programming

1. The designing, scheduling, or planning of a program, as in broadcasting.
2. The writing of a computer program.

Creating a computer program. The steps are:

1. Developing the program logic to solve the

particular problem.

2. Writing the program logic in a specific

programming language (coding the program).

3. Assembling or compiling the program to turn

it into machine language.

4. Testing and debugging the program.

5. Preparing the necessary documentation.

The logic is generally the most difficult part of programming. However, depending on the programming language, writing the statements may also be laborious. One thing is certain. Documenting the program is considered the most annoying activity by most programmers. See estimating a programming job and peer review.

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Process of writing instructions for a computer. The program has to be turned into machine-readable form and put into the computer. The program must be tested to assure accuracy, and supporting documentation prepared.

Within the context of information systems, the term programming is understood to mean computer programming, which is the process of writing computer programs. A computer program is a detailed, step-by-step set of instructions that is executed by a computer in order to perform a specific task or solve a specific problem. A computer can perform a wide variety of tasks, including arithmetic calculations, text formatting, and submission of documents to the printer to be printed. However, the computer hardware does not perform these tasks by itself. It needs specific instructions on how to go about performing each specific task. It is these task-specific sets of instructions that are referred to as programs.

Programming Languages

Computer programs are written in a variety of programming languages. These languages fall into two broad categories: low-level programming languages and high-level programming languages. Low-level programming languages are so named because they are closer to machine language than to human language; that is, it is easier for the machine (computer) to understand them than it is for humans. Machine language is made up of a series of 0's and 1's. Each 0 or 1 is known as a bit (short for binary digit). A group of eight bits, known as a byte, represents one character(i.e., a number or a letter). For example, the number 2 is represented as 00000010 and the letter B as 01000010 in the American National Standards Institute (ANSI) code for character representation inside a computer. There are other coding schemes besides the ANSI standard, such as the American Standard Code for Information Interchange (ASCII) and IBM's Extended Binary Coded Decimal Interchange Code (EBCDIC). Each of these standards represents characters in a slightly different way. Such binary representation of characters is the only thing that the computer can directly "understand" and execute.

In the early days of computer programming, programmers wrote their programs directly in machine language. The time-consuming and painstaking nature of this process led to the development of assembly language, which uses alphabetic mnemonics (rather than binary digits) to write programs. For example, an assembly-language instruction to load the number 5 into a computer's accumulator is: LDA 5. This is more readable than a string of 0's and 1's. A special program called an assembler translates assembly-language instructions into machine-language instructions. Assembly language is machine-specific and is used to directly manipulate activity at the hardware level. Therefore, it is still considered low-level.

Further technological advances led to the development of high-level programming languages such as COBOL (COmmon Business Oriented Language), FORTRAN (FORmula TRANslator). BASIC (Beginners' All-purpose Symbolic Instruction Code), PASCAL, PL/1, and C. These languages are described high-level because they are closer to human language than to machine language. In these languages, the number 2 and the letter B are coded in the program exactly as they are written. Similarly, the following is a valid line of program code in some high-level languages: SUM NUM1 NUM2. A special program, known as a compiler or an interpreter (depending on the programming language) translates the high-level program code into machine language before it is executed.

Categories of Programming

There are two main categories of programming, systems programming and applications programming. Systems programs are more likely to be written in low-level programming languages, while applications programs are written almost exclusively in high-level languages.

Systems Programming Systems programming involves writing programs that enable a computer to carry out its basic internal functions as well as some other specialized functions. Examples of systems programs include operating systems, device drivers, and utility programs.

An operating system, which comes as an essential and necessary component of any computer system, is a complex set of programs that coordinates activities inside a computer and ensures the proper and efficient use of all the computer's resources. Among its basic functions are scheduling and running multiple jobs inside the computer, managing storage space, enforcing security (e.g., through password verification), and detecting equipment failure. Through its actions, the operating system enables a user to access the computer's hardware and software components. Examples of operating systems include DOS, Windows 95, Windows 98, Windows NT, Macintosh System 8, UNIX, OS/2, and VAX VMS.

