Variant Parametric Types: a Flexible Subtyping Scheme for Generics
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1=Haskell =1=Making Our Own Types and Typeclasses
Haskell Making Our Own Types and Typeclasses http://igm.univ-mlv.fr/~vialette/?section=teaching St´ephaneVialette LIGM, Universit´eParis-Est Marne-la-Vall´ee November 13, 2016 Making Our Own Types and Typeclasses Algebraic data types intro So far, we've run into a lot of data types: Bool, Int, Char, Maybe, etc. But how do we make our own? One way is to use the data keyword to define a type. Let's see how the Bool type is defined in the standard library. data Bool= False| True data means that we're defining a new data type. Making Our Own Types and Typeclasses Algebraic data types intro data Bool= False| True The part before the = denotes the type, which is Bool. The parts after the = are value constructors. They specify the different values that this type can have. The | is read as or. So we can read this as: the Bool type can have a value of True or False. Both the type name and the value constructors have to be capital cased. Making Our Own Types and Typeclasses Algebraic data types intro We can think of the Int type as being defined like this: data Int=-2147483648|-2147483647| ...|-1|0|1|2| ...| 2147483647 The first and last value constructors are the minimum and maximum possible values of Int. It's not actually defined like this, the ellipses are here because we omitted a heapload of numbers, so this is just for illustrative purposes. Shape let's think about how we would represent a shape in Haskell. -
An Extended Theory of Primitive Objects: First Order System Luigi Liquori
An extended Theory of Primitive Objects: First order system Luigi Liquori To cite this version: Luigi Liquori. An extended Theory of Primitive Objects: First order system. ECOOP, Jun 1997, Jyvaskyla, Finland. pp.146-169, 10.1007/BFb0053378. hal-01154568 HAL Id: hal-01154568 https://hal.inria.fr/hal-01154568 Submitted on 22 May 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. An Extended Theory of Primitive Objects: First Order System Luigi Liquori ? Dip. Informatica, Universit`adi Torino, C.so Svizzera 185, I-10149 Torino, Italy e-mail: [email protected] Abstract. We investigate a first-order extension of the Theory of Prim- itive Objects of [5] that supports method extension in presence of object subsumption. Extension is the ability of modifying the behavior of an ob- ject by adding new methods (and inheriting the existing ones). Object subsumption allows to use objects with a bigger interface in a context expecting another object with a smaller interface. This extended calcu- lus has a sound type system which allows static detection of run-time errors such as message-not-understood, \width" subtyping and a typed equational theory on objects. -
A Polymorphic Type System for Extensible Records and Variants
A Polymorphic Typ e System for Extensible Records and Variants Benedict R. Gaster and Mark P. Jones Technical rep ort NOTTCS-TR-96-3, November 1996 Department of Computer Science, University of Nottingham, University Park, Nottingham NG7 2RD, England. fbrg,[email protected] Abstract b oard, and another indicating a mouse click at a par- ticular p oint on the screen: Records and variants provide exible ways to construct Event = Char + Point : datatyp es, but the restrictions imp osed by practical typ e systems can prevent them from b eing used in ex- These de nitions are adequate, but they are not par- ible ways. These limitations are often the result of con- ticularly easy to work with in practice. For example, it cerns ab out eciency or typ e inference, or of the di- is easy to confuse datatyp e comp onents when they are culty in providing accurate typ es for key op erations. accessed by their p osition within a pro duct or sum, and This pap er describ es a new typ e system that reme- programs written in this way can b e hard to maintain. dies these problems: it supp orts extensible records and To avoid these problems, many programming lan- variants, with a full complement of p olymorphic op era- guages allow the comp onents of pro ducts, and the al- tions on each; and it o ers an e ective type inference al- ternatives of sums, to b e identi ed using names drawn gorithm and a simple compilation metho d. -
On Model Subtyping Cl´Ement Guy, Benoit Combemale, Steven Derrien, James Steel, Jean-Marc J´Ez´Equel
