In computer sciencefunctional programming is a programming paradigm —a style of building the structure and elements of computer programs —that treats computation as the evaluation of mathematical functions and avoids changing- state and mutable data. It is a declarative programming paradigm, which means programming is done with expressions [1] or declarations [2] instead of statements.
In functional code, the output value of a function depends only on the arguments that are passed to the function, so calling a function f twice with the same value for an argument x produces the same result f x each time; this is in contrast to procedures depending on a trading robot programming course 003 variables if formula or global statewhich may produce different results at different times when called with the same arguments but a different program state.
Eliminating side effectsi. Functional programming has its origins in lambda calculusa formal system developed in the s to investigate computabilitythe Entscheidungsproblemfunction definition, function applicationand recursion. Many functional programming languages can be viewed as elaborations on the lambda calculus.
Another well-known declarative programming paradigm, logic programmingis based on relations. In contrast, imperative programming changes state with commands in the source codethe simplest example being assignment.
Imperative programming does have subroutine functions, but trading robot programming course 003 variables if formula are not functions in the mathematical sense. They can have side effects that may change the value of program state.
Functions without return values therefore make sense. Trading robot programming course 003 variables if formula of this, they lack referential transparencyi. Functional programming languages have trading robot programming course 003 variables if formula been emphasized in academia rather than in commercial software development.
However, prominent programming languages that support functional programming such as Common LispScheme[4] [5] [6] [7] Clojure[8] [9] Wolfram Language [10] also known as MathematicaRacket[11] Erlang[12] [13] [14] OCaml[15] [16] Haskell[17] [18] and F [19] [20] have been used in industrial and commercial applications by a wide variety of organizations. JavaScriptone of the world's most widely distributed languages, [21] [22] has the properties of an untyped functional language, [23] in addition to imperative and object-oriented paradigms.
Programming in a functional style can also be accomplished in languages that are not specifically designed for functional programming. For example, the imperative Perl programming language has been the subject of a book describing how to apply functional programming concepts.
The Julia language also offers functional programming abilities. An interesting case is that of Scala [31] — it is frequently written in a functional style, but the presence of side effects and mutable state place it in a grey area between imperative and functional languages. Lambda calculus trading robot programming course 003 variables if formula a theoretical framework for describing functions and their evaluation. It is a mathematical abstraction rather than a programming language—but it forms the basis of almost all current functional programming languages.
An equivalent theoretical formulation, combinatory logicis commonly perceived as more abstract than lambda calculus and preceded it in invention.
Combinatory logic and lambda calculus were both originally developed to achieve a clearer approach to the foundations of mathematics. Later dialects, such as Scheme and Clojureand offshoots such as Dylan and Juliasought to simplify and rationalise Lisp around a cleanly functional core, while Common Lisp was designed to preserve and update the paradigmatic features of the numerous older dialects it replaced.
Information Processing Language IPL is sometimes cited as the first computer-based functional programming language. It does have a notion of generatorwhich amounts to a function that accepts a function as an argument, and, since it is an assembly-level language, code can be data, so IPL can be regarded as having higher-order functions. However, it relies heavily on mutating list structure and similar imperative features.
In the early s, Iverson and Roger Hui created J. In the mids, Arthur Whitneywho had previously worked with Iverson, created Kwhich is used commercially in financial industries along with its descendant Q.
A Functional Style and its Algebra of Programs". Backus's paper popularized research into functional programming, though it emphasized function-level programming rather than the lambda-calculus style now associated with functional programming.
Meanwhile, the development of Schemea simple lexically scoped and impurely functional dialect of Lisp, as described in the influential Lambda Papers and the classic textbook Structure and Interpretation of Computer Programsbrought awareness of the power of functional programming to the wider programming-languages community.
This led to powerful new approaches to interactive theorem proving and has influenced the development of many subsequent functional programming languages. The Haskell language began with a consensus in to form an open standard for functional programming research; implementation releases have been ongoing since A number of concepts and paradigms trading robot programming course 003 variables if formula specific to functional programming, and generally foreign to imperative programming including object-oriented programming.
However, programming languages are often hybrids of several programming paradigms, so programmers using "mostly imperative" languages may have utilized some of these concepts. Higher-order functions are functions that can either take other functions as arguments or return them as results. Higher-order functions are closely related to first-class functions in that higher-order functions and first-class functions trading robot programming course 003 variables if formula allow functions as arguments and results of other functions.
The distinction between the two is subtle: Higher-order functions enable partial application or curryinga technique that applies a function to its arguments one at a time, with each application returning a new function that accepts the next argument.
This lets a programmer succinctly express, for example, the successor function as the addition operator partially applied to the natural number one. This means that pure functions have several useful properties, many of which can be used to optimize the code:. While most compilers for imperative programming languages detect pure functions and perform common-subexpression elimination for pure function calls, they cannot always do this for pre-compiled libraries, which generally do not expose this information, thus preventing optimizations that involve those external functions.
Some compilers, such as gccadd extra keywords for a programmer to explicitly mark external functions as pure, to enable such optimizations. Fortran 95 also lets functions be designated pure. Iteration looping in functional languages is usually accomplished via recursion.
Recursive functions invoke themselves, letting an operation be repeated until it reaches the base case. Though some recursion requires maintaining a stack, tail recursion can be recognized and optimized by a compiler into the same code used to implement iteration in imperative languages.
