Balancing the Eulisp Metaobject Protocol
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Metaobject Protocols: Why We Want Them and What Else They Can Do
Metaobject protocols: Why we want them and what else they can do Gregor Kiczales, J.Michael Ashley, Luis Rodriguez, Amin Vahdat, and Daniel G. Bobrow Published in A. Paepcke, editor, Object-Oriented Programming: The CLOS Perspective, pages 101 ¾ 118. The MIT Press, Cambridge, MA, 1993. © Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. Metaob ject Proto cols WhyWeWant Them and What Else They Can Do App ears in Object OrientedProgramming: The CLOS Perspective c Copyright 1993 MIT Press Gregor Kiczales, J. Michael Ashley, Luis Ro driguez, Amin Vahdat and Daniel G. Bobrow Original ly conceivedasaneat idea that could help solve problems in the design and implementation of CLOS, the metaobject protocol framework now appears to have applicability to a wide range of problems that come up in high-level languages. This chapter sketches this wider potential, by drawing an analogy to ordinary language design, by presenting some early design principles, and by presenting an overview of three new metaobject protcols we have designed that, respectively, control the semantics of Scheme, the compilation of Scheme, and the static paral lelization of Scheme programs. Intro duction The CLOS Metaob ject Proto col MOP was motivated by the tension b etween, what at the time, seemed liketwo con icting desires. The rst was to have a relatively small but p owerful language for doing ob ject-oriented programming in Lisp. The second was to satisfy what seemed to b e a large numb er of user demands, including: compatibility with previous languages, p erformance compara- ble to or b etter than previous implementations and extensibility to allow further exp erimentation with ob ject-oriented concepts see Chapter 2 for examples of directions in which ob ject-oriented techniques might b e pushed. -
Towards Practical Runtime Type Instantiation
Towards Practical Runtime Type Instantiation Karl Naden Carnegie Mellon University [email protected] Abstract 2. Dispatch Problem Statement Symmetric multiple dispatch, generic functions, and variant type In contrast with traditional dynamic dispatch, the runtime of a lan- parameters are powerful language features that have been shown guage with multiple dispatch cannot necessarily use any static in- to aid in modular and extensible library design. However, when formation about the call site provided by the typechecker. It must symmetric dispatch is applied to generic functions, type parameters check if there exists a more specific function declaration than the may have to be instantiated as a part of dispatch. Adding variant one statically chosen that has the same name and is applicable to generics increases the complexity of type instantiation, potentially the runtime types of the provided arguments. The process for deter- making it prohibitively expensive. We present a syntactic restriction mining when a function declaration is more specific than another is on generic functions and an algorithm designed and implemented for laid out in [4]. A fully instantiated function declaration is applicable the Fortress programming language that simplifies the computation if the runtime types of the arguments are subtypes of the declared required at runtime when these features are combined. parameter types. To show applicability for a generic function we need to find an instantiation that witnesses the applicability and the type safety of the function call so that it can be used by the code. Formally, given 1. Introduction 1. a function signature f X <: τX (y : τy): τr, J K Symmetric multiple dispatch brings with it several benefits for 2. -
Common Lisp Object System Specification 3. Metaobject Protocol
Common Lisp Object System Specification 3. Metaobject Protocol This document was written by Daniel G. Bobrow, Linda G. DeMichiel, Richard P. Gabriel, Sonya E. Keene, Gregor Kiczales, and David A. Moon. Contributors to this document include Patrick Dussud, Kenneth Kahn, Jim Kempf, Larry Masinter, Mark Stefik, Daniel L. Weinreb, and Jon L White. CONTENTS CONTENTS ................................................... ............ 3–2 Status of Document ................................................... ........... 3–5 Terminology ................................................... ................ 3–6 Introduction ................................................... ................ 3–7 Class Organization in the CLOS Kernel ............................................... 3–9 The Classes in the CLOS Kernel ................................................... 3–10 standard-class ................................................... ............ 3–11 forward-referenced-class ................................................... ..... 3–11 built-in-class ................................................... ............. 3–11 structure-class ................................................... ............ 3–12 funcallable-standard-class ................................................... .... 3–12 standard-slot-description ................................................... .... 3–12 standard-class-slot-description ................................................... 3–12 standard-method ................................................... .......... 3–12 -
