Concepts: Linguistic Support for Generic Programming in C++
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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. -
The Pros of Cons: Programming with Pairs and Lists
The Pros of cons: Programming with Pairs and Lists CS251 Programming Languages Spring 2016, Lyn Turbak Department of Computer Science Wellesley College Racket Values • booleans: #t, #f • numbers: – integers: 42, 0, -273 – raonals: 2/3, -251/17 – floang point (including scien3fic notaon): 98.6, -6.125, 3.141592653589793, 6.023e23 – complex: 3+2i, 17-23i, 4.5-1.4142i Note: some are exact, the rest are inexact. See docs. • strings: "cat", "CS251", "αβγ", "To be\nor not\nto be" • characters: #\a, #\A, #\5, #\space, #\tab, #\newline • anonymous func3ons: (lambda (a b) (+ a (* b c))) What about compound data? 5-2 cons Glues Two Values into a Pair A new kind of value: • pairs (a.k.a. cons cells): (cons v1 v2) e.g., In Racket, - (cons 17 42) type Command-\ to get λ char - (cons 3.14159 #t) - (cons "CS251" (λ (x) (* 2 x)) - (cons (cons 3 4.5) (cons #f #\a)) Can glue any number of values into a cons tree! 5-3 Box-and-pointer diagrams for cons trees (cons v1 v2) v1 v2 Conven3on: put “small” values (numbers, booleans, characters) inside a box, and draw a pointers to “large” values (func3ons, strings, pairs) outside a box. (cons (cons 17 (cons "cat" #\a)) (cons #t (λ (x) (* 2 x)))) 17 #t #\a (λ (x) (* 2 x)) "cat" 5-4 Evaluaon Rules for cons Big step seman3cs: e1 ↓ v1 e2 ↓ v2 (cons) (cons e1 e2) ↓ (cons v1 v2) Small-step seman3cs: (cons e1 e2) ⇒* (cons v1 e2); first evaluate e1 to v1 step-by-step ⇒* (cons v1 v2); then evaluate e2 to v2 step-by-step 5-5 cons evaluaon example (cons (cons (+ 1 2) (< 3 4)) (cons (> 5 6) (* 7 8))) ⇒ (cons (cons 3 (< 3 4)) -
The Use of UML for Software Requirements Expression and Management
The Use of UML for Software Requirements Expression and Management Alex Murray Ken Clark Jet Propulsion Laboratory Jet Propulsion Laboratory California Institute of Technology California Institute of Technology Pasadena, CA 91109 Pasadena, CA 91109 818-354-0111 818-393-6258 [email protected] [email protected] Abstract— It is common practice to write English-language 1. INTRODUCTION ”shall” statements to embody detailed software requirements in aerospace software applications. This paper explores the This work is being performed as part of the engineering of use of the UML language as a replacement for the English the flight software for the Laser Ranging Interferometer (LRI) language for this purpose. Among the advantages offered by the of the Gravity Recovery and Climate Experiment (GRACE) Unified Modeling Language (UML) is a high degree of clarity Follow-On (F-O) mission. However, rather than use the real and precision in the expression of domain concepts as well as project’s model to illustrate our approach in this paper, we architecture and design. Can this quality of UML be exploited have developed a separate, ”toy” model for use here, because for the definition of software requirements? this makes it easier to avoid getting bogged down in project details, and instead to focus on the technical approach to While expressing logical behavior, interface characteristics, requirements expression and management that is the subject timeliness constraints, and other constraints on software using UML is commonly done and relatively straight-forward, achiev- of this paper. ing the additional aspects of the expression and management of software requirements that stakeholders expect, especially There is one exception to this choice: we will describe our traceability, is far less so. -
Generic Programming
Generic Programming July 21, 1998 A Dagstuhl Seminar on the topic of Generic Programming was held April 27– May 1, 1998, with forty seven participants from ten countries. During the meeting there were thirty seven lectures, a panel session, and several problem sessions. The outcomes of the meeting include • A collection of abstracts of the lectures, made publicly available via this booklet and a web site at http://www-ca.informatik.uni-tuebingen.de/dagstuhl/gpdag.html. • Plans for a proceedings volume of papers submitted after the seminar that present (possibly extended) discussions of the topics covered in the lectures, problem sessions, and the panel session. • A list of generic programming projects and open problems, which will be maintained publicly on the World Wide Web at http://www-ca.informatik.uni-tuebingen.de/people/musser/gp/pop/index.html http://www.cs.rpi.edu/˜musser/gp/pop/index.html. 1 Contents 1 Motivation 3 2 Standards Panel 4 3 Lectures 4 3.1 Foundations and Methodology Comparisons ........ 4 Fundamentals of Generic Programming.................. 