Efficient Lambda Encodings for Mendler-Style Coinductive Types In
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NICOLAS WU Department of Computer Science, University of Bristol (E-Mail: [email protected], [email protected])
Hinze, R., & Wu, N. (2016). Unifying Structured Recursion Schemes. Journal of Functional Programming, 26, [e1]. https://doi.org/10.1017/S0956796815000258 Peer reviewed version Link to published version (if available): 10.1017/S0956796815000258 Link to publication record in Explore Bristol Research PDF-document University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/red/research-policy/pure/user-guides/ebr-terms/ ZU064-05-FPR URS 15 September 2015 9:20 Under consideration for publication in J. Functional Programming 1 Unifying Structured Recursion Schemes An Extended Study RALF HINZE Department of Computer Science, University of Oxford NICOLAS WU Department of Computer Science, University of Bristol (e-mail: [email protected], [email protected]) Abstract Folds and unfolds have been understood as fundamental building blocks for total programming, and have been extended to form an entire zoo of specialised structured recursion schemes. A great number of these schemes were unified by the introduction of adjoint folds, but more exotic beasts such as recursion schemes from comonads proved to be elusive. In this paper, we show how the two canonical derivations of adjunctions from (co)monads yield recursion schemes of significant computational importance: monadic catamorphisms come from the Kleisli construction, and more astonishingly, the elusive recursion schemes from comonads come from the Eilenberg-Moore construction. Thus we demonstrate that adjoint folds are more unifying than previously believed. 1 Introduction Functional programmers have long realised that the full expressive power of recursion is untamable, and so intensive research has been carried out into the identification of an entire zoo of structured recursion schemes that are well-behaved and more amenable to program comprehension and analysis (Meijer et al., 1991). -
Practical Coinduction
Math. Struct. in Comp. Science: page 1 of 21. c Cambridge University Press 2016 doi:10.1017/S0960129515000493 Practical coinduction DEXTER KOZEN† and ALEXANDRA SILVA‡ †Computer Science, Cornell University, Ithaca, New York 14853-7501, U.S.A. Email: [email protected] ‡Intelligent Systems, Radboud University Nijmegen, Postbus 9010, 6500 GL Nijmegen, the Netherlands Email: [email protected] Received 6 March 2013; revised 17 October 2014 Induction is a well-established proof principle that is taught in most undergraduate programs in mathematics and computer science. In computer science, it is used primarily to reason about inductively defined datatypes such as finite lists, finite trees and the natural numbers. Coinduction is the dual principle that can be used to reason about coinductive datatypes such as infinite streams or trees, but it is not as widespread or as well understood. In this paper, we illustrate through several examples the use of coinduction in informal mathematical arguments. Our aim is to promote the principle as a useful tool for the working mathematician and to bring it to a level of familiarity on par with induction. We show that coinduction is not only about bisimilarity and equality of behaviors, but also applicable to a variety of functions and relations defined on coinductive datatypes. 1. Introduction Perhaps the single most important general proof principle in computer science, and argu- ably in all of mathematics, is induction. There is a valid induction principle corresponding to any well-founded relation, but in computer science, it is most often seen in the form known as structural induction, in which the domain of discourse is an inductively-defined datatype such as finite lists, finite trees, or the natural numbers. -
A Category Theory Explanation for the Systematicity of Recursive Cognitive
