COM111 Lecture Schedule 12

COM111 Lecture Schedule 12

Programming paradigms, Introduction to Programming Languages

Programming paradigms:

A programming paradigm is a fundamental style of computer programming, serving as a way of building the structure and elements of computer programs. Capabilities and styles of various programming languages are defined by their supported programming paradigms; some programming languages are designed to follow only one paradigm, while others support multiple paradigms.
Programming paradigms that are often distinguished include imperative, declarative, functional, object-oriented, procedural, logic and symbolic programming. With different paradigms, programs can be seen and built in different ways; for example, in object-oriented programming, a program is a collection of objects interacting in explicitly defined ways, while in declarative programming the computer is told only what the problem is, not how to actually solve it.

Procedural languages:

The next advance was the development of procedural languages. These third-generation languages (the first described as high-level languages) use vocabulary related to the problem being solved. For example,

• COBOL (COmmon Business Oriented Language) – uses terms like file, move and copy.
• FORTRAN (FORmula TRANslation) – using mathematical language terminology, it was developed mainly for scientific and engineering problems.
• ALGOL (ALGOrithmic Language) – focused on being an appropriate language to define algorithms, while using mathematical language terminology and targeting scientific and engineering problems just like FORTRAN.
• PL/I (Programming Language One) – a hybrid commercial/scientific general purpose language supporting pointers.
• BASIC (Beginners All purpose Symbolic Instruction Code) – it was developed to enable more people to write programs.
• C – a general-purpose programming language, initially developed by Dennis Ritchie between 1969 and 1973 at AT&T Bell Labs.

All these languages follow the procedural paradigm. That is, they describe, step by step, exactly the procedure that should, according to the particular programmer at least, be followed to solve a specific problem. The efficacy and efficiency of any such solution are both therefore entirely subjective and highly dependent on that programmer's experience, inventiveness and ability.

Object-oriented programming:

Following the widespread use of procedural languages, object-oriented languages like Simula, Smalltalk, C++, C#, Eiffel and Java were created. In these languages, data and methods of manipulating the data are kept as a single unit called an object. The only way that a user can access the data is via the object's "methods"; as a result, the inner workings of an object may be changed without affecting any code that uses the object. There is still some controversy raised by Alexander Stepanov, Richard Stallman  and other programmers, concerning the efficacy of the OOP paradigm versus the procedural paradigm. The necessity of every object to have associative methods leads some skeptics to associate OOP with software bloat. Polymorphism was developed as one attempt to resolve this dilemma.

Because object-oriented programming is considered a paradigm, not a language, it is possible to create even an object-oriented assembler language. High Level Assembly (HLA) is an example of this that fully supports advanced data types and object-oriented assembly language programming – despite its early origins. Thus, differing programming paradigms can be thought of as more like "motivational memes" of their advocates – rather than necessarily representing progress from one level to the next. Precise comparisons of the efficacy of competing paradigms are frequently made more difficult because of new and differing terminology applied to similar entities and processes together with numerous implementation distinctions across languages.

Further paradigms:

Literate programming, as a form of imperative programming, structures programs as a human-centered web, as in a hypertext essay: documentation is integral to the program, and the program is structured following the logic of prose exposition, rather than compiler convenience.

Independent of the imperative branch, declarative programming paradigms were developed. In these languages the computer is told what the problem is, not how to solve the problem – the program is structured as a collection of properties to find in the expected result, not as a procedure to follow. Given a database or a set of rules, the computer tries to find a solution matching all the desired properties. The archetypical example of a declarative language is the fourth generation language SQL, as well as the family of functional languages and logic programming.

Functional programming is a subset of declarative programming. Programs written using this paradigm use functions, blocks of code intended to behave like mathematical functions. Functional languages discourage changes in the value of variables through assignment, making a great deal of use of recursion instead.

