [doi](/source/Doi_(identifier)):[10.1016/S0094-114X(01)00005-2](https://doi.org/10.1016%2FS0094-114X%2801%2900005-2).

1. **[^](#cite_ref-4)** Kapur, Ajay; Carnegie, Dale; Murphy, Jim; Long, Jason (2017). ["Loudspeakers Optional: A history of non-loudspeaker-based electroacoustic music"](https://doi.org/10.1017%2FS1355771817000103). *[Organised Sound](/source/Organised_Sound)*. **22** (2). [Cambridge University Press](/source/Cambridge_University_Press): 195–205. [doi](/source/Doi_(identifier)):[10.1017/S1355771817000103](https://doi.org/10.1017%2FS1355771817000103). [ISSN](/source/ISSN_(identifier)) [1355-7718](https://search.worldcat.org/issn/1355-7718).

1. **[^](#cite_ref-5)** Fowler, Charles B. (October 1967). "The Museum of Music: A History of Mechanical Instruments". *Music Educators Journal*. **54** (2): 45–49. [doi](/source/Doi_(identifier)):[10.2307/3391092](https://doi.org/10.2307%2F3391092). [JSTOR](/source/JSTOR_(identifier)) [3391092](https://www.jstor.org/stable/3391092). [S2CID](/source/S2CID_(identifier)) [190524140](https://api.semanticscholar.org/CorpusID:190524140).

1. **[^](#cite_ref-Sharkey_6-0)** [Noel Sharkey](/source/Noel_Sharkey) (2007), [A 13th Century Programmable Robot](https://web.archive.org/web/20070629182810/http://www.shef.ac.uk/marcoms/eview/articles58/robot.html), [University of Sheffield](/source/University_of_Sheffield)

1. **[^](#cite_ref-7)** Dooley, John F. (2013). *A Brief History of Cryptology and Cryptographic Algorithms*. Springer Science & Business Media. pp. 12–3. [ISBN](/source/ISBN_(identifier)) [9783319016283](https://en.wikipedia.org/wiki/Special:BookSources/9783319016283).

1. **[^](#cite_ref-IEEE_8-0)** Fuegi, J.; Francis, J. (2003). "Lovelace & Babbage and the Creation of the 1843 'notes'". *IEEE Annals of the History of Computing*. **25** (4): 16. [Bibcode](/source/Bibcode_(identifier)):[2003IAHC...25d..16F](https://ui.adsabs.harvard.edu/abs/2003IAHC...25d..16F). [doi](/source/Doi_(identifier)):[10.1109/MAHC.2003.1253887](https://doi.org/10.1109%2FMAHC.2003.1253887).

1. **[^](#cite_ref-IEEE2021_9-0)** Rojas, R. (2021). "The Computer Programs of Charles Babbage". *IEEE Annals of the History of Computing*. **43** (1): 6–18. [Bibcode](/source/Bibcode_(identifier)):[2021IAHC...43a...6R](https://ui.adsabs.harvard.edu/abs/2021IAHC...43a...6R). [doi](/source/Doi_(identifier)):[10.1109/MAHC.2020.3045717](https://doi.org/10.1109%2FMAHC.2020.3045717).

1. **[^](#cite_ref-IEEE2024_10-0)** Rojas, R. (2024). ["The First Computer Program"](https://refubium.fu-berlin.de/bitstream/fub188/44090/1/3624731.pdf) (PDF). *Communications of the ACM*. **67** (6): 78–81. [doi](/source/Doi_(identifier)):[10.1145/3624731](https://doi.org/10.1145%2F3624731).

1. **[^](#cite_ref-11)** da Cruz, Frank (March 10, 2020). ["Columbia University Computing History – Herman Hollerith"](http://www.columbia.edu/acis/history/hollerith.html). *Columbia University*. Columbia.edu. [Archived](https://web.archive.org/web/20200429210742/http://www.columbia.edu/cu/computinghistory/hollerith.html) from the original on April 29, 2020. Retrieved April 25, 2010.

1. **[^](#cite_ref-12)** ["Memory & Storage | Timeline of Computer History | Computer History Museum"](https://www.computerhistory.org/timeline/memory-storage/). *www.computerhistory.org*. [Archived](https://web.archive.org/web/20210527071533/https://www.computerhistory.org/timeline/memory-storage/) from the original on May 27, 2021. Retrieved June 3, 2021.

