Many programming languages have some form of written specification of their syntax and semantics, since computers require precisely defined instructions. Some are defined by a specification document (for example, an ISO Standard), while others have a dominant implementation (such as Perl).
The earliest programming languages predate the invention of the computer, and were used to direct the behavior of machines such as automated looms and player pianos. Thousands of different programming languages have been created, mainly in the computer field , where many more are being created every year.
Traits often considered important for constituting a programming language:
Some authors restrict the term "programming language" to those languages that can express all possible algorithms; sometimes the term "computer language" is used for more limited artificial languages.
Non-computational languages, such as markup languages like HTML or formal grammars like BNF, are usually not considered programming languages. A programming language (which may or may not be Turing complete) may be embedded in these non-computational (host) languages.
A programming language provides a structured mechanism for defining pieces of data, and the operations or transformations that may be carried out automatically on that data. The abstractions present in the language allow a programmer to represent the concepts involved in a computation as a collection of the simple elements available (called primitives).
Programming languages (sometimes also known as computer languages) differ from most other forms of human expression in that they require a greater degree of precision and completeness. When using a natural language to communicate with other people, human authors and speakers can be ambiguous and make small errors, and still expect their intent to be understood. However, figuratively speaking, computers "do exactly what they are told to do", and cannot "understand" what code the programmer intended to write. The combination of the language definition, a program, and the program's inputs must fully specify the external behavior that occurs when the program is executed, within the domain of control of that program.
Programs for a computer might be executed in a batch process without human interaction, or a user might type commands in an interactive session of an interpreter. In this case the "commands" are simply programs, whose execution is chained together. When a language is used to give commands to a software application (such as a shell) it is called a scripting language.
Many languages have been designed from scratch, altered to meet new needs, combined with other languages, and eventually fallen into disuse. Although there have been attempts to design one "universal" computer language that serves all purposes, all of them have failed to be generally accepted as filling this role. The need for diverse computer languages arises from the diversity of contexts in which languages are used:
One common trend in the development of programming languages has been to add more ability to solve problems using a higher level of abstraction. The earliest programming languages were tied very closely to the underlying hardware of the computer. As new programming languages have developed, features have been added that let programmers express ideas that are more remote from simple translation into underlying hardware instructions. Because programmers are less tied to the complexity of the computer, their programs can do more computing with less effort from the programmer. This lets them write more functionality per time unit.
Natural language processors have been proposed as a way to eliminate the need for a specialized language for programming. However, this goal remains distant and its benefits are open to debate. Edsger Dijkstra took the position that the use of a formal language is essential to prevent the introduction of meaningless constructs, and dismissed natural language programming as "foolish." Alan Perlis was similarly dismissive of the idea.
All programming languages have some primitive building blocks for the description of data and the processes or transformations applied to them (like the addition of two numbers or the selection of an item from a collection). These primitives are defined by syntactic and semantic rules which describe their structure and meaning respectively.
A programming language's surface form is known as its syntax. Most programming languages are purely textual; they use sequences of text including words, numbers, and punctuation, much like written natural languages. On the other hand, there are some programming languages which are more graphical in nature, using visual relationships between symbols to specify a program.
The syntax of a language describes the possible combinations of symbols that form a syntactically correct program. The meaning given to a combination of symbols is handled by semantics (either formal or hard-coded in a reference implementation). Since most languages are textual, this article discusses textual syntax.
Programming language syntax is usually defined using a combination of regular expressions (for lexical structure) and Backus-Naur Form (for grammatical structure). Below is a simple grammar, based on Lisp:
This grammar specifies the following:
The following are examples of well-formed token sequences
in this grammar: '
Not all syntactically correct programs are semantically correct. Many syntactically correct programs are nonetheless ill-formed, per the language's rules; and may (depending on the language specification and the soundness of the implementation) result in an error on translation or execution. In some cases, such programs may exhibit undefined behavior. Even when a program is well-defined within a language, it may still have a meaning that is not intended by the person who wrote it.
Using natural language as an example, it may not be possible to assign a meaning to a grammatically correct sentence or the sentence may be false:
The following C language fragment is syntactically correct, but performs an operation that is not semantically defined (because p is a null pointer, the operations p->real and p->im have no meaning):
complex *p = NULL; complex abs_p = sqrt (p->real * p->real + p->im * p->im);
The grammar needed to specify a programming language can be classified by its position in the Chomsky hierarchy. The syntax of most programming languages can be specified using a Type-2 grammar, i.e., they are context-free grammars.
