Variable-Arity Generic Interfaces
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A Call-By-Need Lambda Calculus
A CallByNeed Lamb da Calculus Zena M Ariola Matthias Fel leisen Computer Information Science Department Department of Computer Science University of Oregon Rice University Eugene Oregon Houston Texas John Maraist and Martin Odersky Philip Wad ler Institut fur Programmstrukturen Department of Computing Science Universitat Karlsruhe UniversityofGlasgow Karlsruhe Germany Glasgow Scotland Abstract arguments value when it is rst evaluated More pre cisely lazy languages only reduce an argument if the The mismatchbetween the op erational semantics of the value of the corresp onding formal parameter is needed lamb da calculus and the actual b ehavior of implemen for the evaluation of the pro cedure b o dy Moreover af tations is a ma jor obstacle for compiler writers They ter reducing the argument the evaluator will remember cannot explain the b ehavior of their evaluator in terms the resulting value for future references to that formal of source level syntax and they cannot easily com parameter This technique of evaluating pro cedure pa pare distinct implementations of dierent lazy strate rameters is called cal lbyneed or lazy evaluation gies In this pap er we derive an equational characteri A simple observation justies callbyneed the re zation of callbyneed and prove it correct with resp ect sult of reducing an expression if any is indistinguish to the original lamb da calculus The theory is a strictly able from the expression itself in all p ossible contexts smaller theory than the lamb da calculus Immediate Some implementations attempt -
Interface Types for Haskell
Interface Types for Haskell Peter Thiemann and Stefan Wehr Institut f¨urInformatik, Universit¨atFreiburg, Germany {thiemann,wehr}@informatik.uni-freiburg.de Abstract. Interface types are a useful concept in object-oriented pro- gramming languages like Java or C#. A clean programming style advo- cates relying on interfaces without revealing their implementation. Haskell’s type classes provide a closely related facility for stating an in- terface separately from its implementation. However, there are situations in which no simple mechanism exists to hide the identity of the imple- mentation type of a type class. This work provides such a mechanism through the integration of lightweight interface types into Haskell. The extension is non-intrusive as no additional syntax is needed and no existing programs are affected. The implementation extends the treat- ment of higher-rank polymorphism in production Haskell compilers. 1 Introduction Interfaces in object-oriented programming languages and type classes in Haskell are closely related: both define the types of certain operations without revealing their implementations. In Java, the name of an interface also acts as an interface type, whereas the name of a type class can only be used to constrain types. Interface types are a proven tool for ensuring data abstraction and information hiding. In many cases, Haskell type classes can serve the same purpose, but there are situations for which the solutions available in Haskell have severe drawbacks. Interface types provide a simple and elegant solution in these situations. A modest extension to Haskell provides the simplicity and elegance of interface types: simply allow programmers to use the name of a type class as a first- class type. -
Metaclasses: Generative C++
Metaclasses: Generative C++ Document Number: P0707 R3 Date: 2018-02-11 Reply-to: Herb Sutter ([email protected]) Audience: SG7, EWG Contents 1 Overview .............................................................................................................................................................2 2 Language: Metaclasses .......................................................................................................................................7 3 Library: Example metaclasses .......................................................................................................................... 18 4 Applying metaclasses: Qt moc and C++/WinRT .............................................................................................. 35 5 Alternatives for sourcedefinition transform syntax .................................................................................... 41 6 Alternatives for applying the transform .......................................................................................................... 43 7 FAQs ................................................................................................................................................................. 46 8 Revision history ............................................................................................................................................... 51 Major changes in R3: Switched to function-style declaration syntax per SG7 direction in Albuquerque (old: $class M new: constexpr void M(meta::type target, -
Chapter 8. Deploying an Osgi Service