Device drivers are those programs that identify particular devices to a computer and enable the computer to correctly use those devices. For example, a mouse driver program helps a computer identify the mouse attached to it.

Utility programs (or utilities) are programs that perform such specialized tasks as reorganizing data on disks, recovering lost data, recovering from system crashes, and detecting and removing computer viruses.

Applications Programming Applications programming refers to the process of developing programs to be used for specific applications, such as a business application (e.g., computing benefits to be paid to different employee classifications) or an academic application (e.g., determining who qualifies for which scholarship, based on specified eligibility criteria). Programming such applications usually requires the programmer to specify the precise logic that would be required to solve the given problem. There are a number of stages in the applications programming process, including problem statement, algorithm development, program coding, program testing, and program documentation.

Problem statement: The programming process begins with a clear, written statement of the problem to be solved by the computer. The importance of this step cannot be overemphasized. A poorly articulated or poorly understood problem statement will result in the wrong solution being developed for the problem at hand. There should also be a statement of the conditions that would determine when the problem has been solved. All known and relevant facts should also be stated at this stage, as well as any necessary assumptions to be made in the program.

Algorithm development: Once the problem has been clearly stated and all the requirements have been understood, the next step is to develop the program logic necessary for accomplishing the task. An algorithm is defined as a logical sequence of steps that must be performed in order to accomplish a given task. There are some tools available to help the programmer develop the algorithm for a given problem. The two best-known and most widely used ones are the flowchart and pseudocode. Both of these are language-independent, focusing primarily on logic flow rather than the syntax of any particular language. A flowchart uses standard flowcharting symbols to visually represent the flow of program logic. Pseudocode, on the other hand, often looks like actual program code, but it is not, since it does not follow any particular language's syntax. The term pseudocode means "false code." Unlike flowcharting, in which standard, universally accepted symbols are used, there are no set standards for writing pseudocode. Figures 1 and 2 illustrate the use of a flowchart and pseudocode, respectively, to depict the logic needed to add up all the even numbers between 2 and 100, inclusive, and print the resulting total.

Program coding: When the programmer is satisfied with the efficacy of the logic developed in the preceding step, it is time to convert that logic (in either flowchart or pseudocode form) to the specific syntax of the programming language that will be used. At this stage, the programmer adheres strictly to all of the syntax requirements for coding the logic as well as other aspects of the program.

Program testing: The coded program is next checked for errors. At least two types of programming errors must be checked for, namely, syntax errors and logic errors. The presence of syntax errors indicates that some syntactic rule(s) of the programming language has (have) been violated. Syntax errors are detected when the program is compiled (the compiler identifies all such errors within the program). They must be corrected before the program can be successfully executed. Even when all the syntax errors have been corrected, there is the possibility of logic errors. Logic errors arise when the desired logic is incorrectly specified in the program, thereby resulting in an erroneous output. An example is a program that makes students with failing grades eligible for academic scholarships when, in fact, they should not be. In computer terminology, any error in a program—syntax or logic—is known as a bug. The process of correcting these errors is known as debugging.

Program documentation: The programming process is complete when the program has been fully documented. The documentation can be either incorporated into the body of the program itself (in-line documentation) or it can be a completely separate document (external documentation). Frequently, it is both. Good documentation typically includes the following: a statement of the program's objective(s); descriptions of any input or output records or files needed to run the program; a complete definition of all data names used; and an explanation of the underlying logic, preferably with an accompanying flowchart. Pro gram documentation greatly facilitates program maintenance, which is the periodic modification to, or update of, the program in order to keep it current. This is especially important if the person maintaining the program is not the same one who wrote it.

