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Static semantics[ edit ] The static semantics defines restrictions on the structure of valid texts that are hard or impossible to express in standard syntactic formalisms.
Examples include checking that every identifier is declared before it is used in languages that require such declarations or that the labels on the arms of a case statement are distinct. Other forms of static analyses like data flow analysis may also be part of static semantics. Newer programming languages like Java and C have definite assignment analysis , a form of data flow analysis, as part of their static semantics.
Main article: Semantics of programming languages Once data has been specified, the machine must be instructed to perform operations on the data.
For example, the semantics may define the strategy by which expressions are evaluated to values, or the manner in which control structures conditionally execute statements.
The dynamic semantics also known as execution semantics of a language defines how and when the various constructs of a language should produce a program behavior. There are many ways of defining execution semantics. Natural language is often used to specify the execution semantics of languages commonly used in practice.
A significant amount of academic research went into formal semantics of programming languages , which allow execution semantics to be specified in a formal manner.
Results from this field of research have seen limited application to programming language design and implementation outside academia. Main articles: Data type , Type system , and Type safety A type system defines how a programming language classifies values and expressions into types, how it can manipulate those types and how they interact.
The goal of a type system is to verify and usually enforce a certain level of correctness in programs written in that language by detecting certain incorrect operations. Any decidable type system involves a trade-off: while it rejects many incorrect programs, it can also prohibit some correct, albeit unusual programs. In order to bypass this downside, a number of languages have type loopholes, usually unchecked casts that may be used by the programmer to explicitly allow a normally disallowed operation between different types.
In most typed languages, the type system is used only to type check programs, but a number of languages, usually functional ones, infer types , relieving the programmer from the need to write type annotations. The formal design and study of type systems is known as type theory. Typed versus untyped languages[ edit ] A language is typed if the specification of every operation defines types of data to which the operation is applicable.
The invalid operation may be detected when the program is compiled "static" type checking and will be rejected by the compiler with a compilation error message, or it may be detected while the program is running "dynamic" type checking , resulting in a run-time exception. Many languages allow a function called an exception handler to handle this exception and, for example, always return "-1" as the result.
A special case of typed languages are the single-typed languages. These are often scripting or markup languages, such as REXX or SGML , and have only one data type[ dubious — discuss ]——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, generally sequences of bits of various lengths.
In practice, while few languages are considered typed from the type theory verifying or rejecting all operations , most modern languages offer a degree of typing. Static versus dynamic typing[ edit ] In static typing , all expressions have their types determined prior to when the program is executed, typically at compile-time. In the first case, the programmer must explicitly write types at certain textual positions for example, at variable declarations. In the second case, the compiler infers the types of expressions and declarations based on context.
Complete type inference has traditionally been associated with less mainstream languages, such as Haskell and ML. Dynamic typing , also called latent typing, determines the type-safety of operations at run time; in other words, types are associated with run-time values rather than textual expressions. Among other things, this may permit a single variable to refer to values of different types at different points in the program execution.
However, type errors cannot be automatically detected until a piece of code is actually executed, potentially making debugging more difficult. Weak and strong typing[ edit ] Weak typing allows a value of one type to be treated as another, for example treating a string as a number.
Such implicit conversions are often useful, but they can mask programming errors. 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. This is extremely similar to somehow casting an array of bytes to any kind of datatype in C without using an explicit cast, such as int or char.
Core libraries typically include definitions for commonly used algorithms, data structures, and mechanisms for input and output. The line between a language and its core library differs from language to language. In some cases, the language designers may treat the library as a separate entity from the 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. 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.
Design and implementation[ edit ] Programming languages share properties with natural languages related to their purpose as vehicles for communication, having a syntactic form separate from its semantics, and showing language families of related languages branching one from another. A significant difference is that a programming language can be fully described and studied in its entirety, since it has a precise and finite definition.
While constructed languages are also artificial languages designed from the ground up with a specific purpose, they lack the precise and complete semantic definition that a programming language has.
Many programming languages have been designed from scratch, altered to meet new needs, and combined with other languages. Many have eventually fallen into disuse.
Although there have been attempts to design one "universal" programming language that serves all purposes, all of them have failed to be generally accepted as filling this role. Programmers range in expertise from novices who need simplicity above all else, to experts who may be comfortable with considerable complexity. Programs must balance speed, size, and simplicity on systems ranging from microcontrollers to supercomputers.
Programs may be written once and not change for generations, or they may undergo continual modification. Programmers may simply differ in their tastes: they may be accustomed to discussing problems and expressing them in a particular language. 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. However, this goal remains distant and its benefits are open to debate. Edsger W. 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".
The most important of these artifacts are the language specification and implementation. Main article: Programming language specification The specification of a programming language is an artifact that the language users and the implementors can use to agree upon whether a piece of source code is a valid program in that language, and if so what its behavior shall be. A programming language specification can take several forms, including the following: An explicit definition of the syntax, static semantics, and execution semantics of the language.
While syntax is commonly specified using a formal grammar, semantic definitions may be written in natural language e. A description of the behavior of a translator for the language e. The syntax and semantics of the language have to be inferred from this description, which may be written in natural or a formal language.
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