The static semantics defines restrictions on the structure of valid texts that are hard or impossible to express in standard syntactic formalisms. The most important of these restrictions are covered by type systems.
A type system defines how a programming language classifies values and expressions into types, how it can manipulate those types and how they interact. This generally includes a description of the data structures that can be constructed in the language. The design and study of type systems using formal mathematics is known as type theory.
Typed versus untyped languages
A language is typed if the specification of every
operation defines types of data to which the operation is
applicable, with the implication that it is not applicable
to other types.
For example, "
A special case of typed languages are the single-type languages. These are often scripting or markup languages, such as Rexx or SGML, and have only one data type — most commonly character strings which are used for both symbolic and numeric data.
In contrast, an untyped language, such as most assembly languages, allows any operation to be performed on any data, which are generally considered to be sequences of bits of various lengths. High-level languages which are untyped include BCPL and some varieties of Forth.
In practice, while few languages are considered typed from the point of view of type theory (verifying or rejecting all operations), most modern languages offer a degree of typing. Many production languages provide means to bypass or subvert the type system.
Static versus dynamic typing
In static typing all expressions have their types determined prior to the program being run (typically at compile-time). For example, 1 and (2+2) are integer expressions; they cannot be passed to a function that expects a string, or stored in a variable that is defined to hold dates.
Weak and strong typing
Weak typing allows a value of one type to be treated as another, for example treating a string as a number. This can occasionally be useful, but it can also allow some kinds of program faults to go undetected at compile time and even at run time.
An alternative definition for "weakly typed" refers to
languages, such as Perl,
which permit a large number of implicit type conversions.
Strong and static are now generally considered orthogonal concepts, but usage in the literature differs. Some use the term strongly typed to mean strongly, statically typed, or, even more confusingly, to mean simply statically typed. Thus C has been called both strongly typed and weakly, statically typed.
Once data has been specified, the machine must be instructed to perform operations on the data. The execution semantics of a language defines how and when the various constructs of a language should produce a program behavior.
Most programming languages have an associated core library (sometimes known as the 'Standard library', especially if it is included as part of the published language standard), which is conventionally made available by all implementations of the language. Core libraries typically include definitions for commonly used algorithms, data structures, and mechanisms for input and output.
A language's core library is often treated as part of the language by its users, although the designers may have treated it as a separate entity. Many language specifications define a core that must be made available in all implementations, and in the case of standardized languages this core library may be required. The line between a language and its core library therefore differs from language to language. Indeed, some languages are designed so that the meanings of certain syntactic constructs cannot even be described without referring to the core library. For example, in Java, a string literal is defined as an instance of the java.lang.String class; similarly, in Smalltalk, an anonymous function expression (a "block") constructs an instance of the library's BlockContext class. Conversely, Scheme contains multiple coherent subsets that suffice to construct the rest of the language as library macros, and so the language designers do not even bother to say which portions of the language must be implemented as language constructs, and which must be implemented as parts of a library.
A language's designers and users must construct a number of artifacts that govern and enable the practice of programming. The most important of these artifacts are the language specification and implementation.
The specification of a programming language is intended to provide a definition that the language users and the implementors can use to determine whether the behavior of a program is correct, given its source code.
A programming language specification can take several forms, including the following:
An implementation of a programming language provides a way to execute that program on one or more configurations of hardware and software. There are, broadly, two approaches to programming language implementation: compilation and interpretation. It is generally possible to implement a language using either technique.
Programs that are executed directly on the hardware usually run several orders of magnitude faster than those that are interpreted in software.
One technique for improving the performance of interpreted programs is just-in-time compilation. Here the virtual machine, just before execution, translates the blocks of bytecode which are going to be used to machine code, for direct execution on the hardware.
For more details on this topic, see History of programming languages.
The first programming languages predate the modern computer. The 19th century had "programmable" looms and player piano scrolls which implemented what are today recognized as examples of domain-specific programming languages. By the beginning of the twentieth century, punch cards encoded data and directed mechanical processing. In the 1930s and 1940s, the formalisms of Alonzo Church's lambda calculus and Alan Turing's Turing machines provided mathematical abstractions for expressing algorithms; the lambda calculus remains influential in language design.