Chapter 8. Deploying an OSGi Service The OSGi core framework defines the OSGi Service Layer, which provides a simple mechanism for bundles to interact by registering Java objects as services in the OSGi service registry. One of the strengths of the OSGi service model is that any Java object can be offered as a service: there are no particular constraints, inheritance rules, or annotations that must be applied to the service class. This chapter describes how to deploy an OSGi service using the OSGi blueprint container. The Blueprint Container ........................................................................................................... 92 Blueprint Configuration ................................................................................................... 93 Defining a Service Bean .................................................................................................. 95 Exporting a Service ........................................................................................................ 98 Importing a Service ...................................................................................................... 104 Publishing an OSGi Service .................................................................................................... 113 Accessing an OSGi Service ..................................................................................................... 118 FUSE ESB Deploying into the OSGi Container Version 4.2 91 Chapter 8. Deploying an OSGi Service The Blueprint Container Blueprint Configuration -
Mixin-Based Programming in C++1
Mixin-Based Programming in C++1 Yannis Smaragdakis Don Batory College of Computing Department of Computer Sciences Georgia Institute of Technology The University of Texas at Austin Atlanta, GA 30332 Austin, Texas 78712 [email protected] [email protected] Abstract. Combinations of C++ features, like inheritance, templates, and class nesting, allow for the expression of powerful component patterns. In particular, research has demonstrated that, using C++ mixin classes, one can express lay- ered component-based designs concisely with efficient implementations. In this paper, we discuss pragmatic issues related to component-based programming using C++ mixins. We explain surprising interactions of C++ features and poli- cies that sometimes complicate mixin implementations, while other times enable additional functionality without extra effort. 1 Introduction Large software artifacts are arguably among the most complex products of human intellect. The complexity of software has led to implementation methodologies that divide a problem into manageable parts and compose the parts to form the final prod- uct. Several research efforts have argued that C++ templates (a powerful parameteriza- tion mechanism) can be used to perform this division elegantly. In particular, the work of VanHilst and Notkin [29][30][31] showed how one can implement collaboration-based (or role-based) designs using a certain templatized class pattern, known as a mixin class (or just mixin). Compared to other techniques (e.g., a straightforward use of application frameworks [17]) the VanHilst and Notkin method yields less redundancy and reusable components that reflect the structure of the design. At the same time, unnecessary dynamic binding can be eliminated, result- ing into more efficient implementations. -
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 . -
Interface Evolution Via Virtual Extension Methods Brian Goetz Fourth Draft, June 2011
Interface evolution via virtual extension methods Brian Goetz Fourth draft, June 2011 1. Problem statement Once published, it is impossible to add methods to an interface without breaking existing implementations. (Specifically, adding a method to an interface is not a source- compatible change.) The longer the time since a library has been published, the more likely it is that this restriction will cause grief for its maintainers. The addition of closures to the Java language in JDK 7 place additional stress on the aging Collection interfaces; one of the most significant benefits of closures is that it enables the development of more powerful libraries. It would be disappointing to add a language feature that enables better libraries while at the same time not extending the core libraries to take advantage of that feature1. V1 of the Lambda Strawman proposed C#-style static extension methods as a means of creating the illusion of adding methods to existing classes and interfaces, but they have significant limitations – for example, they cannot be overridden by classes that implement the interface being extended, so implementations are stuck with the “one size fits all” implementation provided as an extension2, and they are not reflectively discoverable. 2. Virtual extension methods3 In this document, we outline a mechanism for adding new methods to existing interfaces, which we call virtual extension methods. Existing interfaces can be augmented without compromising backward compatibility4 by adding extension methods to the interface, whose declaration would contain instructions for finding the default implementation in the event that implementers do not provide a method body. -
Dynamic Interfaces
Dynamic Interfaces Vasco T. Vasconcelos Simon J. Gay Antonio´ Ravara Departamento de Informatica´ Department of Computing Science SQIG at Instituto de Telecomunicac¸oes˜ Faculdade de Cienciasˆ da University of Glasgow, UK Department of Mathematics, IST, Universidade de Lisboa, Portugal [email protected] Technical University of Lisbon, Portugal [email protected] [email protected] Nils Gesbert Alexandre Z. Caldeira Department of Computing Science Departamento de Informatica´ University of Glasgow, UK Faculdade de Cienciasˆ da [email protected] Universidade de Lisboa, Portugal [email protected] Abstract 1. Introduction We define a small class-based object-oriented language in which Standard class-based object-oriented languages present the pro- the availability of methods depends on an object’s abstract state: grammer with the following view: an object is declared to belong to objects’ interfaces are dynamic. Each class has a session type which a certain type, and the type defines various methods; it is therefore provides a global specification of the availability of methods in possible at any time to call any of the methods described in the type. each state. A key feature is that the abstract state of an object However, there are often semantic reasons why it is not appropriate may depend on the result of a method whose return type is an to call a particular method when the object is in a particular inter- enumeration. Static typing guarantees that methods are only called nal state. For example: with a stack, one should not attempt to pop when they are available. -