Applications Programs on the Market

There is a wide array of programs and compilers on the market today, in the form of various software packages. Compilers for all the major programming languages mentioned above are available on virtually all computing platforms. Most of these commercial packages, such as Visual Basic, Visual C, and Micro focus COBOL, have "visual" front-ends to their programming environments, which makes it easy for programmers to design user-friendly programs for their clients.

Bibliography

Berlioux, Pierre, and Bizard, Philippe. (1986). Algorithms: The Construction. Proof, and Analysis of Programs, trans. Annwyl Williams. New York: Wiley.

Dodd, Kenneth N. (1969). Computer Programming and Languages. New York: Plenum.

Flores, Ivan. (1971). Assemblers and BAL. Englewood Cliffs, NJ: Prentice-Hall.

Iliffe, J.K. (1972). Basic Machine Principles, 2d ed. New York: American Elsevier.

Knuth, Donald E. (1997). The Art of Computer Programming, 3d ed. Reading, MA: Addison-Wesley.

McCracken, Daniel, and Golden, Donald. (1990). Simplified Structured COBOL with Microsoft/Microfocus COBOL. New York: Wiley.

Parsons, June J., and Oja, Dan. (1998). Computer Concepts—Comprehensive, 3d ed. Cambridge, MA: Course Technology.

Washburn, Dale W. (1970). Computer Programming: A Total Language Approach. New York: Holt, Reinhart & Winston.

[Article by: THEOPHILUS B. A. ADDO]

1. The art of debugging a blank sheet of paper (or, in these days of on-line editing, the art of debugging an empty file). “Bloody instructions which, being taught, return to plague their inventor” (Macbeth, Act 1, Scene 7)

2. A pastime similar to banging one's head against a wall, but with fewer opportunities for reward.

3. The most fun you can have with your clothes on.

4. The least fun you can have with your clothes off.

The process of describing in a computer language a problem or its method of solution. Programming includes planning, designing, writing, and debugging of programs.

Computer programming has evolved from the development of programs that run on big mainframe computers to ones that run on desktop personal computers (PCs) and small local area networks. Individuals working in public health, therefore, have had to become versed in a variety of different PC applications, such as Access and SPSS. They are charged with the responsibility of determining which programs available on the open market are the best suited to the individual needs of a specific health agency. Decisions are based on the information required to be stored and accessed and the skill level of the staff that will utilize the programs. These individuals are then charged with updating and maintaining these systems for optimum performance.

(SEE ALSO: Biostatistics; Information Systems; Information Technology; Statistics for Public Health)

— NEIL CASEY

"Programming" redirects here. For other uses, see Programming (disambiguation).

Software development process
Activities and steps
Requirements · Specification Architecture · Design Implementation · Testing Deployment · Maintenance
Models
Agile · Cleanroom · DSDM Iterative · RAD  · RUP  · Spiral Waterfall · XP · Scrum  · Lean V-Model  · FDD  · TDD
Supporting disciplines
Configuration management Documentation Quality assurance (SQA) Project management User experience design
Tools
Compiler  · Debugger  · Profiler GUI designer Integrated development environment
This box: view • talk

Computer programming (often shortened to programming or coding) is the process of writing, testing, debugging/troubleshooting, and maintaining the source code of computer programs. This source code is written in a programming language. The code may be a modification of an existing source or something completely new. The purpose of programming is to create a program that exhibits a certain desired behaviour (customization). The process of writing source code often requires expertise in many different subjects, including knowledge of the application domain, specialized algorithms and formal logic.

Contents 1 Overview 2 History of programming 3 Modern programming 3.1 Quality requirements 3.2 Algorithmic complexity 3.3 Methodologies 3.4 Measuring language usage 3.5 Debugging 4 Programming languages 5 Programmers 6 See also 7 References 8 Further reading 9 External links

Overview

Wikiversity has learning materials about programming

Within software engineering, programming (the implementation) is regarded as one phase in a software development process.