The logic programming paradigm views computation as automated reasoning over a corpus of knowledge. Facts about the problem domain are expressed as logic formulae, and programs are executed by applying inference rules over them until an answer to the problem is found, or the collection of formulae is proved inconsistent.

Symbolic programming is a paradigm that describes programs able to manipulate formulas and program components as data. Programs can thus effectively modify themselves, and appear to "learn", making them suited for applications such as artificial intelligence, expert systems, natural language processing and computer games. Languages that support this paradigm include LISP and Prolog.

Multi-paradigm:

A multi-paradigm programming language is a programming language that supports more than one programming paradigm. The design goal of such languages is to allow programmers to use the most suitable programming style and associated language constructs for a particular job, considering that no single paradigm solves all problems in the easiest or most efficient way.

One example is C#, which includes imperative and object-oriented paradigms as well as some support for functional programming with features like delegates (allowing functions to be treated as first-order objects), type inference, anonymous functions and Language Integrated Query. Other examples are F# and Scala, which provides similar functionality to C# but also includes full support for functional programming (including currying, pattern matching, algebraic data types, lazy evaluation, tail recursion, immutability, etc.). Perhaps the most extreme example is Oz, which has subsets that adhere to logic (Oz descends from logic programming), functional, object-oriented, dataflow concurrent, and other paradigms. Oz was designed over a ten-year period to combine in a harmonious way concepts that are traditionally associated with different programming paradigms. Lisp, while often taught as a functional language, is known for its malleability and thus its ability to engulf many paradigms.

Programming language

A programming language is a notation for writing programs, which are specifications of a computation or algorithm. Some, but not all, authors restrict the term "programming language" to those languages that can express all possible algorithms. Traits often considered important for what constitutes a programming language include:

Function and target

A computer programming language is a language used to write computer programs, which involve a computer performing some kind of computation or algorithm and possibly control external devices such as printers, disk drives, robots, and so on. For example, PostScript programs are frequently created by another program to control a computer printer or display. More generally, a programming language may describe computation on some, possibly abstract, machine.

It is generally accepted that a complete specification for a programming language includes a description, possibly idealized, of a machine or processor for that language. In most practical contexts, a programming language involves a computer; consequently, programming languages are usually defined and studied this way. Programming languages differ from natural languages in that natural languages are only used for interaction between people, while programming languages also allow humans to communicate instructions to machines.

Abstractions

Programming languages usually contain abstractions for defining and manipulating data structures or controlling the flow of execution. The practical necessity that a programming language support adequate abstractions is expressed by the abstraction principle; this principle is sometimes formulated as recommendation to the programmer to make proper use of such abstractions.

Expressive power

The theory of computation classifies languages by the computations they are capable of expressing. All Turing complete languages can implement the same set of algorithms. ANSI/ISO SQL-92 and Charity are examples of languages that are not Turing complete, yet often called programming languages.^[11][12]

Markup languages like XML, HTML or troff, which define structured data, are not usually considered programming languages. Programming languages may, however, share the syntax with markup languages if a computational semantics is defined. XSLT, for example, is a Turing complete XML dialect. Moreover, LaTeX, which is mostly used for structuring documents, also contains a Turing complete subset.

The term computer language is sometimes used interchangeably with programming language. However, the usage of both terms varies among authors, including the exact scope of each. One usage describes programming languages as a subset of computer languages. In this vein, languages used in computing that have a different goal than expressing computer programs are generically designated computer languages. For instance, markup languages are sometimes referred to as computer languages to emphasize that they are not meant to be used for programming.

Another usage regards programming languages as theoretical constructs for programming abstract machines, and computer languages as the subset thereof that runs on physical computers, which have finite hardware resources. John C. Reynolds emphasizes that formal specification languages are just as much programming languages as are the languages intended for execution. He also argues that textual and even graphical input formats that affect the behavior of a computer are programming languages, despite the fact they are commonly not Turing-complete, and remarks that ignorance of programming language concepts is the reason for many flaws in input formats.