The Evolution of Lisp
1 The Evolution of Lisp Guy L. Steele Jr. Richard P. Gabriel Thinking Machines Corporation Lucid, Inc. 245 First Street 707 Laurel Street Cambridge, Massachusetts 02142 Menlo Park, California 94025 Phone: (617) 234-2860 Phone: (415) 329-8400 FAX: (617) 243-4444 FAX: (415) 329-8480 E-mail: [email protected] E-mail: [email protected] Abstract Lisp is the world’s greatest programming language—or so its proponents think. The structure of Lisp makes it easy to extend the language or even to implement entirely new dialects without starting from scratch. Overall, the evolution of Lisp has been guided more by institutional rivalry, one-upsmanship, and the glee born of technical cleverness that is characteristic of the “hacker culture” than by sober assessments of technical requirements. Nevertheless this process has eventually produced both an industrial- strength programming language, messy but powerful, and a technically pure dialect, small but powerful, that is suitable for use by programming-language theoreticians. We pick up where McCarthy’s paper in the first HOPL conference left off. We trace the development chronologically from the era of the PDP-6, through the heyday of Interlisp and MacLisp, past the ascension and decline of special purpose Lisp machines, to the present era of standardization activities. We then examine the technical evolution of a few representative language features, including both some notable successes and some notable failures, that illuminate design issues that distinguish Lisp from other programming languages. We also discuss the use of Lisp as a laboratory for designing other programming languages. We conclude with some reflections on the forces that have driven the evolution of Lisp. -
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 . -
OOD and C++ Section 5: Templates
Templates - Generic Programming Decide which algorithms you want: parameterize them so that they work for OOD and C++ a wide-range of types & data structures Section 5: Templates Templates in C++ support generic progarmming Templates provide: •simple way to represent general concepts •simple way to combine concepts Use ‘data-types’ as parameters at compilation Advantage: • more general ‘generic code’ • reuse same code for different data types • less bugs - only implement/debug one piece of code • no overhead on run-time efficiency compared to data specific code Use of Templates Templates in C++ Make the definition of your class as broad as possible! template class declaration: mytemplate.hh template <class DataC> class mytemplate { public: Widely used for container classes: mytemplate(); • Storage independent of data type void function(); • C++ Standard Template Library (Arrays,Lists,…..) protected: int protected_function(); Encapsulation: private: Hide a sophisticated implementation behind a simple double private_data; interface }; template <class DataC>: • specifies a template is being declared • type parameter ‘DataC’ (generic class) will be used • DataC can be any type name: class, built in type, typedef • DataC must contain data/member functions which are used in template implementation. Example - Generic Array Example - Generic Array (cont’d) simple_array.hh template<class DataC> class simple_array { private: #include “simple_array.hh” int size; DataC *array; #include “string.hh” public: void myprogram(){ simple_array(int s); simple_array<int> intarray(100); ~simple_array(); simple_array<double> doublearray(200); DataC& operator[](int i); simple_array<StringC> stringarray(500); }; for (int i(0); i<100; i++) template<class DataC> intarray[i] = i*10; simple_array<DataC>::simple_array(int s) : size(s) { array = new DataC[size]; } // & the rest…. -
Julia: a Modern Language for Modern ML
Julia: A modern language for modern ML Dr. Viral Shah and Dr. Simon Byrne www.juliacomputing.com What we do: Modernize Technical Computing Today’s technical computing landscape: • Develop new learning algorithms • Run them in parallel on large datasets • Leverage accelerators like GPUs, Xeon Phis • Embed into intelligent products “Business as usual” will simply not do! General Micro-benchmarks: Julia performs almost as fast as C • 10X faster than Python • 100X faster than R & MATLAB Performance benchmark relative to C. A value of 1 means as fast as C. Lower values are better. A real application: Gillespie simulations in systems biology 745x faster than R • Gillespie simulations are used in the field of drug discovery. • Also used for simulations of epidemiological models to study disease propagation • Julia package (Gillespie.jl) is the state of the art in Gillespie simulations • https://github.com/openjournals/joss- papers/blob/master/joss.00042/10.21105.joss.00042.pdf Implementation Time per simulation (ms) R (GillespieSSA) 894.25 R (handcoded) 1087.94 Rcpp (handcoded) 1.31 Julia (Gillespie.jl) 3.99 Julia (Gillespie.jl, passing object) 1.78 Julia (handcoded) 1.2 Those who convert ideas to products fastest will win Computer Quants develop Scientists prepare algorithms The last 25 years for production (Python, R, SAS, DEPLOY (C++, C#, Java) Matlab) Quants and Computer Compress the Scientists DEPLOY innovation cycle collaborate on one platform - JULIA with Julia Julia offers competitive advantages to its users Julia is poised to become one of the Thank you for Julia. Yo u ' v e k i n d l ed leading tools deployed by developers serious excitement. -
Ccured Type-Safe Retrofitting of Legacy Code
CCured Type-Safe Retrofitting of Legacy Code George C. Necula Scott McPeak Westley Weimer University of California, Berkeley {necula, smcpeak, weimer}@cs, berkeley, edu Abstract While in lhe 1970s sacrificing lype safely for flexibilily and perfbrmance mighl have been a sensible language design In lhis paper we propose a scheme lhai combines type in- choice, today lhere are more and more siiuaiions in which ference and run-time checking to make exisiing C programs type safety is jusi as imporiani as, if noi more importani type saI~. }V~ describe lhe CCured type sysiem, which ex- lhan, performance. Errors like array oui-of:bounds accesses lends lhat of C by separaiing poinier types according to lead boih lo painful debugging sessions chasing inadverieni lheir usage. This type sysiem allows boih poiniers whose memory updaies and lo malicious atiacks exploiiing buft>r usage can be verified siaiically to be type saI>, and poiniers overrun errors in security-criiical code. (Almost g0% of re- whose sai>ty musi be checked ai run lime. }V~ prove a type ceni CERT advisories resuli fi'om security violaiions of this soundness resuli and lhen we preseni a surprisingly simple kind [29].) Type safety is desirable for isolaiing program type inference algoriihm lhai is able lo infer lhe appropriaie componenis in a large or exiensible sysiem, wiihoui lhe loss poinier kinds for exisiing C programs. of performance of separaie address spaces. II is also valu- Our experience wiih lhe CCured sysiem shows lhai lhe able for inter-operaiion wiih sysiems wriiien in type-saf> inference is very eft~ciive for many C programs, as ii is able languages (such as type-saf> Java naiive meihods, for exam- io infer ihai most or all of the pointers are statically ver- pie). -
Genericity Vs Inheritance
s Genericity Versus Inheritance Bertrand Meyer Interactive Software Engineering, Inc., 270 Storke Road, Suite #7, Goleta CA 93117 ABSTRACT with which a software system may be changed to account for modifications of its requirements), reus Genericity, as in Ada or ML, and inheritance, as in ability (the ability of a system to be reused, in whole object-oriented languages, are two alternative tech or in parts, for the construction of new systems), and niques for ensuring better extendibility, reusability, compatibility (the ease of combining a system with and compatibility of software components. This ar others). ticle is a comparative analysis of these two methods. Good answers to these issues are not purely It studies their similarities and differences and as technical, but must include economical and mana sesses to what extent each may be simulated in a gerial components as well; and their technical as language offering only the other. It shows what fea pects extend beyond programming language fea tures are needed to successfully combine the two ap tures' to such obviously relevant concerns as proaches in an object-oriented language that also fea specification and design techniques. It would be wrong, tures strong type checking. The discussion introduces however, to underestimate the technical aspects and, the principal aspects of the language EiffePM whose among these, the role played by proper programming design, resulting in part from this study, includes language features: any acceptable solution must in multiple inheritance and a limited form of genericity the end be expressible in terms of programs, and under full static typing. programming languages fundamentally shape the software designers' way of thinking. -
The Embeddable Common Lisp
