In functional programming, fold (also termed reduce, accumulate, aggregate, compress, or inject) refers to a family of higher-order functions that analyze a recursive data structure and through use of a given combining operation, recombine the results of recursively processing its constituent parts, building up a return value. Typically, a fold is presented with a combining function, a top node of a data structure, and possibly some default values to be used under certain conditions. The fold then proceeds to combine elements of the data structure's hierarchy, using the function in a systematic way. Folds are in a sense dual to unfolds, which take a seed value and apply a function corecursively to decide how to progressively construct a corecursive data structure, whereas a fold recursively breaks that structure down, replacing it with the results of applying a combining function at each node on its terminal values and the recursive results (catamorphism, versus anamorphism of unfolds). 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(...(Cons(Xn,nil))))) ), resulting from application of a cons function (written down as a colon (:) in Haskell). One can view a fold on lists as replacing the nil at the end of the list with a specific value, and replacing each cons with a specific function. These replacements can be viewed as a diagram: There's another way to perform the structural transformation in a consistent manner, with the order of the two links of each node flipped when fed into the combining function: These pictures illustrate right and left fold of a list visually. They also highlight the fact that foldr (:) [] is the identity function on lists (a shallow copy in Lisp parlance), as replacing cons with cons and nil with nil will not change the result.

À propos de ce résultat
Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.
Cours associés (8)
CS-214: Software construction
Learn how to design and implement reliable, maintainable, and efficient software using a mix of programming skills (declarative style, higher-order functions, inductive types, parallelism) and fundam
CS-550: Formal verification
We introduce formal verification as an approach for developing highly reliable systems. Formal verification finds proofs that computer systems work under all relevant scenarios. We will learn how to u
MATH-351: Advanced numerical analysis II
The student will learn state-of-the-art algorithms for solving differential equations. The analysis and implementation of these algorithms will be discussed in some detail.
Afficher plus
Séances de cours associées (47)
Fonctions d'ordre supérieur utilisant des substitutions naïves
Explore les fonctions d'ordre supérieur, les environnements, l'évaluation à l'aide de la substitution et des exemples tels que double factorielle.
Éviter la capture variable
Explore la capture de variables dans les fonctions d'ordre supérieur et l'importance du renommage des variables.
Programmation fonctionnelle en Python
Couvre les concepts de programmation fonctionnelle en Python, montrant des listes de filtrage basées sur des critères spécifiques.
Afficher plus
Publications associées (38)

Results on Sparse Integer Programming and Geometric Independent Sets

Jana Tabea Cslovjecsek

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n.Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed p ...
EPFL2023

Scaling Language Features for Program Verification

Georg Stefan Schmid

Formal verification of real-world software systems remains challenging for a number of reasons, including lack of automation, friction in specifying properties, and limited support for the diverse programming paradigms used in industry. In this thesis we m ...
EPFL2022

Macro Annotations for Scala 3

Zhendong Ang

Macro annotations are an important feature in Scala 2 macro system. Many projects use macro annotations to implement their systems or libraries. Due to the unportability of Scala 2 macro system, Scala 3 redesigns the macro system to make it more reliable a ...
2022
Afficher plus
Concepts associés (16)
Corecursion
In computer science, corecursion is a type of operation that is to recursion. Whereas recursion works analytically, starting on data further from a base case and breaking it down into smaller data and repeating until one reaches a base case, corecursion works synthetically, starting from a base case and building it up, iteratively producing data further removed from a base case. Put simply, corecursive algorithms use the data that they themselves produce, bit by bit, as they become available, and needed, to produce further bits of data.
Clojure
Clojure est un langage de programmation fonctionnelle compilée, multi-plateforme et destiné à la création de programmes sûrs et facilement distribuables. C’est un dialecte de Lisp. Il transpile vers du bytecode Java, du code JavaScript et du bytecode .NET. Clojure est donc disponible sur la JVM, le CLR, les navigateurs et Node.js. vignette|Rich Hickey, créateur de Clojure Rich Hickey est le créateur du langage Clojure. Avant Clojure, il a développé dotLisp, un projet similaire basé sur la plate-forme .
Map (higher-order function)
In many programming languages, map is the name of a higher-order function that applies a given function to each element of a collection, e.g. a list or set, returning the results in a collection of the same type. It is often called apply-to-all when considered in functional form. The concept of a map is not limited to lists: it works for sequential containers, tree-like containers, or even abstract containers such as futures and promises. Suppose we have a list of integers [1, 2, 3, 4, 5] and would like to calculate the square of each integer.
Afficher plus

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.