Categorial compositionality continued (further): A category theory explanation for the systematicity of recursive cognitive capacities Steven Phillips ([email protected]) Mathematical Neuroinformatics Group, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 JAPAN William H. Wilson ([email protected]) School of Computer Science and Engineering, The University of New South Wales, Sydney, New South Wales, 2052 AUSTRALIA Abstract together afford cognition) whereby cognitive capacity is or- ganized around groups of related abilities. A standard exam- Human cognitive capacity includes recursively definable con- cepts, which are prevalent in domains involving lists, numbers, ple since the original formulation of the problem (Fodor & and languages. Cognitive science currently lacks a satisfactory Pylyshyn, 1988) has been that you don’t find people with the explanation for the systematic nature of recursive cognitive ca- capacity to infer John as the lover from the statement John pacities. The category-theoretic constructs of initial F-algebra, catamorphism, and their duals, final coalgebra and anamor- loves Mary without having the capacity to infer Mary as the phism provide a formal, systematic treatment of recursion in lover from the related statement Mary loves John. An in- computer science. Here, we use this formalism to explain the stance of systematicity is when a cognizer has cognitive ca- systematicity of recursive cognitive capacities without ad hoc assumptions (i.e., why the capacity for some recursive cogni- pacity c1 if and only if the cognizer has cognitive capacity tive abilities implies the capacity for certain others, to the same c2 (see McLaughlin, 2009). So, e.g., systematicity is evident explanatory standard used in our account of systematicity for where one has the capacity to remove the jokers if and only if non-recursive capacities). -
The Method of Coalgebra: Exercises in Coinduction
The Method of Coalgebra: exercises in coinduction Jan Rutten CWI & RU [email protected] Draft d.d. 8 July 2018 (comments are welcome) 2 Draft d.d. 8 July 2018 Contents 1 Introduction 7 1.1 The method of coalgebra . .7 1.2 History, roughly and briefly . .7 1.3 Exercises in coinduction . .8 1.4 Enhanced coinduction: algebra and coalgebra combined . .8 1.5 Universal coalgebra . .8 1.6 How to read this book . .8 1.7 Acknowledgements . .9 2 Categories { where coalgebra comes from 11 2.1 The basic definitions . 11 2.2 Category theory in slogans . 12 2.3 Discussion . 16 3 Algebras and coalgebras 19 3.1 Algebras . 19 3.2 Coalgebras . 21 3.3 Discussion . 23 4 Induction and coinduction 25 4.1 Inductive and coinductive definitions . 25 4.2 Proofs by induction and coinduction . 28 4.3 Discussion . 32 5 The method of coalgebra 33 5.1 Basic types of coalgebras . 34 5.2 Coalgebras, systems, automata ::: ....................... 34 6 Dynamical systems 37 6.1 Homomorphisms of dynamical systems . 38 6.2 On the behaviour of dynamical systems . 41 6.3 Discussion . 44 3 4 Draft d.d. 8 July 2018 7 Stream systems 45 7.1 Homomorphisms and bisimulations of stream systems . 46 7.2 The final system of streams . 52 7.3 Defining streams by coinduction . 54 7.4 Coinduction: the bisimulation proof method . 59 7.5 Moessner's Theorem . 66 7.6 The heart of the matter: circularity . 72 7.7 Discussion . 76 8 Deterministic automata 77 8.1 Basic definitions . 78 8.2 Homomorphisms and bisimulations of automata . -
Friends with Benefits: Implementing Corecursion in Foundational
Friends with Benefits Implementing Corecursion in Foundational Proof Assistants Jasmin Christian Blanchette1;2, Aymeric Bouzy3, Andreas Lochbihler4, Andrei Popescu5;6, and Dmitriy Traytel4 1 Vrije Universiteit Amsterdam, the Netherlands 2 Inria Nancy – Grand Est, Nancy, France 3 Laboratoire d’informatique, École polytechnique, Palaiseau, France 4 Institute of Information Security, Department of Computer Science, ETH Zürich, Switzerland 5 Department of Computer Science, Middlesex University London, UK 6 Institute of Mathematics Simion Stoilow of the Romanian Academy, Bucharest, Romania Abstract. We introduce AmiCo, a tool that extends a proof assistant, Isabelle/ HOL, with flexible function definitions well beyond primitive corecursion. All definitions are certified by the assistant’s inference kernel to guard against in- consistencies. A central notion is that of friends: functions that preserve the pro- ductivity of their arguments and that are allowed in corecursive call contexts. As new friends are registered, corecursion benefits by becoming more expressive. We describe this process and its implementation, from the user’s specification to the synthesis of a higher-order definition to the registration of a friend. We show some substantial case studies where our approach makes a difference. 