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In computer programming, apply applies a function to a list of arguments. Eval and apply are the two interdependent components of the eval-apply cycle, which is the essence of evaluating Lisp, described in SICP. [1] Function application corresponds to beta reduction in lambda calculus.
A function call using named parameters differs from a regular function call in that the arguments are passed by associating each one with a parameter name, instead of providing an ordered list of arguments. For example, consider this Java or C# method call that doesn't use named parameters:
A higher-order function is a function that takes a function as an argument or returns one as a result. This is commonly used to customize the behavior of a generically defined function, often a looping construct or recursion scheme. Anonymous functions are a convenient way to specify such function arguments. The following examples are in Python 3.
In Python, functions are first-class objects that can be created and passed around dynamically. Python's limited support for anonymous functions is the lambda construct. An example is the anonymous function which squares its input, called with the argument of 5:
A simple example of a higher-ordered function is the map function, which takes, as its arguments, a function and a list, and returns the list formed by applying the function to each member of the list. For a language to support map, it must support passing a function as an argument.
In functional programming languages, variadics can be considered complementary to the apply function, which takes a function and a list/sequence/array as arguments, and calls the function with the arguments supplied in that list, thus passing a variable number of arguments to the function.
What is thought of as functions with multiple parameters is usually represented in lambda calculus as a function which takes the first argument, and returns a function which takes the rest of the arguments; this is a transformation known as currying. Some programming languages, like ML and Haskell, follow this scheme.
Folds can be regarded as consistently replacing the structural components of a data structure with functions and values. Lists, for example, are built up in many functional languages from two primitives: any list is either an empty list, commonly called nil ([]), or is constructed by prefixing an element in front of another list, creating what is called a cons node ( Cons(X1,Cons(X2,Cons ...