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by HAL-Rennes 1 On Model Subtyping Cl´ement Guy, Benoit Combemale, Steven Derrien, James Steel, Jean-Marc J´ez´equel To cite this version: Cl´ement Guy, Benoit Combemale, Steven Derrien, James Steel, Jean-Marc J´ez´equel.On Model Subtyping. ECMFA - 8th European Conference on Modelling Foundations and Applications, Jul 2012, Kgs. Lyngby, Denmark. 2012. <hal-00695034> HAL Id: hal-00695034 https://hal.inria.fr/hal-00695034 Submitted on 7 May 2012 HAL is a multi-disciplinary open access L'archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destin´eeau d´ep^otet `ala diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publi´esou non, lished or not. The documents may come from ´emanant des ´etablissements d'enseignement et de teaching and research institutions in France or recherche fran¸caisou ´etrangers,des laboratoires abroad, or from public or private research centers. publics ou priv´es. On Model Subtyping Clément Guy1, Benoit Combemale1, Steven Derrien1, Jim R. H. Steel2, and Jean-Marc Jézéquel1 1 University of Rennes1, IRISA/INRIA, France 2 University of Queensland, Australia Abstract. Various approaches have recently been proposed to ease the manipu- lation of models for specific purposes (e.g., automatic model adaptation or reuse of model transformations). Such approaches raise the need for a unified theory that would ease their combination, but would also outline the scope of what can be expected in terms of engineering to put model manipulation into action. -
Design and Implementation of Generics for the .NET Common Language Runtime
Design and Implementation of Generics for the .NET Common Language Runtime Andrew Kennedy Don Syme Microsoft Research, Cambridge, U.K. fakeÒÒ¸d×ÝÑeg@ÑicÖÓ×ÓfغcÓÑ Abstract cally through an interface definition language, or IDL) that is nec- essary for language interoperation. The Microsoft .NET Common Language Runtime provides a This paper describes the design and implementation of support shared type system, intermediate language and dynamic execution for parametric polymorphism in the CLR. In its initial release, the environment for the implementation and inter-operation of multiple CLR has no support for polymorphism, an omission shared by the source languages. In this paper we extend it with direct support for JVM. Of course, it is always possible to “compile away” polymor- parametric polymorphism (also known as generics), describing the phism by translation, as has been demonstrated in a number of ex- design through examples written in an extended version of the C# tensions to Java [14, 4, 6, 13, 2, 16] that require no change to the programming language, and explaining aspects of implementation JVM, and in compilers for polymorphic languages that target the by reference to a prototype extension to the runtime. JVM or CLR (MLj [3], Haskell, Eiffel, Mercury). However, such Our design is very expressive, supporting parameterized types, systems inevitably suffer drawbacks of some kind, whether through polymorphic static, instance and virtual methods, “F-bounded” source language restrictions (disallowing primitive type instanti- type parameters, instantiation at pointer and value types, polymor- ations to enable a simple erasure-based translation, as in GJ and phic recursion, and exact run-time types. -
Subtyping Recursive Types
ACM Transactions on Programming Languages and Systems, 15(4), pp. 575-631, 1993. Subtyping Recursive Types Roberto M. Amadio1 Luca Cardelli CNRS-CRIN, Nancy DEC, Systems Research Center Abstract We investigate the interactions of subtyping and recursive types, in a simply typed λ-calculus. The two fundamental questions here are whether two (recursive) types are in the subtype relation, and whether a term has a type. To address the first question, we relate various definitions of type equivalence and subtyping that are induced by a model, an ordering on infinite trees, an algorithm, and a set of type rules. We show soundness and completeness between the rules, the algorithm, and the tree semantics. We also prove soundness and a restricted form of completeness for the model. To address the second question, we show that to every pair of types in the subtype relation we can associate a term whose denotation is the uniquely determined coercion map between the two types. Moreover, we derive an algorithm that, when given a term with implicit coercions, can infer its least type whenever possible. 1This author's work has been supported in part by Digital Equipment Corporation and in part by the Stanford-CNR Collaboration Project. Page 1 Contents 1. Introduction 1.1 Types 1.2 Subtypes 1.3 Equality of Recursive Types 1.4 Subtyping of Recursive Types 1.5 Algorithm outline 1.6 Formal development 2. A Simply Typed λ-calculus with Recursive Types 2.1 Types 2.2 Terms 2.3 Equations 3. Tree Ordering 3.1 Subtyping Non-recursive Types 3.2 Folding and Unfolding 3.3 Tree Expansion 3.4 Finite Approximations 4. -
G22.2110-003 Programming Languages - Fall 2012 Week 14 - Part 1