There is an ongoing debate on the extent to which the writing of programs is an art, a craft or an engineering discipline.^[1] In general, good programming is considered to be the measured application of all three, with the goal of producing an efficient and evolvable software solution (the criteria for "efficient" and "evolvable" vary considerably). The discipline differs from many other technical professions in that programmers, in general, do not need to be licensed or pass any standardized (or governmentally regulated) certification tests in order to call themselves "programmers" or even "software engineers." However, representing oneself as a "Professional Software Engineer" without a license from an accredited institution is illegal in many parts of the world.^{[citation needed]}

Another ongoing debate is the extent to which the programming language used in writing computer programs affects the form that the final program takes. This debate is analogous to that surrounding the Sapir-Whorf hypothesis ^[2] in linguistics, that postulates that a particular language's nature influences the habitual thought of its speakers. Different language patterns yield different patterns of thought. This idea challenges the possibility of representing the world perfectly with language, because it acknowledges that the mechanisms of any language condition the thoughts of its speaker community.

Said another way, programming is the craft of transforming requirements into something that a computer can execute.

History of programming

See also: History of programming languages

Wired plug board for an IBM 402 Accounting Machine.

The concept of devices that operate following a pre-defined set of instructions traces back to Greek Mythology, notably Hephaestus and his mechanical servants^[3]. The Antikythera mechanism was a calculator utilizing gears of various sizes and configuration to determine its operation. The earliest known programmable machines (machines whose behavior can be controlled and predicted with a set of instructions) were Al-Jazari's programmable Automata in 1206.^[4] One of Al-Jazari's robots was originally a boat with four automatic musicians that floated on a lake to entertain guests at royal drinking parties. Programming this mechanism's behavior meant placing pegs and cams into a wooden drum at specific locations. These would then bump into little levers that operate a percussion instrument. The output of this device was a small drummer playing various rhythms and drum patterns.^[5][6] Another sophisticated programmable machine by Al-Jazari was the castle clock, notable for its concept of variables, which the operator could manipulate as necessary (i.e., the length of day and night). The Jacquard Loom, which Joseph Marie Jacquard developed in 1801, uses a series of pasteboard cards with holes punched in them. The hole pattern represented the pattern that the loom had to follow in weaving cloth. The loom could produce entirely different weaves using different sets of cards. Charles Babbage adopted the use of punched cards around 1830 to control his Analytical Engine. The synthesis of numerical calculation, predetermined operation and output, along with a way to organize and input instructions in a manner relatively easy for humans to conceive and produce, led to the modern development of computer programming. Development of computer programming accelerated through the Industrial Revolution.

In the late 1880s, Herman Hollerith invented the recording of data on a medium that could then be read by a machine. Prior uses of machine readable media, above, had been for control, not data. "After some initial trials with paper tape, he settled on punched cards..."^[7] To process these punched cards, first known as "Hollerith cards" he invented the tabulator, and the key punch machines. These three inventions were the foundation of the modern information processing industry. In 1896 he founded the Tabulating Machine Company (which later became the core of IBM). The addition of a control panel to his 1906 Type I Tabulator allowed it to do different jobs without having to be physically rebuilt. By the late 1940s, there were a variety of plug-board programmable machines, called unit record equipment, to perform data-processing tasks (card reading). Early computer programmers used plug-boards for the variety of complex calculations requested of the newly invented machines.

Data and instructions could be stored on external punch cards, which were kept in order and arranged in program decks.

The invention of the Von Neumann architecture allowed computer programs to be stored in computer memory. Early programs had to be painstakingly crafted using the instructions of the particular machine, often in binary notation. Every model of computer would be likely to need different instructions to do the same task. Later assembly languages were developed that let the programmer specify each instruction in a text format, entering abbreviations for each operation code instead of a number and specifying addresses in symbolic form (e.g., ADD X, TOTAL). In 1954 Fortran was invented, being the first high level programming language to have a functional implementation.^[8][9] It allowed programmers to specify calculations by entering a formula directly (e.g. Y = X*2 + 5*X + 9). The program text, or source, is converted into machine instructions using a special program called a compiler. Many other languages were developed, including some for commercial programming, such as COBOL. Programs were mostly still entered using punch 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 so programs could be created by typing directly into the computers. Text editors were developed that allowed changes and corrections to be made much more easily than with punch cards.

