Computer programming

Software development
Core activities
Paradigms and models
Methodologies and frameworks
Supporting disciplines
Practices
Tools
Standards and Bodies of Knowledge
Glossaries
Outlines

Computer programming is the process of designing and building an executable computer program to accomplish a specific computing result or to perform a specific task. Programming involves tasks such as: analysis, generating algorithms, profiling algorithms' accuracy and resource consumption, and the implementation of algorithms in a chosen programming language (commonly referred to as coding).[1][2] The source code of a program is written in one or more languages that are intelligible to programmers, rather than machine code, which is directly executed by the central processing unit. The purpose of programming is to find a sequence of instructions that will automate the performance of a task (which can be as complex as an operating system) on a computer, often for solving a given problem. Proficient programming thus often requires expertise in several different subjects, including knowledge of the application domain, specialized algorithms, and formal logic.

Tasks accompanying and related to programming include: testing, debugging, source code maintenance, implementation of build systems, and management of derived artifacts, such as the machine code of computer programs. These might be considered part of the programming process, but often the term software development is used for this larger process with the term programming, implementation, or coding reserved for the actual writing of code. Software engineering combines engineering techniques with software development practices. Reverse engineering is a related process used by designers, analysts and programmers to understand and re-create/re-implement.[3]:3

History[]

Ada Lovelace, whose notes added to the end of Luigi Menabrea's paper included the first algorithm designed for processing by an Analytical Engine. She is often recognized as history's first computer programmer.

Programmable devices have existed for centuries. As early as the 9th century, a programmable music sequencer was invented by the Persian Banu Musa brothers, who described an automated mechanical flute player in the Book of Ingenious Devices.[4][5] In 1206, the Arab engineer Al-Jazari invented a programmable drum machine where musical mechanical automaton could be made to play different rhythms and drum patterns, via pegs and cams.[6][7] In 1801, the Jacquard loom could produce entirely different weaves by changing the "program" – a series of pasteboard cards with holes punched in them.

Code-breaking algorithms have also existed for centuries. In the 9th century, the Arab mathematician Al-Kindi described a cryptographic algorithm for deciphering encrypted code, in A Manuscript On Deciphering Cryptographic Messages. He gave the first description of cryptanalysis by frequency analysis, the earliest code-breaking algorithm.[8]

The first computer program is generally dated to 1843, when mathematician Ada Lovelace published an algorithm to calculate a sequence of Bernoulli numbers, intended to be carried out by Charles Babbage's Analytical Engine.[9]

Data and instructions were once stored on external punched cards, which were kept in order and arranged in program decks.

In the 1880s Herman Hollerith invented the concept of storing data in machine-readable form.[10] Later a control panel (plugboard) added to his 1906 Type I Tabulator allowed it to be programmed for different jobs, and by the late 1940s, unit record equipment such as the IBM 602 and IBM 604, were programmed by control panels in a similar way; as were the first electronic computers. However, with the concept of the stored-program computers introduced in 1949, both programs and data were stored and manipulated in the same way in computer memory.[citation needed]

Machine language[]

Machine code was the language of early programs, written in the instruction set of the particular machine, often in binary notation. Assembly languages were soon developed that let the programmer specify instruction in a text format, (e.g., ADD X, TOTAL), with abbreviations for each operation code and meaningful names for specifying addresses. However, because an assembly language is little more than a different notation for a machine language, any two machines with different instruction sets also have different assembly languages.

Wired control panel for an IBM 402 Accounting Machine.

Compiler languages[]

High-level languages made the process of developing a program simpler and more understandable, and less bound to the underlying hardware. FORTRAN, the first widely used high-level language to have a functional implementation, came out in 1957[11] and many other languages were soon developed – in particular, COBOL aimed at commercial data processing, and Lisp for computer research.

These compiled languages allow the programmer to write programs in terms that are syntactically richer, and more capable of abstracting the code, making it targetable to varying machine instruction sets via compilation declarations and heuristics. The first compiler for a programming language was developed by Grace Hopper.[12] When Hopper went to work on UNIVAC in 1949, she brought the idea of using compilers with her.[13][14] Compilers harness the power of computers to make programming easier[15] by allowing programmers to specify calculations by entering a formula using infix notation (e.g., Y = X*2 + 5*X + 9) for example. FORTRAN, the first widely used high-level language to have a functional implementation which permitted the abstraction of reusable blocks of code, came out in 1957[16] and many other languages were soon developed - in particular, COBOL aimed at commercial data processing, and Lisp for computer research. In 1951 Frances E. Holberton developed the first sort-merge generator which ran on the UNIVAC I.[17] Another woman working at UNIVAC, Adele Mildred Koss, developed a program that was a precursor to report generators.[17] The idea for the creation of COBOL started in 1959 when Mary K. Hawes, who worked for Burroghs Corporation, set up a meeting to discuss creating a common business language.[18] She invited six people, including Grace Hopper.[18] Hopper was involved in developing COBOL as a business language and creating "self-documenting" programming.[19][20] Hopper's contribution to COBOL was based on her programming language, called FLOW-MATIC.[14] In 1961, Jean E. Sammet developed FORMAC and also published Programming Languages: History and Fundamentals which went on to be a standard work on programming languages.[18][21]