1. **[^](#cite_ref-13)** Lumpp, Janet K.; Lovely, Jennifer; Letellier, Laura M.P.E. (2019). [*Instructional use of computers in a hands-on programming course for first-year engineering students*](https://scholars.uky.edu/en/publications/instructional-use-of-computers-in-a-hands-on-programming-course-f/). ASEE Annual Conference and Exposition.

1. **[^](#cite_ref-14)** Ridgway, Richard (1952). "Compiling routines". *Proceedings of the 1952 ACM national meeting (Toronto) on - ACM '52*. pp. 1–5. [doi](/source/Doi_(identifier)):[10.1145/800259.808980](https://doi.org/10.1145%2F800259.808980). [ISBN](/source/ISBN_(identifier)) [9781450379250](https://en.wikipedia.org/wiki/Special:BookSources/9781450379250). [S2CID](/source/S2CID_(identifier)) [14878552](https://api.semanticscholar.org/CorpusID:14878552). {{[cite book](https://en.wikipedia.org/wiki/Template:Cite_book)}}: ISBN / Date incompatibility ([help](https://en.wikipedia.org/wiki/Help:CS1_errors#invalid_isbn_date))

1. **[^](#cite_ref-wikles1968_15-0)** [Maurice V. Wilkes](/source/Maurice_V._Wilkes). 1968. Computers Then and Now. Journal of the Association for Computing Machinery, 15(1):1–7, January. p. 3 (a comment in brackets added by editor), "(I do not think that the term compiler was then [1953] in general use, although it had in fact been introduced by Grace Hopper.)"

1. **[^](#cite_ref-computerhistory.org_16-0)** [\[1\]](http://www.computerhistory.org/events/lectures/cobol_06121997/index.shtml) The World's First COBOL Compilers [Archived](https://web.archive.org/web/20111013021915/http://www.computerhistory.org/events/lectures/cobol_06121997/index.shtml) 13 October 2011 at the [Wayback Machine](/source/Wayback_Machine)

1. ^ [***a***](#cite_ref-bergstein_17-0) [***b***](#cite_ref-bergstein_17-1) Bergstein, Brian (March 20, 2007). ["Fortran creator John Backus dies"](https://www.nbcnews.com/id/wbna17704662). *NBC News*. [Archived](https://web.archive.org/web/20200429211030/http://www.nbcnews.com/id/17704662) from the original on April 29, 2020. Retrieved April 25, 2010.

1. **[^](#cite_ref-18)** ["NIST To Develop Cloud Roadmap"](https://www.informationweek.com/cloud/nist-to-develop-cloud-roadmap/d/d-id/1093958?). *[InformationWeek](/source/InformationWeek)*. November 5, 2010. Computing initiative seeks to remove barriers to cloud adoption in security, interoperability, portability and reliability.

1. **[^](#cite_ref-19)** "What is it based on". *[Computerworld](/source/Computerworld)*. April 9, 1984. p. 13. Is it based on ... Reliability Portability. Compatibility

1. **[^](#cite_ref-20)** ["Programming 101: Tips to become a good programmer - Wisdom Geek"](https://wisdomgeek.com/programming/tips-become-good-programmer). *Wisdom Geek*. May 19, 2016. [Archived](https://web.archive.org/web/20160523063915/http://wisdomgeek.com/programming/tips-become-good-programmer) from the original on May 23, 2016. Retrieved May 23, 2016.

1. **[^](#cite_ref-21)** *Fundamentals of Software Architecture: An Engineering Approach*. O'Reilly Media. 2020. [ISBN](/source/ISBN_(identifier)) [978-1492043454](https://en.wikipedia.org/wiki/Special:BookSources/978-1492043454).

1. **[^](#cite_ref-22)** Elshoff, James L.; Marcotty, Michael (1982). ["Improving computer program readability to aid modification"](https://doi.org/10.1145%2F358589.358596). *Communications of the ACM*. **25** (8): 512–521. [doi](/source/Doi_(identifier)):[10.1145/358589.358596](https://doi.org/10.1145%2F358589.358596). [S2CID](/source/S2CID_(identifier)) [30026641](https://api.semanticscholar.org/CorpusID:30026641).