As time has progressed, computers have made giant leaps in the area of processing power. This has brought about newer programming languages that are more abstracted from the underlying hardware. Although these high-level languages usually incur greater overhead, the increase in speed of modern computers has made the use of these languages much more practical than in the past. These increasingly abstracted languages typically are easier to learn and allow the programmer to develop applications much more efficiently and with less code. However, high-level languages are still impractical for a few programs, such as those where low-level hardware control is necessary or where processing speed is at a premium.

Throughout the second half of the twentieth century, programming was an attractive career in most developed countries. Some forms of programming have been increasingly subject to offshore outsourcing (importing software and services from other countries, usually at a lower wage), making programming career decisions in developed countries more complicated, while increasing economic opportunities in less developed areas. It is unclear how far this trend will continue and how deeply it will impact programmer wages and opportunities.

Modern programming

Quality requirements

Whatever the approach to software development may be, the final program must satisfy some fundamental properties. The following properties are among the most relevant:

• Efficiency/performance: the amount 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 correct disposal of some resources, such as cleaning up temporary files and lack of memory leaks.
• 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 and race conditions) and logic errors (such as division by zero).
• Robustness: how well a program anticipates problems not due to programmer error. This includes situations such as incorrect, inappropriate or corrupt data, unavailability of needed resources such as memory, operating system services and network connections, and user error.
• Usability: the 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: the range of computer hardware and operating system platforms on which the source code of a program can be compiled/interpreted and run. This depends on differences in the programming facilities provided by the different platforms, including hardware and operating system resources, expected behaviour of the hardware and operating system, and availability of platform specific compilers (and sometimes libraries) for the language of the source code.
• Maintainability: the ease with which a program can be modified by its present or future developers in order to make improvements or customizations, fix bugs and security holes, or adapt it to new environments. Good practices 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.

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, O(n), 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 projects 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.

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 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 of modern programming languages. Some languages are very popular for particular kinds of applications (e.g., COBOL is still strong in the corporate data center, often on large mainframes, FORTRAN in engineering applications, scripting languages in web development, and C in embedded applications), while some languages are regularly used to write many different kinds of applications.

Methods of measuring programming language popularity include: counting the number of job advertisements that mention the language^[10], the number of books teaching the language that are sold (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).

Debugging

A bug, which was debugged in 1947.

Debugging is a very important task in the software development process, because an incorrect 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 analysis tool can help detect some possible problems.

Debugging is often done with IDEs like Visual Studio, NetBeans, and Eclipse. Standalone debuggers like gdb are also used, and these often provide less of a visual environment, usually using a command line.

Programming languages

Main articles: Programming language and List of 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.

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: Get 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 libraries. Provided the functions in a library follow the appropriate runtime conventions (eg, method of passing arguments), then these functions may be written in any other language.

Programmers

Main article: Programmer

See also: Software developer and Software engineer

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

• Coding
• Compilation
• Documentation
• Integration
• Maintenance
• Requirements analysis
• Software architecture
• Software testing
• Specification
• Debugging

See also

Wikipedia:Books has a book on: Programming

Wikiquote has a collection of quotations related to: Programming

Main article: Outline of computer programming

• ACCU (organisation)
• Association for Computing Machinery
• Computer programming in the punch card era
• Hello world program
• List of basic computer programming topics
• List of computer programming topics
• Programming paradigms
• Software engineering
• The Art of Computer Programming