1 Introduction Codatatypes and corecursion are emerging as a major methodology for programming with infinite objects. Unlike in traditional lazy functional programming, codatatypes support total (co)programming [1, 8, 30, 68], where the defined functions have a simple set-theoretic semantics and productivity is guaranteed. The proof assistants Agda [19], Coq [12], and Matita [7] have been supporting this methodology for years. By contrast, proof assistants based on higher-order logic (HOL), such as HOL4 [64], HOL Light [32], and Isabelle/HOL [56], have traditionally provided only datatypes. -
Abstract Nonsense and Programming: Uses of Category Theory in Computer Science
Bachelor thesis Computing Science Radboud University Abstract Nonsense and Programming: Uses of Category Theory in Computer Science Author: Supervisor: Koen Wösten dr. Sjaak Smetsers [email protected] [email protected] s4787838 Second assessor: prof. dr. Herman Geuvers [email protected] June 29, 2020 Abstract In this paper, we try to explore the various applications category theory has in computer science and see how from this application of category theory numerous concepts in computer science are analogous to basic categorical definitions. We will be looking at three uses in particular: Free theorems, re- cursion schemes and monads to model computational effects. We conclude that the applications of category theory in computer science are versatile and many, and applying category theory to programming is an endeavour worthy of pursuit. Contents Preface 2 Introduction 4 I Basics 6 1 Categories 8 2 Types 15 3 Universal Constructions 22 4 Algebraic Data types 36 5 Function Types 43 6 Functors 52 7 Natural Transformations 60 II Uses 67 8 Free Theorems 69 9 Recursion Schemes 82 10 Monads and Effects 102 11 Conclusions 119 1 Preface The original motivation for embarking on the journey of writing this was to get a better grip on categorical ideas encountered as a student assistant for the course NWI-IBC040 Functional Programming at Radboud University. When another student asks ”What is a monad?” and the only thing I can ex- plain are its properties and some examples, but not its origin and the frame- work from which it comes. Then the eventual answer I give becomes very one-dimensional and unsatisfactory. -
Recursion Patterns As Hylomorphisms
Recursion Patterns as Hylomorphisms Manuel Alcino Cunha [email protected] Techn. Report DI-PURe-03.11.01 2003, November PURe Program Understanding and Re-engineering: Calculi and Applications (Project POSI/ICHS/44304/2002) Departamento de Inform´atica da Universidade do Minho Campus de Gualtar — Braga — Portugal DI-PURe-03.11.01 Recursion Patterns as Hylomorphisms by Manuel Alcino Cunha Abstract In this paper we show how some of the recursion patterns typically used in algebraic programming can be defined using hylomorphisms. Most of these def- initions were previously known. However, unlike previous approaches that use fixpoint induction, we show how to derive the standard laws of each recursion pattern by using just the basic laws of hylomorphisms. We also define the accu- mulation recursion pattern introduced by Pardo using a hylomorphism, and use this definition to derive the strictness conditions that characterize this operator in the presence of partiality. All definitions are implemented and exemplified in Haskell. 1 Introduction The exponential growth in the use of computers in the past decades raised important questions about the correctness of software, specially in safety critical systems. Compared to other areas of engineering, software engineers are still very unfamiliar with the mathematical foundations of computation, and tend to approach programming more as (black) art and less as a science [5]. Ideally, final implementations should be calculated from their specifications, using simple laws that relate programs, in the same way we calculate with mathematical expressions in algebra. The calculational approach is particular appealing in the area of functional programming, since referential transparency ensures that expressions in func- tional programs behave as ordinary expressions in mathematics. -
Some New Approaches in Functional Programming Using Algebras and Coalgebras