G22.2110-003 Programming Languages - Fall 2012 Week 14 - Part 1 Thomas Wies New York University Review Last lecture I Exceptions Outline Today: I Generic Programming Sources for today's lecture: I PLP, ch. 8.4 I Programming in Scala, ch. 19, 20.6 Generic programming Subroutines provide a way to abstract over values. Generic programming lets us abstract over types. Examples: I A sorting algorithm has the same structure, regardless of the types being sorted I Stack primitives have the same semantics, regardless of the objects stored on the stack. One common use: I algorithms on containers: updating, iteration, search Language models: I C: macros (textual substitution) or unsafe casts I Ada: generic units and instantiations I C++, Java, C#, Scala: generics (also called templates) I ML: parametric polymorphism, functors Parameterizing software components Construct Parameter(s): array bounds, element type subprogram values (arguments) Ada generic package values, types, packages Ada generic subprogram values, types C++ class template values, types C++ function template values, types Java generic classes Scala generic types (and implicit values) ML function values (including other functions) ML type constructor types ML functor values, types, structures Templates in C++ template <typename T> class Array { public : explicit Array (size_t); // constructor T& operator[] (size_t); // subscript operator ... // other operations private : ... // a size and a pointer to an array }; Array<int> V1(100); // instantiation Array<int> V2; // use default constructor -
Parametric Polymorphism Parametric Polymorphism
Parametric Polymorphism Parametric Polymorphism • is a way to make a language more expressive, while still maintaining full static type-safety (every Haskell expression has a type, and types are all checked at compile-time; programs with type errors will not even compile) • using parametric polymorphism, a function or a data type can be written generically so that it can handle values identically without depending on their type • such functions and data types are called generic functions and generic datatypes Polymorphism in Haskell • Two kinds of polymorphism in Haskell – parametric and ad hoc (coming later!) • Both kinds involve type variables, standing for arbitrary types. • Easy to spot because they start with lower case letters • Usually we just use one letter on its own, e.g. a, b, c • When we use a polymorphic function we will usually do so at a specific type, called an instance. The process is called instantiation. Identity function Consider the identity function: id x = x Prelude> :t id id :: a -> a It does not do anything with the input other than returning it, therefore it places no constraints on the input's type. Prelude> :t id id :: a -> a Prelude> id 3 3 Prelude> id "hello" "hello" Prelude> id 'c' 'c' Polymorphic datatypes • The identity function is the simplest possible polymorphic function but not very interesting • Most useful polymorphic functions involve polymorphic types • Notation – write the name(s) of the type variable(s) used to the left of the = symbol Maybe data Maybe a = Nothing | Just a • a is the type variable • When we instantiate a to something, e.g. -
CSE 307: Principles of Programming Languages Classes and Inheritance
OOP Introduction Type & Subtype Inheritance Overloading and Overriding CSE 307: Principles of Programming Languages Classes and Inheritance R. Sekar 1 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Topics 1. OOP Introduction 3. Inheritance 2. Type & Subtype 4. Overloading and Overriding 2 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Section 1 OOP Introduction 3 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding OOP (Object Oriented Programming) So far the languages that we encountered treat data and computation separately. In OOP, the data and computation are combined into an “object”. 4 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Benefits of OOP more convenient: collects related information together, rather than distributing it. Example: C++ iostream class collects all I/O related operations together into one central place. Contrast with C I/O library, which consists of many distinct functions such as getchar, printf, scanf, sscanf, etc. centralizes and regulates access to data. If there is an error that corrupts object data, we need to look for the error only within its class Contrast with C programs, where access/modification code is distributed throughout the program 5 / 52 OOP Introduction Type & Subtype Inheritance Overloading and Overriding Benefits of OOP (Continued) Promotes reuse. by separating interface from implementation. We can replace the implementation of an object without changing client code. Contrast with C, where the implementation of a data structure such as a linked list is integrated into the client code by permitting extension of new objects via inheritance. Inheritance allows a new class to reuse the features of an existing class. -
