Towards the Integration of Metaprogramming Services Into Java
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Why Untyped Nonground Metaprogramming Is Not (Much Of) a Problem
NORTH- HOLLAND WHY UNTYPED NONGROUND METAPROGRAMMING IS NOT (MUCH OF) A PROBLEM BERN MARTENS* and DANNY DE SCHREYE+ D We study a semantics for untyped, vanilla metaprograms, using the non- ground representation for object level variables. We introduce the notion of language independence, which generalizes range restriction. We show that the vanilla metaprogram associated with a stratified normal oljjctct program is weakly stratified. For language independent, stratified normal object programs, we prove that there is a natural one-to-one correspon- dence between atoms p(tl, . , tr) in the perfect Herbrand model of t,he object program and solve(p(tl, , tT)) atoms in the weakly perfect Her\) and model of the associated vanilla metaprogram. Thus, for this class of programs, the weakly perfect, Herbrand model provides a sensible SC mantics for the metaprogram. We show that this result generalizes to nonlanguage independent programs in the context of an extended Hcr- brand semantics, designed to closely mirror the operational behavior of logic programs. Moreover, we also consider a number of interesting exterl- sions and/or variants of the basic vanilla metainterpreter. For instance. WC demonstrate how our approach provides a sensible semantics for a limit4 form of amalgamation. a “Partly supported by the Belgian National Fund for Scientific Research, partly by ESPRlT BRA COMPULOG II, Contract 6810, and partly by GOA “Non-Standard Applications of Ab- stract Interpretation,” Belgium. TResearch Associate of the Belgian National Fund for Scientific Research Address correspondence to Bern Martens and Danny De Schreye, Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A. B-3001 Hevrrlee Belgium E-mail- {bern, dannyd}@cs.kuleuven.ac.be. -
Practical Reflection and Metaprogramming for Dependent
Practical Reflection and Metaprogramming for Dependent Types David Raymond Christiansen Advisor: Peter Sestoft Submitted: November 2, 2015 i Abstract Embedded domain-specific languages are special-purpose pro- gramming languages that are implemented within existing general- purpose programming languages. Dependent type systems allow strong invariants to be encoded in representations of domain-specific languages, but it can also make it difficult to program in these em- bedded languages. Interpreters and compilers must always take these invariants into account at each stage, and authors of embedded languages must work hard to relieve users of the burden of proving these properties. Idris is a dependently typed functional programming language whose semantics are given by elaboration to a core dependent type theory through a tactic language. This dissertation introduces elabo- rator reflection, in which the core operators of the elaborator are real- ized as a type of computations that are executed during the elab- oration process of Idris itself, along with a rich API for reflection. Elaborator reflection allows domain-specific languages to be imple- mented using the same elaboration technology as Idris itself, and it gives them additional means of interacting with native Idris code. It also allows Idris to be used as its own metalanguage, making it into a programmable programming language and allowing code re-use across all three stages: elaboration, type checking, and execution. Beyond elaborator reflection, other forms of compile-time reflec- tion have proven useful for embedded languages. This dissertation also describes error reflection, in which Idris code can rewrite DSL er- ror messages before presenting domain-specific messages to users, as well as a means for integrating quasiquotation into a tactic-based elaborator so that high-level syntax can be used for low-level reflected terms. -
Jpype Documentation Release 0.7.0
JPype Documentation Release 0.7.0 Steve Menard, Luis Nell and others Jul 22, 2019 Contents 1 Parts of the documentation 3 1.1 Installation................................................3 1.2 User Guide................................................6 1.3 QuickStart Guide............................................. 17 1.4 API Reference.............................................. 27 1.5 JImport.................................................. 34 1.6 Changelog................................................ 36 1.7 Developer Guide............................................. 40 2 Indices and tables 53 Python Module Index 55 Index 57 i ii JPype Documentation, Release 0.7.0 JPype is a Python module to provide full access to Java from within Python. It allows Python to make use of Java only libraries, exploring and visualization of Java structures, development and testing of Java libraries, scientific computing, and much more. By gaining the best of both worlds using Python for rapid prototyping and Java for strong typed production code, JPype provides a powerful environment for engineering and code development. This is achieved not through re-implementing Python, as Jython/JPython has done, but rather through interfacing at the native level in both virtual machines. This shared memory based approach achieves decent computing preformance, while providing the access to the entirety of CPython and Java libraries. Contents 1 JPype Documentation, Release 0.7.0 2 Contents CHAPTER 1 Parts of the documentation 1.1 Installation JPype is available either as a pre-compiled binary for Anaconda, or may be build from source though several methods. 1.1.1 Binary Install JPype can be installed as pre-compiled binary if you are using the Anaconda Python stack. Binaries are available for Linux, OSX, ad windows are available on conda-forge. -