1. **[^](#cite_ref-23)** Multiple (wiki). ["Readability"](http://docforge.com/wiki/Readability). *Docforge*. [Archived](https://web.archive.org/web/20200429211203/http://www.docforge.com/wiki/Readability) from the original on April 29, 2020. Retrieved January 30, 2010.

1. **[^](#cite_ref-24)** Enticknap, Nicholas (September 11, 2007). ["SSL/Computer Weekly IT salary survey: finance boom drives IT job growth"](http://www.computerweekly.com/Articles/2007/09/11/226631/sslcomputer-weekly-it-salary-survey-finance-boom-drives-it-job.htm). [Archived](https://web.archive.org/web/20111026035734/http://www.computerweekly.com/Articles/2007/09/11/226631/SSLComputer-Weekly-IT-salary-survey-finance-boom-drives-IT-job.htm) from the original on October 26, 2011. Retrieved June 24, 2009.

1. **[^](#cite_ref-25)** Mitchell, Robert (May 21, 2012). ["The Cobol Brain Drain"](http://www.computerworld.com/article/2504568/data-center/the-cobol-brain-drain.html). Computer World. [Archived](https://web.archive.org/web/20190212185631/https://www.computerworld.com/article/2504568/data-center/the-cobol-brain-drain.html) from the original on February 12, 2019. Retrieved May 9, 2015.

1. **[^](#cite_ref-26)** ["Photograph courtesy Naval Surface Warfare Center, Dahlgren, Virginia, from National Geographic Sept. 1947"](https://www.nationalgeographic.org/thisday/sep9/worlds-first-computer-bug). July 15, 2020. [Archived](https://web.archive.org/web/20201113163443/https://www.nationalgeographic.org/thisday/sep9/worlds-first-computer-bug/) from the original on November 13, 2020. Retrieved November 10, 2020.

1. **[^](#cite_ref-27)** Stone, Dan N.; Jordan, Eleanor W.; Wright, M. Keith (1990). ["The impact of Pascal education on debugging skill"](https://scholars.uky.edu/en/publications/the-impact-of-pascal-education-on-debugging-skill/). *International Journal of Man-Machine Studies*. **33** (1): 81–95. [doi](/source/Doi_(identifier)):[10.1016/S0020-7373(05)80116-6](https://doi.org/10.1016%2FS0020-7373%2805%2980116-6).

1. **[^](#cite_ref-28)** ["Top Programming Languages 2024"](https://spectrum.ieee.org/top-programming-languages-2024). *IEEE Spectrum*. Retrieved January 20, 2025.

1. **[^](#cite_ref-29)** Halvorson, Michael J. (2020). *Code Nation: Personal Computing and the Learn to Program Movement in America*. New York, NY: ACM Books. pp. 3–6.

1. **[^](#cite_ref-30)** ["2024 State of Computer Science Education"](https://code.org/research). *Code.org*. Retrieved January 20, 2025.

1. **[^](#cite_ref-31)** *2014 Worldwide Software Developer and ICT-Skilled Worker Estimates*. Framingham, MA: International Data Corporation. 2014.

1. **[^](#cite_ref-32)** Ensmenger, Nathan (2010). *The Computer Boys Take Over: Computers, Programmers, and the Politics and Technical Expertise*. Cambridge, MA: The MIT Press.

1. **[^](#cite_ref-33)** Halvorson, Michael J. (2020). *Code Nation: Personal Computing and the Learn to Program Movement in America*. New York, NY: ACM Books. p. 80.

1. **[^](#cite_ref-34)** Perlis, Alan (1961). "The role of the digital computer in the university". *Computers and Automation 10, 4 and 4B*. pp. 10–15.

1. **[^](#cite_ref-35)** Halvorson, Michael J. (2020). *Code Nation: Personal Computing and the Learn to Program Movement in America*. New York, NY: ACM Books. p. 352.

1. **[^](#cite_ref-36)** Halvorson, Michael J. (2020). *Code Nation: Personal Computing and the Learn to Program Movement in America*. New York, NY: ACM Books. pp. 365–368.