Java Secrets.Pdf
Java Secrets by Elliotte Rusty Harold IDG Books, IDG Books Worldwide, Inc. ISBN: 0764580078 Pub Date: 05/01/97 Buy It Preface About the Author Part I—How Java Works Chapter 1—Introducing Java SECRETS A Little Knowledge Can Be a Dangerous Thing What’s in This Book? Part I: How Java Works Part II: The sun Classes Part III: Platform-Dependent Java Why Java Secrets? Broader applicability More power Inspiration Where Did the Secrets Come From? Where is the documentation? The source code The API documentation What Versions of Java Are Covered? Some Objections Java is supposed to be platform independent Why aren’t these things documented? FUD (fear, uncertainty, and doubt) How secret is this, anyway? Summary Chapter 2—Primitive Data Types Bytes in Memory Variables, Values, and Identifiers Place-Value Number Systems Binary notation Hexadecimal notation Octal notation Integers ints Long, short, and byte Floating-Point Numbers Representing floating-point numbers in binary code Special values Denormalized floating-point numbers CHAR ASCII ISO Latin-1 Unicode UTF8 Boolean Cross-Platform Issues Byte order Unsigned integers Integer widths Conversions and Casting Using a cast The mechanics of conversion Bit-Level Operators Some terminology Bitwise operators Bit shift operators Summary Chapter 2—Primitive Data Types Bytes in Memory Variables, Values, and Identifiers Place-Value Number Systems Binary notation Hexadecimal notation Octal notation Integers ints Long, short, and byte Floating-Point Numbers Representing floating-point numbers in binary code -
Advanced-Java.Pdf
Advanced java i Advanced java Advanced java ii Contents 1 How to create and destroy objects 1 1.1 Introduction......................................................1 1.2 Instance Construction.................................................1 1.2.1 Implicit (Generated) Constructor.......................................1 1.2.2 Constructors without Arguments.......................................1 1.2.3 Constructors with Arguments........................................2 1.2.4 Initialization Blocks.............................................2 1.2.5 Construction guarantee............................................3 1.2.6 Visibility...................................................4 1.2.7 Garbage collection..............................................4 1.2.8 Finalizers...................................................5 1.3 Static initialization..................................................5 1.4 Construction Patterns.................................................5 1.4.1 Singleton...................................................6 1.4.2 Utility/Helper Class.............................................7 1.4.3 Factory....................................................7 1.4.4 Dependency Injection............................................8 1.5 Download the Source Code..............................................9 1.6 What’s next......................................................9 2 Using methods common to all objects 10 2.1 Introduction...................................................... 10 2.2 Methods equals and hashCode........................................... -
INF 102 CONCEPTS of PROG. LANGS Type Systems
INF 102 CONCEPTS OF PROG. LANGS Type Systems Instructors: James Jones Copyright © Instructors. What is a Data Type? • A type is a collection of computational entities that share some common property • Programming languages are designed to help programmers organize computational constructs and use them correctly. Many programming languages organize data and computations into collections called types. • Some examples of types are: o the type Int of integers o the type (Int→Int) of functions from integers to integers Why do we need them? • Consider “untyped” universes: • Bit string in computer memory • λ-expressions in λ calculus • Sets in set theory • “untyped” = there’s only 1 type • Types arise naturally to categorize objects according to patterns of use • E.g. all integer numbers have same set of applicable operations Use of Types • Identifying and preventing meaningless errors in the program o Compile-time checking o Run-time checking • Program Organization and documentation o Separate types for separate concepts o Indicates intended use declared identifiers • Supports Optimization o Short integers require fewer bits o Access record component by known offset Type Errors • A type error occurs when a computational entity, such as a function or a data value, is used in a manner that is inconsistent with the concept it represents • Languages represent values as sequences of bits. A "type error" occurs when a bit sequence written for one type is used as a bit sequence for another type • A simple example can be assigning a string to an integer