References

1. ^ Paul Graham (2003). Hackers and Painters. http://www.paulgraham.com/hp.html. Retrieved 2006-08-22. 
2. ^ Kenneth E. Iverson, the originator of the APL programming language, believed that the Sapir–Whorf hypothesis applied to computer languages (without actually mentioning the hypothesis by name). His Turing award lecture, "Notation as a tool of thought", was devoted to this theme, arguing that more powerful notations aided thinking about computer algorithms. Iverson K.E.,"Notation as a tool of thought", Communications of the ACM, 23: 444-465 (August 1980).
3. ^ New World Encyclopedia Online Edition New World Encyclopedia
4. ^ Al-Jazari - the Mechanical Genius, MuslimHeritage.com
5. ^ A 13th Century Programmable Robot, University of Sheffield
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 
7. ^ Columbia University Computing History - Herman Hollerith
8. ^ [1]
9. ^ [2]
10. ^ Survey of Job advertisements mentioning a given language>

Further reading

• Weinberg, Gerald M., The Psychology of Computer Programming, New York: Van Nostrand Reinhold, 1971

External links

Wikibooks has a book on the topic of Computer programming

Wikibooks has a book on the topic of Windows Programming

• Programming Wikia
• Programming Wiki
• How to Think Like a Computer Scientist - by Jeffrey Elkner, Allen B. Downey and Chris Meyers

v • d • e Major fields of computer science Mathematical foundations Mathematical logic · Set theory · Number theory · Graph theory · Type theory · Category theory · Numerical analysis  · Information theory Theory of computation Automata theory · Computability theory · Computational complexity theory · Quantum computing theory Algorithms and data structures Analysis of algorithms · Algorithm design · Computational geometry Programming languages and Compilers Parsers · Interpreters · Procedural programming · Object-oriented programming · Functional programming · Logic programming · Programming paradigms Concurrent, Parallel, and Distributed systems Multiprocessing · Grid computing · Concurrency control Software engineering Requirements analysis · Software design · Computer programming · Formal methods · Software testing · Software development process System architecture Computer architecture · Computer organization · Operating systems Telecommunication & Networking Computer audio · Routing · Network topology · Cryptography Databases Data mining · Relational databases · SQL • OLAP Artificial intelligence Automated reasoning · Computational linguistics · Computer vision · Evolutionary computation · Expert systems · Machine learning · Natural language processing · Robotics Computer graphics Visualization · Image processing Human computer interaction Computer accessibility · User interfaces · Wearable computing · Ubiquitous computing · Virtual reality Scientific computing Artificial life · Bioinformatics · Cognitive Science · Computational chemistry · Computational neuroscience · Computational physics · Numerical algorithms · Symbolic mathematics NOTE: Computer science can also be split up into different topics or fields according to the ACM Computing Classification System.

v • d • e Software engineering Fields Requirements analysis • System analysis • Software design • Computer programming • Formal methods • Software testing • Software deployment • Software maintenance Concepts Data modeling • Enterprise architecture • Functional specification • Modeling language • Programming paradigm • Software • Software architecture • Software development methodology • Software development process • Software quality • Software quality assurance • Structured analysis Orientations Agile • Aspect-oriented • Object orientation • Ontology • Service orientation • SDLC Models Development models: Agile • Iterative model • RUP • Scrum • Spiral model • Waterfall model • XP • V-Model Other models: Automotive SPICE • CMMI • Data model • Function model • Information model • Metamodeling • Object model • Systems model • View model Modeling languages: IDEF • UML Software engineers Kent Beck • Grady Booch • Fred Brooks • Barry Boehm • Ward Cunningham • Ole-Johan Dahl • Tom DeMarco • Edsger W. Dijkstra • Martin Fowler • C. A. R. Hoare • Watts Humphrey • Michael A. Jackson • Ivar Jacobson • Craig Larman • James Martin • Bertrand Meyer • David Parnas • Winston W. Royce • James Rumbaugh • Niklaus Wirth • Edward Yourdon Related fields Computer science • Computer engineering • Enterprise engineering • History • Management • Mathematics • Project management • Quality management • Software ergonomics • Systems engineering

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