Available online at www.sciencedirect.com Electronic Notes in Theoretical Computer Science 279 (3) (2011) 41–62 www.elsevier.com/locate/entcs Some New Approaches in Functional Programming Using Algebras and Coalgebras Viliam Slodiˇc´ak1,2 Pavol Macko3 Department of Computers and Informatics Technical University of Koˇsice Koˇsice, Slovak Republic Abstract In our paper we deal with the expressing of recursion and corecursion in functional programming. We discuss about the morphisms which express the recursion or corecursion, respectively. Here we consider especially the catamorphisms, anamorphisms and their composition called the hylomorphisms. The main essence of this work is to describe a new method of programming the function for calculating the factorial by using hylomorphism. We show that using of hylomorphism is an alternative method for the computation of factorial to recursive methods programmed classically. Our new method we describe in action semantics which is a new formal method for the program description. Keywords: Recursion, duality, hylomorphism, algebra, recursive coalgebras, action semantics. 1 Introduction Recursion is a very useful tool in modern programming languages, in particular when we deal with inductive data structures such as lists, trees, etc. [9]. The theory of recursive functions was developed by Kurt G¨odeland Stephen Kleene in the 1930s. Now the recursion has the great importance in mathematics and in computer science. The recursion method presents very interesting solution of many computational algorithms. It is an inherent part of functional programming. On the other hand, the dual method called corecursion brings the new opportunities in programming. In section 2 we formulate basic notions from the category the- ory, the mathematical tool which importance for theoretical informatics growth in last decade. -
Corecursive Algebras: a Study of General Structured Corecursion (Extended Abstract)
Corecursive Algebras: A Study of General Structured Corecursion (Extended Abstract) Venanzio Capretta1, Tarmo Uustalu2, and Varmo Vene3 1 Institute for Computer and Information Science, Radboud University Nijmegen 2 Institute of Cybernetics, Tallinn University of Technology 3 Department of Computer Science, University of Tartu Abstract. We study general structured corecursion, dualizing the work of Osius, Taylor, and others on general structured recursion. We call an algebra of a functor corecursive if it supports general structured corecur- sion: there is a unique map to it from any coalgebra of the same functor. The concept of antifounded algebra is a statement of the bisimulation principle. We show that it is independent from corecursiveness: Neither condition implies the other. Finally, we call an algebra focusing if its codomain can be reconstructed by iterating structural refinement. This is the strongest condition and implies all the others. 1 Introduction A line of research started by Osius and Taylor studies the categorical foundations of general structured recursion. A recursive coalgebra (RCA) is a coalgebra of a functor F with a unique coalgebra-to-algebra morphism to any F -algebra. In other words, it is an algebra guaranteeing unique solvability of any structured recursive diagram. The notion was introduced by Osius [Osi74] (it was also of interest to Eppendahl [Epp99]; we studied construction of recursive coalgebras from coalgebras known to be recursive with the help of distributive laws of functors over comonads [CUV06]). Taylor introduced the notion of wellfounded coalgebra (WFCA) and proved that, in a Set-like category, it is equivalent to RCA [Tay96a,Tay96b],[Tay99, Ch. -
A Category Theory Primer