1. **[^](#cite_ref-37)** Stemkoski, L., & Pascale, M. (2021). [*Developing Graphics Frameworks with Python and OpenGL. Taylor & Francis*](https://directory.doabooks.org/handle/20.500.12854/70094). Taylor & Francis. [ISBN](/source/ISBN_(identifier)) [978-0-367-72180-0](https://en.wikipedia.org/wiki/Special:BookSources/978-0-367-72180-0).{{[cite book](https://en.wikipedia.org/wiki/Template:Cite_book)}}: CS1 maint: multiple names: authors list ([link](https://en.wikipedia.org/wiki/Category:CS1_maint:_multiple_names:_authors_list))

1. **[^](#cite_ref-38)** Berssanette, J. H., & de Francisco, A. C. (August 2022). "Cognitive Load Theory in the Context of Teaching and Learning Computer Programming: A Systematic Literature Review". *IEEE Transactions on Education*. **65** (3): 440–449. [Bibcode](/source/Bibcode_(identifier)):[2022ITEdu..65..440B](https://ui.adsabs.harvard.edu/abs/2022ITEdu..65..440B). [doi](/source/Doi_(identifier)):[10.1109/TE.2021.3127215](https://doi.org/10.1109%2FTE.2021.3127215).{{[cite journal](https://en.wikipedia.org/wiki/Template:Cite_journal)}}: CS1 maint: multiple names: authors list ([link](https://en.wikipedia.org/wiki/Category:CS1_maint:_multiple_names:_authors_list))

1. **[^](#cite_ref-39)** Kinnett, Seth J.; Shinedling, Tatum; Sunset, Ben (July 1, 2025). ["Adventure RPG: A Text Adventure Game for an Introductory Java Programming Course"](https://research.ebsco.com/linkprocessor/plink?id=b4dad981-a76d-30ca-b003-cb67298436eb). *Journal of Information Systems Education*. **36** (3): 209–223. [doi](/source/Doi_(identifier)):[10.62273/ASHE6341](https://doi.org/10.62273%2FASHE6341).

1. **[^](#cite_ref-40)** Zaffalon, F.; Prisco, A.; De Souza, R.; Teixeira, D.; Paes, W.; Evald, P.; Tonin, N.; Devincenzi, S.; Botelho, S. (2022). [*A Recommender System of Computer Programming Exercises based on Student's Multiple Abilities and Skills Model*](https://doi.org/10.1109/FIE56618.2022.9962646). pp. 1–8. [doi](/source/Doi_(identifier)):[10.1109/FIE56618.2022.9962646](https://doi.org/10.1109%2FFIE56618.2022.9962646). [ISBN](/source/ISBN_(identifier)) [978-1-6654-6244-0](https://en.wikipedia.org/wiki/Special:BookSources/978-1-6654-6244-0).

1. **[^](#cite_ref-41)** Prat, Chantel S.; Madhyastha, Tara M.; Mottarella, Malayka J.; Kuo, Chu-Hsuan (March 2, 2020). ["Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages"](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7051953). *Scientific Reports*. **10** (1): 3817. [Bibcode](/source/Bibcode_(identifier)):[2020NatSR..10.3817P](https://ui.adsabs.harvard.edu/abs/2020NatSR..10.3817P). [doi](/source/Doi_(identifier)):[10.1038/s41598-020-60661-8](https://doi.org/10.1038%2Fs41598-020-60661-8). [ISSN](/source/ISSN_(identifier)) [2045-2322](https://search.worldcat.org/issn/2045-2322). [PMC](/source/PMC_(identifier)) [7051953](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7051953). [PMID](/source/PMID_(identifier)) [32123206](https://pubmed.ncbi.nlm.nih.gov/32123206).

1. **[^](#cite_ref-42)** ["To the brain, reading computer code is not the same as reading language"](https://news.mit.edu/2020/brain-reading-computer-code-1215). *MIT News | Massachusetts Institute of Technology*. December 15, 2020. Retrieved July 29, 2023.