ACM Lisp Pointers 8(1), 1995, 30-41 The Embeddable Common Lisp Giuseppe Attardi Dipartimento di Informatica, Universit`adi Pisa Corso Italia 40, I-56125 Pisa, Italy net: [email protected] Abstract The Embeddable Common Lisp is an implementation of Common Lisp designed for being embeddable within C based applications. ECL uses standard C calling conventions for Lisp compiled functions, which allows C programs to easily call Lisp functions and viceversa. No foreign function interface is required: data can be exchanged between C and Lisp with no need for conversion. ECL is based on a Common Runtime Support (CRS) which provides basic facilities for memory management, dynamic loading and dumping of binary images, support for multiple threads of execution. The CRS is built into a library that can be linked with the code of the application. ECL is modular: main modules are the program development tools (top level, debugger, trace, stepper), the compiler, and CLOS. A native implementation of CLOS is available in ECL: one can configure ECL with or without CLOS. A runtime version of ECL can be built with just the modules which are required by the application. 1 Introduction As applications become more elaborate, the facilities required to build them grow in number and sophistica- tion. Each facility is accessed through a specific package, quite complex itself, like in the cases of: modeling, simulation, graphics, hypertext facilities, data base management, numerical analysis, deductive capabilities, concurrent programming, heuristic search, symbolic manipulation, language analysis, special device control. Reusability is quite a significant issue: once a package has been developed, tested and debugged, it is un- desirable having to rewrite it in a different language just because the application is based in such other language. -
Object Oriented Programming
Object oriented programming ✔ The main ideas behind object-oriented programming: ✗ the same type of action may be carried out differently on different types of objects • cutting a cake is different from cutting cloth • driving a car is different from driving a bicycle ✗ however, a type of action may involve similar subactions when carried out on similar objects • mailing a letter involves many of the same moves as mailing a postcard • eating at a French restaurant involves many of the same procedures as eating at a Chinese restaurant ✗ a useful way of describing similarities among objects is by describing their place in an object type hierarchy • a Chinese restaurant is a type of Asian restaurant, which is a type of restaurant, which is a type of retail food outlet, which is a type of retail outlet, which is a type of business, ... ✔ So, think about procedures in relation to a hierarchy of object types LANGUAGES FOR AI Page 1 of 14 LEC 9 Object oriented programming ✔ There are two kinds of object-oriented programming perspectives ✗ message-passing systems: “object oriented perspective” • in a message passing system, messages are sent to objects • what happens depends on what the message is, and what type the object is • each object type “knows” what to do (what method to apply) with each message (send starship-1 ‘move-to-andromeda) ✗ generic function systems: “data-driven perspective” • in a generic function system, objects are passed as arguments to generic functions • what happens depends on what the function is, and what type the object is • each generic function “knows” what to do (what method to apply) with each object type (move-to-andromeda starship-1) ✔ The Common LISP Object System is a generic function system LANGUAGES FOR AI Page 2 of 14 LEC 9 The Common LISP Object System (CLOS) ✔ CLOS classes are similar to LISP structure types.. -
Protocols What Are Protocols?
Protocols What are Protocols? • A protocol is a set of possibly interacting functions. • Example: (defgeneric read-bytes (stream n)) (defgeneric read-byte (stream)) Possible Interactions • (defgeneric read-bytes (stream n)) (defgeneric read-byte (stream)) • Option 1: (defmethod read-bytes (stream n) (let ((array (make-array n))) (loop for i below n do (setf (aref array i) (read-byte stream))) array)) Possible Interactions • (defgeneric read-bytes (stream n)) (defgeneric read-byte (stream)) • Option 2: (defmethod read-byte (stream) (let ((array (read-bytes 1))) (aref array 0))) Possible Interactions • (defgeneric read-bytes (stream n)) (defgeneric read-byte (stream)) • Option 3: No interactions. (The two generic functions are independent.) • Why does it matter? You have to know what you can override and what effects overriding has. Protocols in CLOS • CLOS defines some protocols for its operators. make-instance • (defmethod make-instance (class &rest initargs) ... (let ((instance (apply #’allocate-instance class initargs))) (apply #’initialize-instance instance initargs) instance)) initialize-instance • (defmethod initialize-instance ((instance standard-object) &rest initargs) (apply #’shared-initialize instance t initargs)) Initialization Protocol • make-instance calls allocate-instance and then initialize-instance. • allocate-instance allocates storage. • initialize-instance calls shared-initialize. • shared-initialize assigns the slots. change-class • change-class modifies the object to be an instance of a different class and then calls update-instance-for-different-class. • update-instance-for-different-class calls shared-initialize. reinitialize-instance • reinitialize-instance calls shared-initialize. Class Redefinition • When a class is redefined, make-instances-obsolete may be called. • make-instances-obsolete ensures that update-instance-for-redefined-class is called for each instance.