Metaprogramming with Julia
Metaprogramming with Julia https://szufel.pl Programmers effort vs execution speed Octave R Python Matlab time, time, log scale - C JavaScript Java Go Julia C rozmiar kodu Sourcewego w KB Source: http://www.oceanographerschoice.com/2016/03/the-julia-language-is-the-way-of-the-future/ 2 Metaprogramming „Metaprogramming is a programming technique in which computer programs have the ability to treat other programs as their data. It means that a program can be designed to read, generate, analyze or transform other programs, and even modify itself while running.” (source: Wikipedia) julia> code = Meta.parse("x=5") :(x = 5) julia> dump(code) Expr head: Symbol = args: Array{Any}((2,)) 1: Symbol x 2: Int64 5 3 Metaprogramming (cont.) julia> code = Meta.parse("x=5") :(x = 5) julia> dump(code) Expr head: Symbol = args: Array{Any}((2,)) 1: Symbol x 2: Int64 5 julia> eval(code) 5 julia> x 5 4 Julia Compiler system not quite accurate picture... Source: https://www.researchgate.net/ publication/301876510_High- 5 level_GPU_programming_in_Julia Example 1. Select a field from an object function getValueOfA(x) return x.a end function getValueOf(x, name::String) return getproperty(x, Symbol(name)) end function getValueOf2(name::String) field = Symbol(name) code = quote (obj) -> obj.$field end return eval(code) end function getValueOf3(name::String) return eval(Meta.parse("obj -> obj.$name")) end 6 Let’s test using BenchmarkTools struct MyStruct a b end x = MyStruct(5,6) @btime getValueOfA($x) @btime getValueOf($x,"a") const getVal2 = getValueOf2("a") @btime -
Chargeurs De Classes Java (Classloader)
http://membres-liglab.imag.fr/donsez/cours Chargeurs de classes Java (ClassLoader) Didier Donsez Université Joseph Fourier - Grenoble 1 PolyTech’Grenoble - LIG/ADELE [email protected] [email protected] 06/06/2009 Licence Cette présentation est couverte par le contrat Creative Commons By NC ND http://creativecommons.org/licenses/by-nc-nd/2.0/fr/ Didier Donsez, 2002-2009, ClassLoaders Donsez,2002-2009, Didier 2 06/06/2009 Kequoi ca un chargeur de classes ? Son rôle est 1) de charger le bytecode d’une classe depuis un artéfact (archive Java, répertoire distant …) 2) communiquer le bytecode à la machine virtuelle Didier Donsez, 2002-2009, ClassLoaders Donsez,2002-2009, Didier 4 06/06/2009 Pourquoi utiliser les chargeurs de classes Classes non présentes dans le CLASSPATH URLClassLoader, AppletClassLoader, … ex: WEB-INF/classes et WEB-INF/lib d’une WebApp ex: CODEBASE d’une applet, … Déchargement et Mise à jour du bytecode lors de l’exécution de la VM (runtime) Chargeurs de OSGi Modification du ByteCode à la volée au chargement Instrumentation AOP (Aspect Oriented Programming) BCEL, ASM Protection Chargement de ressources associées à la classe properties, images, … Recherche de Service Providers ou de Drivers META-INF/services (java.util.ServiceLoader de 6.0) Didier Donsez, 2002-2009, ClassLoaders Donsez,2002-2009, Didier 5 06/06/2009 Principe de la délégation (Java 2) Tout chargeur a un chargeur parent sauf le chargeur primordial Tout chargeur vérifie si la classe à charger n’a pas déjà été chargée par un chargeur -
How Java Works JIT, Just in Time Compiler Loading .Class Files The
How Java works JIT, Just In Time Compiler ● The java compiler takes a .java file and generates a .class file ● JVM ultimately translates bytecode into native code, each time ➤ The .class file contains Java bytecodes, the assembler the same bytecodes are processed, the translation into native language for Java programs code must be made ➤ Bytecodes are executed in a JVM (java virtual machine), ➤ If we can cache translated code we can avoid re-translating the valid bytecodes are specified by Sun the same bytecode sequence • What if third parties create platform/OS specific codes? ➤ Why not just translate the entire .java program into native code? ● The JVM interprets the bytecodes ➤ JVM is platform/OS specific, must ultimately run the code ● Still need the JVM, the JIT works in conjunction with the JVM, not in place of it ➤ Different JVMs will have different performance, JITs are part of the overall JDK/Java performance ● How are classes loaded into the JVM? Can this be thwarted? Duke CPS 108 14.1 Duke CPS 108 14.2 Loading .class files The ClassLoader ● The bytecode verifier “proves theorems” about the bytecodes ● The “Primordial” loader is built-in to the JVM being loaded into the JVM ➤ Sometimes called the “default” loader, but it’s not ➤ These bytecodes may come from a non-Java source, e.g., extensible or customizable the way other loaders are compile Ada into bytecodes (why?) ➤ Loads classes from the platform on which the JVM runs ● This verification is a static analysis of properties such as: (what are loader and JVM written in?) ➤ -