### Sources

- Ceruzzi, Paul E. (1998). [*History of Computing*](https://archive.org/details/historyofmodernc00ceru). Cambridge, Massachusetts: MIT Press. [ISBN](/source/ISBN_(identifier)) [9780262032551](https://en.wikipedia.org/wiki/Special:BookSources/9780262032551) – via EBSCOhost.

- Evans, Claire L. (2018). [*Broad Band: The Untold Story of the Women Who Made the Internet*](https://books.google.com/books?id=C8ouDwAAQBAJ&q=9780735211759&pg=PP1). New York: Portfolio/Penguin. [ISBN](/source/ISBN_(identifier)) [9780735211759](https://en.wikipedia.org/wiki/Special:BookSources/9780735211759).

- Gürer, Denise (1995). ["Pioneering Women in Computer Science"](https://courses.cs.washington.edu/courses/csep590/06au/readings/p175-gurer.pdf) (PDF). *Communications of the ACM*. **38** (1): 45–54. [doi](/source/Doi_(identifier)):[10.1145/204865.204875](https://doi.org/10.1145%2F204865.204875). [S2CID](/source/S2CID_(identifier)) [6626310](https://api.semanticscholar.org/CorpusID:6626310). [Archived](https://ghostarchive.org/archive/20221009/https://courses.cs.washington.edu/courses/csep590/06au/readings/p175-gurer.pdf) (PDF) from the original on October 9, 2022.

- Smith, Erika E. (2013). ["Recognizing a Collective Inheritance through the History of Women in Computing"](https://doi.org/10.7771%2F1481-4374.1972). *CLCWeb: Comparative Literature and Culture*. **15** (1): 1–9. [doi](/source/Doi_(identifier)):[10.7771/1481-4374.1972](https://doi.org/10.7771%2F1481-4374.1972).

- Essinger, J., & EBSCO Publishing (Firm). (2014). *Ada's algorithm: How lord byron's daughter ada lovelace launched the digital age*. Melville House.

## Further reading

- A.K. Hartmann, *[Practical Guide to Computer Simulations](https://web.archive.org/web/20090211113048/http://worldscibooks.com/physics/6988.html)*, Singapore: [World Scientific](/source/World_Scientific) (2009)

- A. Hunt, D. Thomas, and W. Cunningham, *The Pragmatic Programmer. From Journeyman to Master*, Amsterdam: Addison-Wesley Longman (1999)

- Brian W. Kernighan, *The Practice of Programming*, Pearson (1999)

- [Weinberg, Gerald M.](/source/Gerald_Weinberg), *The Psychology of Computer Programming*, New York: Van Nostrand Reinhold (1971)

- [Edsger W. Dijkstra](/source/Edsger_W._Dijkstra), *A Discipline of Programming*, Prentice-Hall (1976)

- O.-J. Dahl, [E.W.Dijkstra](/source/Edsger_W._Dijkstra), C.A.R. Hoare, *Structured Programming*, Academic Press (1972)

- [David Gries](/source/David_Gries), *The Science of Programming*, Springer-Verlag (1981)

## External links

[Library resources](https://en.wikipedia.org/wiki/Wikipedia:The_Wikipedia_Library) about
 **Computer programming**

- [Online books](https://ftl.toolforge.org/cgi-bin/ftl?st=wp&su=Computer+programming&library=OLBP)

- [Resources in your library](https://ftl.toolforge.org/cgi-bin/ftl?st=wp&su=Computer+programming)

- [Resources in other libraries](https://ftl.toolforge.org/cgi-bin/ftl?st=wp&su=Computer+programming&library=0CHOOSE0)

Wikibooks has a book on the topic of: ***[Computer Programming](https://en.wikibooks.org/wiki/Computer_Programming)***

Wikibooks has a book on the topic of: ***[Windows Programming](https://en.wikibooks.org/wiki/Windows_Programming)***

Wikiversity has learning resources about ***[Computer Programming](https://en.wikiversity.org/wiki/Computer_Programming)***

- Media related to [Computer programming](https://commons.wikimedia.org/wiki/Category:Computer_programming) at Wikimedia Commons