Source code entry[]

Programs were mostly still entered using punched cards or paper tape. See computer programming in the punch card era. By the late 1960s, data storage devices and computer terminals became inexpensive enough that programs could be created by typing directly into the computers. Frances Holberton created a code to allow keyboard inputs while she worked at UNIVAC.[22]

Text ors were developed that allowed changes and corrections to be made much more easily than with punched cards. Sister Mary Kenneth Keller worked on developing the programming language, BASIC which she was a graduate student at Dartmouth in the 1960s.[23] One of the first object-oriented programming languages, Smalltalk, was developed by seven programmers, including Adele Goldberg, in the 1970s.[24] In 1985, Radia Perlman developed the Spinning Tree Protocol in order to route packets of network information efficiently.[25][26]

Modern programming[]

Quality requirements[]

Whatever the approach to development may be, the final program must satisfy some fundamental properties. The following properties are among the most important:[27] [28]

Readability of source code[]

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

Readability is important because programmers spend the majority of their time reading, trying to understand and modifying existing source code, rather than writing new source code. Unreadable code often leads to bugs, inefficiencies, and duplicated code. A study[30] found that a few simple readability transformations made code shorter and drastically reduced the time to understand it.

Following a consistent 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.[31] Some of these factors include:

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

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

Algorithmic complexity[]

The academic field and the engineering practice of computer programming are both largely concerned with discovering and implementing the most efficient algorithms for a given class of problem. For this purpose, algorithms are classified into orders using so-called 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.

Chess algorithms as an example[]

"Programming a Computer for Playing Chess" was a 1950 paper that evaluated a "minimax" algorithm that is part of the history of algorithmic complexity; a course on IBM's Deep Blue (chess computer) is part of the computer science curriculum at Stanford University.[32]

Methodologies[]

The first step in most formal software development processes is requirements analysis, followed by testing to determine value modeling, implementation, and failure elimination (debugging). There exist a lot of differing approaches for each of those tasks. One approach popular for requirements analysis is Use Case analysis. Many programmers use forms of 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) and Model-Driven Architecture (MDA). The Unified Modeling Language (UML) is a notation used for both the OOAD and MDA.

A similar technique used for database design is Entity-Relationship Modeling (ER Modeling).

Implementation techniques include imperative languages (object-oriented or procedural), functional languages, and logic 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,[33] 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 very popular for particular kinds of applications, while some languages are regularly used to write many different kinds of applications. For example, COBOL is still strong in corporate data centers[34] often on large mainframe computers, Fortran in engineering applications, scripting languages in Web development, and C in 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++ adds object-orientation to C, and Java adds memory management and bytecode to C++, but as a result, loses efficiency and the ability for low-level manipulation).

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.[35] "Bug" was already a common term for a software defect when this bug 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 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 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 remaining actions are sufficient for bugs to appear. Scripting and breakpointing is also part of this process.

Debugging is often done with IDEs like Eclipse, Visual Studio, Xcode, Kdevelop, NetBeans and Code::Blocks. Standalone debuggers like GDB are also used, and these often provide less of a visual environment, usually using a command line. Some text ors such as Emacs allow GDB to be invoked through them, to provide a visual environment.

Programming languages[]

Different programming languages support different styles of programming (called programming paradigms). 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.

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. Provided the functions in a library follow the appropriate run-time conventions (e.g., method of passing arguments), then these functions may be written in any other language.