NU-Prolog Reference Manual
NU-Prolog Reference Manual Version 1.5.24 edited by James A. Thom & Justin Zobel Technical Report 86/10 Machine Intelligence Project Department of Computer Science University of Melbourne (Revised November 1990) Copyright 1986, 1987, 1988, Machine Intelligence Project, The University of Melbourne. All rights reserved. The Technical Report edition of this publication is given away free subject to the condition that it shall not, by the way of trade or otherwise, be lent, resold, hired out, or otherwise circulated, without the prior consent of the Machine Intelligence Project at the University of Melbourne, in any form or cover other than that in which it is published and without a similar condition including this condition being imposed on the subsequent user. The Machine Intelligence Project makes no representations or warranties with respect to the contents of this document and specifically disclaims any implied warranties of merchantability or fitness for any particular purpose. Furthermore, the Machine Intelligence Project reserves the right to revise this document and to make changes from time to time in its content without being obligated to notify any person or body of such revisions or changes. The usual codicil that no part of this publication may be reproduced, stored in a retrieval system, used for wrapping fish, or transmitted, in any form or by any means, electronic, mechanical, photocopying, paper dart, recording, or otherwise, without someone's express permission, is not imposed. Enquiries relating to the acquisition of NU-Prolog should be made to NU-Prolog Distribution Manager Machine Intelligence Project Department of Computer Science The University of Melbourne Parkville, Victoria 3052 Australia Telephone: (03) 344 5229. -
Java Application Programming Interface (API) Java Application Programming Interface (API) Is a List of All Classes That Are Part of the Java Development Kit (JDK)
Java Application Programming Interface (API) Java application programming interface (API) is a list of all classes that are part of the Java development kit (JDK). It includes all Java packages, classes, and interfaces, along with their methods, fields, and constructors. These prewritten classes provide a tremendous amount of functionality to a programmer. A programmer should be aware of these classes and should know how to use them. A complete listing of all classes in Java API can be found at Oracle’s website: http://docs.oracle.com/javase/7/docs/api/. Please visit the above site and bookmark it for future reference. Please consult this site often, especially when you are using a new class and would like to know more about its methods and fields. If you browse through the list of packages in the API, you will observe that there are packages written for GUI programming, networking programming, managing input and output, database programming, and many more. Please browse the complete list of packages and their descriptions to see how they can be used. In order to use a class from Java API, one needs to include an import statement at the start of the program. For example, in order to use the Scanner class, which allows a program to accept input from the keyboard, one must include the following import statement: import java.util.Scanner; The above import statement allows the programmer to use any method listed in the Scanner class. Another choice for including the import statement is the wildcard option shown below: import java.util.*; This version of the import statement imports all the classes in the API’s java.util package and makes them available to the programmer. -
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 . -
Small Hitting-Sets for Tiny Arithmetic Circuits Or: How to Turn Bad Designs Into Good
Electronic Colloquium on Computational Complexity, Report No. 35 (2017) Small hitting-sets for tiny arithmetic circuits or: How to turn bad designs into good Manindra Agrawal ∗ Michael Forbes† Sumanta Ghosh ‡ Nitin Saxena § Abstract Research in the last decade has shown that to prove lower bounds or to derandomize polynomial identity testing (PIT) for general arithmetic circuits it suffices to solve these questions for restricted circuits. In this work, we study the smallest possibly restricted class of circuits, in particular depth-4 circuits, which would yield such results for general circuits (that is, the complexity class VP). We show that if we can design poly(s)-time hitting-sets for Σ ∧a ΣΠO(log s) circuits of size s, where a = ω(1) is arbitrarily small and the number of variables, or arity n, is O(log s), then we can derandomize blackbox PIT for general circuits in quasipolynomial time. Further, this establishes that either E6⊆#P/poly or that VP6=VNP. We call the former model tiny diagonal depth-4. Note that these are merely polynomials with arity O(log s) and degree ω(log s). In fact, we show that one only needs a poly(s)-time hitting-set against individual-degree a′ = ω(1) polynomials that are computable by a size-s arity-(log s) ΣΠΣ circuit (note: Π fanin may be s). Alternatively, we claim that, to understand VP one only needs to find hitting-sets, for depth-3, that have a small parameterized complexity. Another tiny family of interest is when we restrict the arity n = ω(1) to be arbitrarily small.