The Scheme language standard requires implementations to recognize and optimize tail recursion. Tail recursion optimization can be implemented by transforming the program into continuation passing style during compiling, among other approaches. Common patterns of recursion can be factored out using higher order functions, with catamorphisms and anamorphisms or "folds" and "unfolds" being the most obvious examples. Such higher order functions play a role analogous to built-in control structures such as loops in imperative languages.
Most general purpose functional programming languages allow unrestricted recursion and are Turing completewhich makes the halting problem undecidablecan cause unsoundness of equational reasoningand generally requires the introduction of inconsistency into the logic expressed by the language's type system.
Some special purpose languages such as Coq trading robot programming course 003 variables if formula only well-founded recursion and are strongly normalizing nonterminating computations can be expressed only with infinite streams of values called codata. As a consequence, these languages fail to be Turing complete and expressing certain functions in them is impossible, but they can still express a wide class of interesting computations while avoiding the problems introduced by unrestricted recursion.
Functional programming limited to trading robot programming course 003 variables if formula recursion with a trading robot programming course 003 variables if formula other constraints is called total functional programming.
Functional languages can be categorized by whether they use strict eager or non-strict lazy evaluation, concepts that refer to how function arguments are processed when an expression is being evaluated. The technical difference is in the denotational semantics of expressions containing failing or divergent computations.
Under strict evaluation, the evaluation of any term containing a failing subterm fails. For example, the expression:. Under lazy evaluation, trading robot programming course 003 variables if formula length function returns the value 4 i. In brief, strict evaluation always fully evaluates function arguments before invoking the function. Lazy evaluation does not evaluate function arguments unless their values are required to evaluate the function call itself.
The usual implementation strategy for lazy evaluation in functional languages is graph reduction. Hughes argues for lazy evaluation as a mechanism for improving program modularity through separation of concernsby easing independent implementation of producers and consumers of data streams. Especially since the development of Hindley—Milner type inference in the s, functional programming languages have tended to use typed lambda calculusrejecting all invalid programs at compilation time and risking false positive errorsas opposed to the untyped lambda calculusthat accepts all valid programs at compilation time and risks false negative errorstrading robot programming course 003 variables if formula in Lisp and its variants such as Schemethough they reject all invalid programs at runtime, when the information is enough to not reject valid programs.
The use of algebraic datatypes makes manipulation of complex data structures convenient; the presence of strong compile-time type checking makes programs more reliable in absence of other reliability techniques like test-driven developmentwhile type inference frees the programmer from the need to manually declare types to the compiler in most cases.
Some research-oriented functional languages such as CoqAgdaCayenneand Epigram are based on intuitionistic type theorywhich lets types depend on terms. Such types are called dependent types. These type systems do not have decidable type inference and are difficult to understand and program with [ citation needed ].
But dependent types can express arbitrary propositions in predicate logic. Through the Curry—Howard isomorphismthen, well-typed programs in trading robot programming course 003 variables if formula languages become a means of writing formal mathematical proofs from which a compiler can generate certified code.
While these languages are mainly of interest in academic research including in formalized mathematicsthey have begun to be used in engineering as well. Compcert is a compiler for a subset of the C programming language that is written in Coq and formally verified.
A limited form of dependent types called generalized algebraic data types GADT's can be implemented in a way that provides some trading robot programming course 003 variables if formula the benefits of dependently typed programming while avoiding most of its inconvenience. Functional programs do not have assignment statements, that is, the value of a variable in a functional program never changes once defined. This eliminates any chances of side effects because any variable can be replaced with its actual value at any point of execution.
So, functional programs are referentially transparent. Let us say that the initial value of x was 1then two consecutive evaluations of the variable x yields 10 and respectively.
In fact, assignment statements are never referentially transparent. Functional programs exclusively use trading robot programming course 003 variables if formula type of function and are therefore referentially transparent.
It is possible to use a functional style of programming in languages that are not traditionally considered functional languages. JavaScriptLua [52] and Python had first class functions from their inception. In PHPanonymous classesclosures and lambdas are fully supported. Libraries and language extensions for immutable data structures are being developed to aid programming in the functional style.
In Javaanonymous classes can sometimes be used to simulate closures ; [56] however, anonymous classes are not always proper replacements to closures because they have more limited capabilities. In Canonymous classes are not necessary, because closures and lambdas are fully supported.
Libraries and language extensions for immutable data structures are being developed to aid programming in the functional style in C. Trading robot programming course 003 variables if formula object-oriented design patterns are expressible in functional programming terms: Similarly, the idea of immutable data from functional programming is often included in imperative programming languages, [59] for example the tuple in Python, which is an immutable array.
Purely functional data structures are often represented in a different way than their imperative counterparts. Arrays can be replaced by maps or random access listswhich admit purely functional implementation, but have logarithmic access and update times. Therefore, purely functional data structures can be used in non-functional languages, but they may not be the most efficient tool, especially if persistence is not required.
Functional programming is very different from imperative programming. Pure functional programming completely prevents side-effects and provides referential transparency. Higher-order functions are rarely used in older imperative programming.
A traditional imperative program might use a loop to traverse and modify a list. There are tasks for example, maintaining a bank account balance that often seem most naturally implemented with state.
The pure functional programming language Haskell implements them using monadsderived from category theory.
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