A category theory primer Ralf Hinze Computing Laboratory, University of Oxford Wolfson Building, Parks Road, Oxford, OX1 3QD, England [email protected] http://www.comlab.ox.ac.uk/ralf.hinze/ 1 Categories, functors and natural transformations Category theory is a game with objects and arrows between objects. We let C, D etc range over categories. A category is often identified with its class of objects. For instance, we say that Set is the category of sets. In the same spirit, we write A 2 C to express that A is an object of C. We let A, B etc range over objects. However, equally, if not more important are the arrows of a category. So, Set is really the category of sets and total functions. (There is also Rel, the category of sets and relations.) If the objects have additional structure (monoids, groups etc.) then the arrows are typically structure-preserving maps. For every pair of objects A; B 2 C there is a class of arrows from A to B, denoted C(A; B). If C is obvious from the context, we abbreviate f 2 C(A; B) by f : A ! B. We will also loosely speak of A ! B as the type of f . We let f , g etc range over arrows. For every object A 2 C there is an arrow id A 2 C(A; A), called the identity. Two arrows can be composed if their types match: if f 2 C(A; B) and g 2 C(B; C ), then g · f 2 C(A; C ). -
Corecursion in Session-Typed Processes
Corecursion in Session-Typed Processes Bernardo Toninho∗y, Lu´ıs Caires∗ and Frank Pfenningy ∗CITI and FCT - Universidade Nova de Lisboa yCarnegie Mellon University Abstract—Session types are widely accepted as a useful expres- has sparked a renewed interest in session types and their foun- sive discipline for structuring communications in concurrent and dations [5], and in the idea of exploiting logically motivated distributed systems. In order to express infinitely unbounded approaches for providing powerful reasoning techniques about sessions, as required to model the behaviour of realistic dis- tributed systems, session typed languages often introduce general concurrent and distributed systems. This line of work has recursion operators at both the program and the type level. addressed concepts such as value-dependent types [6], proof- Unfortunately, general recursion, in particular when combined carrying code [7] behavioural polymorphism [8], and higher- with name passing and mobility, may easily introduce undesirable order computation [9], approaching a general type theory for divergence, e.g., infinite unobservable reduction sequences. session-based concurrency, with strong guarantees by virtue In this paper we address, by means of typing, the challenge of ensuring non-divergence in a session-typed π-calculus with of typing such as deadlock freedom and session fidelity. general (co)recursion, while still allowing interesting infinite Although in the untyped case infinite behavior is potentially behaviours to be definable, as necessary to model realistic open encodable using replication in the π-calculus, to express process networks and distributed systems. Our approach builds infinitely unbounded session exchanges, as required to model on a Curry-Howard correspondence between our type system the behaviour of realistic distributed systems, session typed and a standard system of linear logic extended with co-inductive types, for which our non-divergence property implies consistency. -
Lambda Jam 2018-05-22 Amy Wong
Introduction to Recursion schemes Lambda Jam 2018-05-22 Amy Wong BRICKX [email protected] Agenda • My background • Problem in recursion • Fix point concept • Recursion patterns, aka morphisms • Using morphisms to solve different recursion problems • References of further reading • Q & A My background • Scala developer • Basic Haskell knowledge • Not familiar with Category Theory • Interested in Functional Programming Recursion is ubiquitous, however, recusive calls are also repeatedly made Example 1 - expression data Expr = Const Int | Add Expr Expr | Mul Expr Expr eval :: Expr -> Int eval (Const x) = x eval (Add e1 e2) = eval e1 + eval e2 eval (Mul e1 e2) = eval e1 * eval e2 Evaluate expression > e = Mul ( Mul (Add (Const 3) (Const 0)) (Add (Const 3) (Const 2)) ) (Const 3) > eval e > 45 Example 2 - factorial factorial :: Int -> Int factorial n | n < 1 = 1 | otherwise = n * factorial (n - 1) > factorial 6 > 720 Example 3 - merge sort mergeSort :: Ord a => [a] -> [a] mergeSort = uncurry merge . splitList where splitList xs | length xs < 2 = (xs, []) | otherwise = join (***) mergeSort . splitAt (length xs `div` 2) $ xs > mergeSort [1,2,3,3,2,1,-10] > [-10,1,1,2,2,3,3] Problem • Recursive call repeatedly made and mix with the application-specific logic • Factoring out the recursive call makes the solution simpler Factor out recursion • Recursion is iteration of nested structures • If we identify abstraction of nested structure • Iteration on abstraction is factored out as pattern • We only need to define non-recursive function for application