In the 1940s, the first electrically powered digital computers were created. The first high-level programming language to be designed for a computer was Plankalkül, developed for the German Z3 by Konrad Zuse between 1943 and 1945.
The computers of the early 1950s, notably the UNIVAC I and the IBM 701 used machine language programs. First generation machine language programming was quickly superseded by a second generation of programming languages known as Assembly languages. Later in the 1950s, assembly language programming, which had evolved to include the use of macro instructions, was followed by the development of three higher-level programming languages: FORTRAN, LISP, and COBOL. Updated versions of all of these are still in general use, and each has strongly influenced the development of later languages. At the end of the 1950s, the language formalized as Algol 60 was introduced, and most later programming languages are, in many respects, descendants of Algol. The format and use of the early programming languages was heavily influenced by the constraints of the interface.
The period from the 1960s to the late 1970s brought the development of the major language paradigms now in use, though many aspects were refinements of ideas in the very first Third-generation programming languages:
Each of these languages spawned an entire family of descendants, and most modern languages count at least one of them in their ancestry.
The 1960s and 1970s also saw considerable debate over the merits of structured programming, and whether programming languages should be designed to support it. Edsger Dijkstra, in a famous 1968 letter published in the Communications of the ACM, argued that GOTO statements should be eliminated from all "higher level" programming languages.
The 1960s and 1970s also saw expansion of techniques that reduced the footprint of a program as well as improved productivity of the programmer and user. The card deck for an early 4GL was a lot smaller for the same functionality expressed in a 3GL deck.
Consolidation and growth
The 1980s were years of relative consolidation. C++ combined object-oriented and systems programming. The United States government standardized Ada, a systems programming language intended for use by defense contractors. In Japan and elsewhere, vast sums were spent investigating so-called "fifth generation" languages that incorporated logic programming constructs. The functional languages community moved to standardize ML and Lisp. Rather than inventing new paradigms, all of these movements elaborated upon the ideas invented in the previous decade.
One important trend in language design during the 1980s was an increased focus on programming for large-scale systems through the use of modules, or large-scale organizational units of code. Modula-2, Ada, and ML all developed notable module systems in the 1980s, although other languages, such as PL/I, already had extensive support for modular programming. Module systems were often wedded to generic programming constructs.
The rapid growth of the Internet in the mid-1990s created opportunities for new languages. Perl, originally a Unix scripting tool first released in 1987, became common in dynamic Web sites. Java came to be used for server-side programming. These developments were not fundamentally novel, rather they were refinements to existing languages and paradigms, and largely based on the C family of programming languages.
Programming language evolution continues, in both industry and research. Current directions include security and reliability verification, new kinds of modularity (mixins, delegates, aspects), and database integration.
Measuring language usage
It is difficult to determine which programming languages are most widely used, and what usage means varies by context. One language may occupy the greater number of programmer hours, a different one have more lines of code, and a third utilize the most CPU time. Some languages are very popular for particular kinds of applications. For example, COBOL is still strong in the corporate data center, often on large mainframes; FORTRAN in engineering applications; C in embedded applications and operating systems; and other languages are regularly used to write many different kinds of applications.
Various methods of measuring language popularity, each subject to a different bias over what is measured, have been proposed:
There is no overarching classification scheme for programming languages. A given programming language does not usually have a single ancestor language. Languages commonly arise by combining the elements of several predecessor languages with new ideas in circulation at the time. Ideas that originate in one language will diffuse throughout a family of related languages, and then leap suddenly across familial gaps to appear in an entirely different family.
The task is further complicated by the fact that languages can be classified along multiple axes. For example, Java is both an object-oriented language (because it encourages object-oriented organization) and a concurrent language (because it contains built-in constructs for running multiple threads in parallel). Python is an object-oriented scripting language.
In broad strokes, programming languages divide into programming paradigms and a classification by intended domain of use. Paradigms include procedural programming, object-oriented programming, functional programming, and logic programming; some languages are hybrids of paradigms or multi-paradigmatic. An assembly language is not so much a paradigm as a direct model of an underlying machine architecture. By purpose, programming languages might be considered general purpose, system programming languages, scripting languages, domain-specific languages, or concurrent/distributed languages (or a combination of these). Some general purpose languages were designed largely with educational goals.
A programming language may also be classified by factors unrelated to programming paradigm. For instance, most programming languages use English language keywords, while a minority do not. Other languages may be classified as being esoteric or not.
Published - December 2008
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