4 Jim Dehnert and Alex Stepanov Automatic Program Specialization by Partial Evaluation........ 4 Robert Gl¨uck Evaluating Generic Programming in Practice............... 6 Mehdi Jazayeri Polytypic Programming........................... 6 Johan Jeuring Recasting Algorithms As Objects: AnAlternativetoIterators . 7 Murali Sitaraman Using Genericity to Improve OO Designs................. 8 Karsten Weihe Inheritance, Genericity, and Class Hierarchies.............. 8 Wolf Zimmermann 3.2 Programming Methodology ................... 9 Hierarchical Iterators and Algorithms................... 9 Matt Austern Generic Programming in C++: Matrix Case Study........... 9 Krzysztof Czarnecki Generative Programming: Beyond Generic Programming........ 10 Ulrich Eisenecker Generic Programming Using Adaptive and Aspect-Oriented Programming . -
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 -
Lecture Slides
Outline Meta-Classes Guy Wiener Introduction AOP Classes Generation 1 Introduction Meta-Classes in Python Logging 2 Meta-Classes in Python Delegation Meta-Classes vs. Traditional OOP 3 Meta-Classes vs. Traditional OOP Outline Meta-Classes Guy Wiener Introduction AOP Classes Generation 1 Introduction Meta-Classes in Python Logging 2 Meta-Classes in Python Delegation Meta-Classes vs. Traditional OOP 3 Meta-Classes vs. Traditional OOP What is Meta-Programming? Meta-Classes Definition Guy Wiener Meta-Program A program that: Introduction AOP Classes One of its inputs is a program Generation (possibly itself) Meta-Classes in Python Its output is a program Logging Delegation Meta-Classes vs. Traditional OOP Meta-Programs Nowadays Meta-Classes Guy Wiener Introduction AOP Classes Generation Compilers Meta-Classes in Python Code Generators Logging Delegation Model-Driven Development Meta-Classes vs. Traditional Templates OOP Syntactic macros (Lisp-like) Meta-Classes The Problem With Static Programming Meta-Classes Guy Wiener Introduction AOP Classes Generation Meta-Classes How to share features between classes and class hierarchies? in Python Logging Share static attributes Delegation Meta-Classes Force classes to adhere to the same protocol vs. Traditional OOP Share code between similar methods Meta-Classes Meta-Classes Guy Wiener Introduction AOP Classes Definition Generation Meta-Classes in Python Meta-Class A class that creates classes Logging Delegation Objects that are instances of the same class Meta-Classes share the same behavior vs. Traditional OOP Classes that are instances of the same meta-class share the same behavior Meta-Classes Meta-Classes Guy Wiener Introduction AOP Classes Definition Generation Meta-Classes in Python Meta-Class A class that creates classes Logging Delegation Objects that are instances of the same class Meta-Classes share the same behavior vs. -
Java for Scientific Computing, Pros and Cons
Journal of Universal Computer Science, vol. 4, no. 1 (1998), 11-15 submitted: 25/9/97, accepted: 1/11/97, appeared: 28/1/98 Springer Pub. Co. Java for Scienti c Computing, Pros and Cons Jurgen Wol v. Gudenb erg Institut fur Informatik, Universitat Wurzburg wol @informatik.uni-wuerzburg.de Abstract: In this article we brie y discuss the advantages and disadvantages of the language Java for scienti c computing. We concentrate on Java's typ e system, investi- gate its supp ort for hierarchical and generic programming and then discuss the features of its oating-p oint arithmetic. Having found the weak p oints of the language we pro- p ose workarounds using Java itself as long as p ossible. 1 Typ e System Java distinguishes b etween primitive and reference typ es. Whereas this distinc- tion seems to b e very natural and helpful { so the primitives which comprise all standard numerical data typ es have the usual value semantics and expression concept, and the reference semantics of the others allows to avoid p ointers at all{ it also causes some problems. For the reference typ es, i.e. arrays, classes and interfaces no op erators are available or may b e de ned and expressions can only b e built by metho d calls. Several variables may simultaneously denote the same ob ject. This is certainly strange in a numerical setting, but not to avoid, since classes have to b e used to intro duce higher data typ es. On the other hand, the simple hierarchy of classes with the ro ot Object clearly b elongs to the advantages of the language. -
A Metaobject Protocol for Fault-Tolerant CORBA Applications