- Quotations related to [Programming](https://en.wikiquote.org/wiki/Programming) at Wikiquote

v t e Computer science This template follows roughly the 2012 ACM Computing Classification System Hardware Printed circuit board Peripheral Integrated circuit Very-large-scale integration System on a chip (SoC) Energy consumption (green computing) Electronic design automation Hardware acceleration Processor Size – Form Systems organization Computer architecture Computational complexity Dependability Embedded system Real-time computing Cyber-physical system Fault tolerance Wireless sensor network Networks Network architecture Network protocol Network components Network scheduler Network performance evaluation Network service Software organization Interpreter Middleware Virtual machine Operating system Software quality Software notations, tools Programming paradigm Programming language Compiler Domain-specific language Modeling language Software framework Integrated development environment Software configuration management Software library Software repository Software development Control flow Software development process Requirements analysis Software design Software construction Software deployment Software engineering Software maintenance Programming team Open source model Theory of computing Model of computation Stochastic Formal language Automata theory Computability theory Computational complexity theory Logic Semantics Algorithms Algorithm design Analysis of algorithms Algorithmic efficiency Randomized algorithm Computational geometry Mathematics of computing Discrete mathematics Probability Statistics Mathematical software Information theory Mathematical analysis Numerical analysis Theoretical computer science Computational problem Information systems Database management Information storage Enterprise information Social information Geographic information Decision support Process control Multimedia information Data mining Digital library Computing platform Digital marketing World Wide Web Information retrieval Security Cryptography Formal methods Security hacker Security services Intrusion detection system Hardware security Network security Information security Application security Human- centered computing Accessibility Extended reality augmented virtual Human–computer interaction Interaction design Mobile computing Social computing Ubiquitous computing Visualization Concurrency Concurrent computing Parallel computing Distributed computing Multithreading Multiprocessing Artificial intelligence Computational intelligence Natural language processing Knowledge representation and reasoning Computer vision Automated planning and scheduling Search methodology Control method Philosophy of Distributed Machine learning Supervised Unsupervised Reinforcement Multi-task Cross-validation Graphics Animation Rendering Photograph manipulation Graphics processing unit Image compression Solid modeling Applied computing Quantum computing E-commerce Enterprise software Computational mathematics Computational physics Computational chemistry Computational biology Computational social science Computational engineering Differentiable computing Computational healthcare Digital art Electronic publishing Cyberwarfare Electronic voting Video games Word processing Operations research Educational technology Document management Outline Glossaries Category

v t e Software engineering Fields Computer programming DevOps Empirical software engineering Experimental software engineering Formal methods Requirements engineering Search-based software engineering Site reliability engineering Social software engineering Software deployment Software design Software maintenance Software testing Systems analysis Concepts Abstraction CI/CD Compatibility Backward compatibility Compatibility layer Compatibility mode Forward compatibility Software incompatibility Component-based software engineering Data modeling Enterprise architecture Functional specification Modeling language Programming paradigm Software Software archaeology Software architecture Software configuration management Software development process/methodology Software quality Software quality assurance Software system Software verification and validation Structured analysis Essential analysis Orientations Agile Aspect-oriented Object orientation Ontology SDLC Service orientation Models Developmental Agile EUP Executable UML Incremental model Iterative model Prototype model RAD Scrum Spiral model UP V-model Waterfall model XP Model-driven engineering Round-trip engineering Other CMMI Data model ER model Function model Information model Metamodeling Object model SPICE Systems model View model Languages IDEF SysML UML USL Related fields Computer engineering Computer science Information science Project management Risk management Systems engineering Category Commons

v t e Software quality Qualities Internal Size Maintainability Flexibility Portability Reusability Readability Scalability Testability Understandability Loose coupling Orthogonality External Usability Reliability Adaptability Correctness Accuracy Efficiency Robustness Security Safety Standards, lists ISO/IEC 9126 Non-functional requirements List of system quality attributes Processes Software quality management Software quality control Software quality assurance Categories: Commons • Software quality • Software testing

Authority control databases International GND FAST National United States France BnF data Japan Czech Republic Spain Latvia Israel Other Yale LUX

---
Adapted from the Wikipedia article [Computer programming](https://en.wikipedia.org/wiki/Computer_programming) by Wikipedia contributors ([contributor history](https://en.wikipedia.org/wiki/Computer_programming?action=history)). Available under [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/). Changes may have been made.