ⓘ Computer programming

Programming language

A programming language is a formal language, which comprises a set of instructions that produce various kinds of output. Programming languages are used in computer programming to implement algorithms. Most programming languages consist of instructions for computers. There are programmable machines that use a set of specific instructions, rather than general programming languages. Early ones preceded the invention of the digital computer, the first probably being the automatic flute player described in the 9th century by the brothers Musa in Baghdad, during the Islamic Golden Age. Since the ...

Software framework

In computer programming, a software framework is an abstraction in which software providing generic functionality can be selectively changed by additional user-written code, thus providing application-specific software. It provides a standard way to build and deploy applications and is a universal, reusable software environment that provides particular functionality as part of a larger software platform to facilitate development of software applications, products and solutions. Software frameworks may include support programs, compilers, code libraries, tool sets, and application programmi ...

Integrated development environment

An integrated development environment is a software application that provides comprehensive facilities to computer programmers for software development. An IDE normally consists of at least a source code editor, build automation tools and a debugger. Some IDEs, such as NetBeans and Eclipse, contain the necessary compiler, interpreter, or both; others, such as SharpDevelop and Lazarus, do not. The boundary between an IDE and other parts of the broader software development environment is not well-defined; sometimes a version control system or various tools to simplify the construction of a g ...

Automata-based programming

Automata-based programming is a programming paradigm in which the program or part of it is thought of as a model of a finite-state machine or any other formal automaton. Sometimes a potentially infinite set of possible states is introduced, and such a set can have a complicated structure, not just an enumeration. Finite-state machine-based programming is generally the same, but, formally speaking, does not cover all possible variants, as FSM stands for finite-state machine, and automata-based programming does not necessarily employ FSMs in the strict sense. The following properties are key ...

Coupling (computer programming)

In software engineering, coupling is the degree of interdependence between software modules; a measure of how closely connected two routines or modules are; the strength of the relationships between modules. Coupling is usually contrasted with cohesion. Low coupling often correlates with high cohesion, and vice versa. Low coupling is often a sign of a well-structured computer system and a good design, and when combined with high cohesion, supports the general goals of high readability and maintainability.

Comet (programming)

Comet is a web application model in which a long-held HTTPS request allows a web server to push data to a browser, without the browser explicitly requesting it. Comet is an umbrella term, encompassing multiple techniques for achieving this interaction. All these methods rely on features included by default in browsers, such as JavaScript, rather than on non-default plugins. The Comet approach differs from the original model of the web, in which a browser requests a complete web page at a time. The use of Comet techniques in web development predates the use of the word Comet as a neologism ...

                                     

ⓘ Computer programming

Computer programming is the process of designing and building an executable computer program to accomplish a specific computing result. Programming involves tasks such as: analysis, generating algorithms, profiling algorithms accuracy and resource consumption, and the implementation of algorithms in a chosen programming language. 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 on a computer, often for solving a given problem. The process of 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 the opposite process. A hacker is any skilled computer expert that uses their technical knowledge to overcome a problem, but it can also mean a security hacker in common language.

                                     

1. History

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. 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. 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.

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 Babbages Analytical Engine.

In the 1880s Herman Hollerith invented the concept of storing data in machine-readable form. 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.

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, 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.

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 and many other languages were soon developed – in particular, COBOL aimed at commercial data processing, and Lisp for computer research.

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. Text editors programs themselves were developed that allowed changes and corrections to be made much more easily than with punched cards.

                                     

2.1. 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:

  • Maintainability: the ease with which a program can be modified by its present or future developers in order to make improvements or customisations, 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.
  • 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 behavior of the hardware and operating system, and availability of platform specific compilers and sometimes libraries for the language of the source code.
  • 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 programs user interface.
  • Efficiency/performance: Measure of system resources a program consumes: the less, the better. This also includes careful management of resources, for example cleaning up temporary files and eliminating 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 or off-by-one errors.
  • Robustness: 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.
                                     

2.2. Modern programming 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 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. Some of these factors include:

  • Different indent styles whitespace
  • Decomposition
  • Naming conventions for objects
  • Comments

The presentation aspects of this are often handled by the source code editor, but the content aspects reflect the programmers 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.



                                     

2.3. Modern programming 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.

                                     

2.4. Modern programming 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 IBMs Deep Blue chess computer is part of the computer science curriculum at Stanford University.

                                     

2.5. Modern programming 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.



                                     

2.6. Modern programming Measuring language usage

It is very difficult to determine what are the most popular of modern programming languages. Methods of measuring programming language popularity include: counting the number of job advertisements that mention the language, 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 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.



                                     

2.7. Modern programming Debugging

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, a bug in a compiler can make it crash when passing some large source file. However, after simplification of the test case, only few lines from the original source file can be sufficient to reproduce the same crash. Such simplification can be done manually, using a divide-and-conquer approach. The programmer will try to remove some parts of 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.

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 editors such as Emacs allow GDB to be invoked through them, to provide a visual environment.

                                     

3. 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:
  • Repetition: Perform some action repeatedly, usually with some variation.
  • Output: Display data on the screen or send data to a file or other device.
  • Input: Gather data from the keyboard, a file, or some other device.
  • Arithmetic: Perform basic arithmetical operations like addition and multiplication.
  • Conditional Execution: Check for certain conditions and execute the appropriate sequence of statements.

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.