A Metaobject Protocol for Fault-Tolerant CORBA Applications Marc-Olivier Killijian*, Jean-Charles Fabre*, Juan-Carlos Ruiz-Garcia*, Shigeru Chiba** *LAAS-CNRS, 7 Avenue du Colonel Roche **Institute of Information Science and 31077 Toulouse cedex, France Electronics, University of Tsukuba, Tennodai, Tsukuba, Ibaraki 305-8573, Japan Abstract The corner stone of a fault-tolerant reflective The use of metalevel architectures for the architecture is the MOP. We thus propose a special implementation of fault-tolerant systems is today very purpose MOP to address the problems of general-purpose appealing. Nevertheless, all such fault-tolerant systems ones. We show that compile-time reflection is a good have used a general-purpose metaobject protocol (MOP) approach for developing a specialized runtime MOP. or are based on restricted reflective features of some The definition and the implementation of an object-oriented language. According to our past appropriate runtime metaobject protocol for implementing experience, we define in this paper a suitable metaobject fault tolerance into CORBA applications is the main protocol, called FT-MOP for building fault-tolerant contribution of the work reported in this paper. This systems. We explain how to realize a specialized runtime MOP, called FT-MOP (Fault Tolerance - MetaObject MOP using compile-time reflection. This MOP is CORBA Protocol), is sufficiently general to be used for other aims compliant: it enables the execution and the state evolution (mobility, adaptability, migration, security). FT-MOP of CORBA objects to be controlled and enables the fault provides a mean to attach dynamically fault tolerance tolerance metalevel to be developed as CORBA software. strategies to CORBA objects as CORBA metaobjects, enabling thus these strategies to be implemented as 1 . -
Polymorphism
Polymorphism A closer look at types.... Chap 8 polymorphism º comes from Greek meaning ‘many forms’ In programming: Def: A function or operator is polymorphic if it has at least two possible types. Polymorphism i) OverloaDing Def: An overloaDeD function name or operator is one that has at least two Definitions, all of Different types. Example: In Java the ‘+’ operator is overloaDeD. String s = “abc” + “def”; +: String * String ® String int i = 3 + 5; +: int * int ® int Polymorphism Example: Java allows user DefineD polymorphism with overloaDeD function names. bool f (char a, char b) { return a == b; f : char * char ® bool } bool f (int a, int b) { f : int * int ® bool return a == b; } Note: ML Does not allow function overloaDing Polymorphism ii) Parameter Coercion Def: An implicit type conversion is calleD a coercion. Coercions usually exploit the type-subtype relationship because a wiDening type conversion from subtype to supertype is always DeemeD safe ® a compiler can insert these automatically ® type coercions. Example: type coercion in Java Double x; x = 2; the value 2 is coerceD from int to Double by the compiler Polymorphism Parameter coercion is an implicit type conversion on parameters. Parameter coercion makes writing programs easier – one function can be applieD to many subtypes. Example: Java voiD f (Double a) { ... } int Ì double float Ì double short Ì double all legal types that can be passeD to function ‘f’. byte Ì double char Ì double Note: ML Does not perform type coercion (ML has no notion of subtype). Polymorphism iii) Parametric Polymorphism Def: A function exhibits parametric polymorphism if it has a type that contains one or more type variables. -
C/C++ Program Design CS205 Week 10
C/C++ Program Design CS205 Week 10 Prof. Shiqi Yu (于仕琪) <[email protected]> Prof. Feng (郑锋) <[email protected]> Operators for cv::Mat Function overloading More convenient to code as follows Mat add(Mat A, Mat B); Mat A, B; Mat add(Mat A, float b); float a, b; Mat add(float a, Mat B); //… Mat C = A + B; Mat mul(Mat A, Mat B); Mat D = A * B; Mat mul(Mat A, float b); Mat E = a * A; Mat mul(float a, Mat B); ... operators for cv::Mat #include <iostream> #include <opencv2/opencv.hpp> using namespace std; int main() { float a[6]={1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f}; float b[6]={1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}; cv::Mat A(2, 3, CV_32FC1, a); cv::Mat B(3, 2, CV_32FC1, b); cv::Mat C = A * B; cout << "Matrix C = " << endl << C << endl; return 0; } The slides are based on the book <Stephen Prata, C++ Primer Plus, 6th Edition, Addison-Wesley Professional, 2011> Operator Overloading Overloading • Function overloading Ø Let you use multiple functions sharing the same name Ø Relationship to others: üDefault arguments üFunction templates • * operator (An operator overloading example) Ø Applied to an address, yield the value stored at that address Ø Applied two numbers, yield the product of the values Operator Function • Operator function Ø Keyword: operator for C++ Ø To overload an operator, you use a special function Ø Function header has the form: üoperator+() overloads the + operator üoperator*() overloads the * operator üoperator[]() overloads the [] operator Ø The compiler, recognizing the operands as belonging to the class, replaces the