Polymorphic Type Inference and Abstract Data Types
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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. -
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. -
Encapsulation and Data Abstraction
Data abstraction l Data abstraction is the main organizing principle for building complex software systems l Without data abstraction, computing technology would stop dead in its tracks l We will study what data abstraction is and how it is supported by the programming language l The first step toward data abstraction is called encapsulation l Data abstraction is supported by language concepts such as higher-order programming, static scoping, and explicit state Encapsulation l The first step toward data abstraction, which is the basic organizing principle for large programs, is encapsulation l Assume your television set is not enclosed in a box l All the interior circuitry is exposed to the outside l It’s lighter and takes up less space, so it’s good, right? NO! l It’s dangerous for you: if you touch the circuitry, you can get an electric shock l It’s bad for the television set: if you spill a cup of coffee inside it, you can provoke a short-circuit l If you like electronics, you may be tempted to tweak the insides, to “improve” the television’s performance l So it can be a good idea to put the television in an enclosing box l A box that protects the television against damage and that only authorizes proper interaction (on/off, channel selection, volume) Encapsulation in a program l Assume your program uses a stack with the following implementation: fun {NewStack} nil end fun {Push S X} X|S end fun {Pop S X} X=S.1 S.2 end fun {IsEmpty S} S==nil end l This implementation is not encapsulated! l It has the same problems as a television set -
9. Abstract Data Types
COMPUTER SCIENCE COMPUTER SCIENCE SEDGEWICK/WAYNE SEDGEWICK/WAYNE 9. Abstract Data Types •Overview 9. Abstract Data Types •Color •Image processing •String processing Section 3.1 http://introcs.cs.princeton.edu http://introcs.cs.princeton.edu Abstract data types Object-oriented programming (OOP) A data type is a set of values and a set of operations on those values. Object-oriented programming (OOP). • Create your own data types (sets of values and ops on them). An object holds a data type value. Primitive types • Use them in your programs (manipulate objects). Variable names refer to objects. • values immediately map to machine representations data type set of values examples of operations • operations immediately map to Color three 8-bit integers get red component, brighten machine instructions. Picture 2D array of colors get/set color of pixel (i, j) String sequence of characters length, substring, compare We want to write programs that process other types of data. • Colors, pictures, strings, An abstract data type is a data type whose representation is hidden from the user. • Complex numbers, vectors, matrices, • ... Impact: We can use ADTs without knowing implementation details. • This lecture: how to write client programs for several useful ADTs • Next lecture: how to implement your own ADTs An abstract data type is a data type whose representation is hidden from the user. 3 4 Sound Strings We have already been using ADTs! We have already been using ADTs! A String is a sequence of Unicode characters. defined in terms of its ADT values (typical) Java's String ADT allows us to write Java programs that manipulate strings. -
Abstract Data Types
Chapter 2 Abstract Data Types The second idea at the core of computer science, along with algorithms, is data. In a modern computer, data consists fundamentally of binary bits, but meaningful data is organized into primitive data types such as integer, real, and boolean and into more complex data structures such as arrays and binary trees. These data types and data structures always come along with associated operations that can be done on the data. For example, the 32-bit int data type is defined both by the fact that a value of type int consists of 32 binary bits but also by the fact that two int values can be added, subtracted, multiplied, compared, and so on. An array is defined both by the fact that it is a sequence of data items of the same basic type, but also by the fact that it is possible to directly access each of the positions in the list based on its numerical index. So the idea of a data type includes a specification of the possible values of that type together with the operations that can be performed on those values. An algorithm is an abstract idea, and a program is an implementation of an algorithm. Similarly, it is useful to be able to work with the abstract idea behind a data type or data structure, without getting bogged down in the implementation details. The abstraction in this case is called an \abstract data type." An abstract data type specifies the values of the type, but not how those values are represented as collections of bits, and it specifies operations on those values in terms of their inputs, outputs, and effects rather than as particular algorithms or program code. -
Abstract Data Types (Adts)
Data abstraction: Abstract Data Types (ADTs) CSE 331 University of Washington Michael Ernst Outline 1. What is an abstract data type (ADT)? 2. How to specify an ADT – immutable – mutable 3. The ADT design methodology Procedural and data abstraction Recall procedural abstraction Abstracts from the details of procedures A specification mechanism Reasoning connects implementation to specification Data abstraction (Abstract Data Type, or ADT): Abstracts from the details of data representation A specification mechanism + a way of thinking about programs and designs Next lecture: ADT implementations Representation invariants (RI), abstraction functions (AF) Why we need Abstract Data Types Organizing and manipulating data is pervasive Inventing and describing algorithms is rare Start your design by designing data structures Write code to access and manipulate data Potential problems with choosing a data structure: Decisions about data structures are made too early Duplication of effort in creating derived data Very hard to change key data structures An ADT is a set of operations ADT abstracts from the organization to meaning of data ADT abstracts from structure to use Representation does not matter; this choice is irrelevant: class RightTriangle { class RightTriangle { float base, altitude; float base, hypot, angle; } } Instead, think of a type as a set of operations create, getBase, getAltitude, getBottomAngle, ... Force clients (users) to call operations to access data Are these classes the same or different? class Point { class Point { public float x; public float r; public float y; public float theta; }} Different: can't replace one with the other Same: both classes implement the concept "2-d point" Goal of ADT methodology is to express the sameness Clients depend only on the concept "2-d point" Good because: Delay decisions Fix bugs Change algorithms (e.g., performance optimizations) Concept of 2-d point, as an ADT class Point { // A 2-d point exists somewhere in the plane, .. -
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. -
Csci 658-01: Software Language Engineering Python 3 Reflexive
CSci 658-01: Software Language Engineering Python 3 Reflexive Metaprogramming Chapter 3 H. Conrad Cunningham 4 May 2018 Contents 3 Decorators and Metaclasses 2 3.1 Basic Function-Level Debugging . .2 3.1.1 Motivating example . .2 3.1.2 Abstraction Principle, staying DRY . .3 3.1.3 Function decorators . .3 3.1.4 Constructing a debug decorator . .4 3.1.5 Using the debug decorator . .6 3.1.6 Case study review . .7 3.1.7 Variations . .7 3.1.7.1 Logging . .7 3.1.7.2 Optional disable . .8 3.2 Extended Function-Level Debugging . .8 3.2.1 Motivating example . .8 3.2.2 Decorators with arguments . .9 3.2.3 Prefix decorator . .9 3.2.4 Reformulated prefix decorator . 10 3.3 Class-Level Debugging . 12 3.3.1 Motivating example . 12 3.3.2 Class-level debugger . 12 3.3.3 Variation: Attribute access debugging . 14 3.4 Class Hierarchy Debugging . 16 3.4.1 Motivating example . 16 3.4.2 Review of objects and types . 17 3.4.3 Class definition process . 18 3.4.4 Changing the metaclass . 20 3.4.5 Debugging using a metaclass . 21 3.4.6 Why metaclasses? . 22 3.5 Chapter Summary . 23 1 3.6 Exercises . 23 3.7 Acknowledgements . 23 3.8 References . 24 3.9 Terms and Concepts . 24 Copyright (C) 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 (662) 915-5358 Note: This chapter adapts David Beazley’s debugly example presentation from his Python 3 Metaprogramming tutorial at PyCon’2013 [Beazley 2013a]. -
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 -
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