A Foundation for Trait-Based Metaprogramming
A foundation for trait-based metaprogramming John Reppy Aaron Turon University of Chicago {jhr, adrassi}@cs.uchicago.edu Abstract We present a calculus, based on the Fisher-Reppy polymorphic Scharli¨ et al. introduced traits as reusable units of behavior inde- trait calculus [FR03], with support for trait privacy, hiding and deep pendent of the inheritance hierarchy. Despite their relative simplic- renaming of trait methods, and a more granular trait typing. Our ity, traits offer a surprisingly rich calculus. Trait calculi typically in- calculus is more expressive (it provides new forms of conflict- clude operations for resolving conflicts when composing two traits. resolution) and more flexible (it allows after-the-fact renaming) In the existing work on traits, these operations (method exclusion than the previous work. Traits provide a useful mechanism for shar- and aliasing) are shallow, i.e., they have no effect on the body of the ing code between otherwise unrelated classes. By adding deep re- other methods in the trait. In this paper, we present a new trait sys- naming, our trait calculus supports sharing code between methods. tem, based on the Fisher-Reppy trait calculus, that adds deep oper- For example, the JAVA notion of synchronized methods can im- ations (method hiding and renaming) to support conflict resolution. plemented as a trait in our system and can be applied to multiple The proposed operations are deep in the sense that they preserve methods in the same class to produce synchronized versions. We any existing connections between the affected method and the other term this new use of traits trait-based metaprogramming. -
Metaprogramming in .NET by Kevin Hazzard Jason Bock
S AMPLE CHAPTER in .NET Kevin Hazzard Jason Bock FOREWORD BY Rockford Lhotka MANNING Metaprogramming in .NET by Kevin Hazzard Jason Bock Chapter 1 Copyright 2013 Manning Publications brief contents PART 1DEMYSTIFYING METAPROGRAMMING ..............................1 1 ■ Metaprogramming concepts 3 2 ■ Exploring code and metadata with reflection 41 PART 2TECHNIQUES FOR GENERATING CODE ..........................63 3 ■ The Text Template Transformation Toolkit (T4) 65 4 ■ Generating code with the CodeDOM 101 5 ■ Generating code with Reflection.Emit 139 6 ■ Generating code with expressions 171 7 ■ Generating code with IL rewriting 199 PART 3LANGUAGES AND TOOLS ............................................221 8 ■ The Dynamic Language Runtime 223 9 ■ Languages and tools 267 10 ■ Managing the .NET Compiler 287 v Metaprogramming concepts In this chapter ■ Defining metaprogramming ■ Exploring examples of metaprogramming The basic principles of object-oriented programming (OOP) are understood by most software developers these days. For example, you probably understand how encapsulation and implementation-hiding can increase the cohesion of classes. Languages like C# and Visual Basic are excellent for creating so-called coarsely grained types because they expose simple features for grouping and hiding both code and data. You can use cohesive types to raise the abstraction level across a system, which allows for loose coupling to occur. Systems that enjoy loose cou- pling at the top level are much easier to maintain because each subsystem isn’t as dependent on the others as they could be in a poor design. Those benefits are realized at the lower levels, too, typically through lowered complexity and greater reusability of classes. In figure 1.1, which of the two systems depicted would likely be easier to modify? Without knowing what the gray circles represent, most developers would pick the diagram on the right as the better one. -
A Fast, Verified, Cross-Platform Cryptographic Provider
EverCrypt: A Fast, Verified, Cross-Platform Cryptographic Provider Jonathan Protzenko∗, Bryan Parnoz, Aymeric Fromherzz, Chris Hawblitzel∗, Marina Polubelovay, Karthikeyan Bhargavany Benjamin Beurdouchey, Joonwon Choi∗x, Antoine Delignat-Lavaud∗,Cedric´ Fournet∗, Natalia Kulatovay, Tahina Ramananandro∗, Aseem Rastogi∗, Nikhil Swamy∗, Christoph M. Wintersteiger∗, Santiago Zanella-Beguelin∗ ∗Microsoft Research zCarnegie Mellon University yInria xMIT Abstract—We present EverCrypt: a comprehensive collection prone (due in part to Intel and AMD reporting CPU features of verified, high-performance cryptographic functionalities avail- inconsistently [78]), with various cryptographic providers able via a carefully designed API. The API provably supports invoking illegal instructions on specific platforms [74], leading agility (choosing between multiple algorithms for the same functionality) and multiplexing (choosing between multiple im- to killed processes and even crashing kernels. plementations of the same algorithm). Through abstraction and Since a cryptographic provider is the linchpin of most zero-cost generic programming, we show how agility can simplify security-sensitive applications, its correctness and security are verification without sacrificing performance, and we demonstrate crucial. However, for most applications (e.g., TLS, cryptocur- how C and assembly can be composed and verified against rencies, or disk encryption), the provider is also on the critical shared specifications. We substantiate the effectiveness of these techniques with -