Programmers[]

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

See also[]

References[]

  1. ^ Bebbington, Shaun (2014). "What is coding". Tumblr. Archived from the original on April 29, 2020. Retrieved March 3, 2014.CS1 maint: date and year (link)
  2. ^ Bebbington, Shaun (2014). "What is programming". Tumblr. Archived from the original on April 29, 2020. Retrieved March 3, 2014.
  3. ^ Eilam, Eldad (2005). Reversing: secrets of reverseengineering. John Wiley & Sons. ISBN 978-0-7645-7481-8.CS1 maint: uses authors parameter (link)
  4. ^ Koetsier, Teun (2001), "On the prehistory of programmable machines: musical automata, looms, calculators", Mechanism and Machine Theory, Elsevier, 36 (5): 589–603, doi:10.1016/S0094-114X(01)00005-2.
  5. ^ Kapur, Ajay; Carnegie, Dale; Murphy, Jim; Long, Jason (2017). "Loudspeakers Optional: A history of non-loudspeaker-based electroacoustic music". Organised Sound. Cambridge University Press. 22 (2): 195–205. doi:10.1017/S1355771817000103. ISSN 1355-7718.
  6. ^ Fowler, Charles B. (October 1967). "The Museum of Music: A History of Mechanical Instruments". Music Educators Journal. 54 (2): 45–49. doi:10.2307/3391092. JSTOR 3391092. S2CID 190524140.
  7. ^ Noel Sharkey (2007), A 13th Century Programmable Robot, University of Sheffield
  8. ^ Dooley, John F. (2013). A Brief History of Cryptology and Cryptographic Algorithms. Springer Science & Business Media. pp. 12–3. ISBN 9783319016283.
  9. ^ Fuegi, J.; Francis, J. (2003). "Lovelace & Babbage and the Creation of the 1843 'notes'". IEEE Annals of the History of Computing. 25 (4): 16. doi:10.1109/MAHC.2003.1253887.
  10. ^ da Cruz, Frank (March 10, 2020). "Columbia University Computing History – Herman Hollerith". Columbia University. Columbia.edu. Archived from the original on April 29, 2020. Retrieved April 25, 2010.
  11. ^ Bergstein, Brian (March 20, 2007). "Fortran creator John Backus dies - Tech and gadgets- NBC News". NBC News. NBC News. Archived from the original on April 29, 2020. Retrieved April 25, 2010.
  12. ^ Smith 2013, p. 6.
  13. ^ Ceruzzi 1998, p. 84-85.
  14. ^ a b Gürer 1995, p. 176.
  15. ^ "Fortran creator John Backus dies". msnbc.com. Retrieved November 19, 2014.
  16. ^ "Fortran creator John Backus dies - Tech and gadgets- msnbc.com". MSNBC. March 20, 2007. Retrieved April 25, 2010.
  17. ^ a b Gürer 1995, p. 177.
  18. ^ a b c Gürer 1995, p. 179.
  19. ^ Smith 2013, p. 7.
  20. ^ Ceruzzi 1998, p. 92.
  21. ^ "Computer Authority to Speak Here". The Times. April 9, 1972. Retrieved October 13, 2018 – via Newspapers.com.
  22. ^ "Frances Holberton, Pioneer in Computer Languages, Dies". The Courier-Journal. December 12, 2001. Retrieved October 13, 2018 – via Newspapers.com.
  23. ^ Gürer 1995, p. 180-181.
  24. ^ "Adele Goldberg". University of Maryland, College Park. Retrieved October 14, 2018.
  25. ^ Evans 2018, p. 126.
  26. ^ Rosen, Rebecca J. (March 3, 2014). "Radia Perlman: Don't Call Me the Mother of the Internet". The Atlantic. Retrieved October 15, 2018.
  27. ^ "NIST To Develop Cloud Roadmap". InformationWeek. November 5, 2010. Computing initiative seeks to remove barriers to cloud adoption in security, interoperability, portability and reliability.
  28. ^ "What is it based on". ComputerWorld. April 9, 1984. p. 13. Is it based on ... Reliability Portability. Compatibility
  29. ^ "Programming 101: Tips to become a good programmer - Wisdom Geek". Wisdom Geek. May 19, 2016. Retrieved May 23, 2016.
  30. ^ Elshoff, James L.; Marcotty, Michael (1982). "Improving computer program readability to aid modification". Communications of the ACM. 25 (8): 512–521. doi:10.1145/358589.358596. S2CID 30026641.
  31. ^ Multiple (wiki). "Readability". Docforge. Archived from the original on April 29, 2020. Retrieved January 30, 2010.
  32. ^ Piech, Chris. "Deep Blue". In 1950, Claude Shannon published ... "Programming a Computer for Playing Chess", ... "minimax" algorithm
  33. ^ Survey of Job advertisements mentioning a given language
  34. ^ Mitchell, Robert (May 21, 2012). "The Cobol Brain Drain". Computer World. Retrieved May 9, 2015.
  35. ^ Photograph courtesy Naval Surface Warfare Center, Dahlgren, Virginia, from National Geographic Sept. 1947

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