Specialising Dynamic Techniques for Implementing the Ruby Programming Language
SPECIALISING DYNAMIC TECHNIQUES FOR IMPLEMENTING THE RUBY PROGRAMMING LANGUAGE A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Engineering and Physical Sciences 2015 By Chris Seaton School of Computer Science This published copy of the thesis contains a couple of minor typographical corrections from the version deposited in the University of Manchester Library. [email protected] chrisseaton.com/phd 2 Contents List of Listings7 List of Tables9 List of Figures 11 Abstract 15 Declaration 17 Copyright 19 Acknowledgements 21 1 Introduction 23 1.1 Dynamic Programming Languages.................. 23 1.2 Idiomatic Ruby............................ 25 1.3 Research Questions.......................... 27 1.4 Implementation Work......................... 27 1.5 Contributions............................. 28 1.6 Publications.............................. 29 1.7 Thesis Structure............................ 31 2 Characteristics of Dynamic Languages 35 2.1 Ruby.................................. 35 2.2 Ruby on Rails............................. 36 2.3 Case Study: Idiomatic Ruby..................... 37 2.4 Summary............................... 49 3 3 Implementation of Dynamic Languages 51 3.1 Foundational Techniques....................... 51 3.2 Applied Techniques.......................... 59 3.3 Implementations of Ruby....................... 65 3.4 Parallelism and Concurrency..................... 72 3.5 Summary............................... 73 4 Evaluation Methodology 75 4.1 Evaluation Philosophy -
An Empirical Evaluation of Osgi Dependencies Best Practices in the Eclipse IDE Lina Ochoa, Thomas Degueule, Jurgen Vinju
An Empirical Evaluation of OSGi Dependencies Best Practices in the Eclipse IDE Lina Ochoa, Thomas Degueule, Jurgen Vinju To cite this version: Lina Ochoa, Thomas Degueule, Jurgen Vinju. An Empirical Evaluation of OSGi Dependencies Best Practices in the Eclipse IDE. 15th International Conference on Mining Software Repositories, May 2018, Gothenburg, Sweden. 10.1145/3196398.3196416. hal-01740131 HAL Id: hal-01740131 https://hal.archives-ouvertes.fr/hal-01740131 Submitted on 27 Mar 2018 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 Empirical Evaluation of OSGi Dependencies Best Practices in the Eclipse IDE Lina Ochoa Thomas Degueule Jurgen Vinju Centrum Wiskunde & Informatica Centrum Wiskunde & Informatica Centrum Wiskunde & Informatica Amsterdam, Netherlands Amsterdam, Netherlands Amsterdam, Netherlands [email protected] [email protected] Eindhoven University of Technology Eindhoven, Netherlands [email protected] ABSTRACT that can be implemented and tested independently. This also fos- OSGi is a module system and service framework that aims to fill ters reuse by allowing software components to be reused from one Java’s lack of support for modular development. Using OSGi, devel- system to the other, or even to be substituted by one another pro- opers divide software into multiple bundles that declare constrained vided that they satisfy the appropriate interface expected by a client. -
An Overview of Feature-Oriented Software Development
Vol. 8, No. 4, July{August 2009 An Overview of Feature-Oriented Software Development Sven Apel, Department of Informatics and Mathematics, University of Passau, Germany Christian K¨astner, School of Computer Science, University of Magdeburg, Germany Feature-oriented software development (FOSD) is a paradigm for the construction, customization, and synthesis of large-scale software systems. In this survey, we give an overview and a personal perspective on the roots of FOSD, connections to other software development paradigms, and recent developments in this field. Our aim is to point to connections between different lines of research and to identify open issues. 1 INTRODUCTION Feature-oriented software development (FOSD) is a paradigm for the construction, customization, and synthesis of large-scale software systems. The concept of a fea- ture is at the heart of FOSD. A feature is a unit of functionality of a software system that satisfies a requirement, represents a design decision, and provides a potential configuration option. The basic idea of FOSD is to decompose a software system in terms of the features it provides. The goal of the decomposition is to construct well-structured software that can be tailored to the needs of the user and the appli- cation scenario. Typically, from a set of features, many different software systems can be generated that share common features and differ in other features. The set of software systems generated from a set of features is also called a software product line [45,101]. FOSD aims essentially at three properties: structure, reuse, and variation. De- velopers use the concept of a feature to structure design and code of a software system, features are the primary units of reuse in FOSD, and the variants of a software system vary in the features they provide.