Common Lisp Objects for Xemacs Didier Verna
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A Brief Introduction to Aspect-Oriented Programming
R R R A Brief Introduction to Aspect-Oriented Programming" R R Historical View Of Languages" R •# Procedural language" •# Functional language" •# Object-Oriented language" 1 R R Acknowledgements" R •# Zhenxiao Yang" •# Gregor Kiczales" •# Eclipse website for AspectJ (www.eclipse.org/aspectj) " R R Procedural Language" R •# Also termed imperative language" •# Describe" –#An explicit sequence of steps to follow to produce a result" •# Examples: Basic, Pascal, C, Fortran" 2 R R Functional Language" R •# Describe everything as a function (e.g., data, operations)" •# (+ 3 4); (add (prod 4 5) 3)" •# Examples" –# LISP, Scheme, ML, Haskell" R R Logical Language" R •# Also termed declarative language" •# Establish causal relationships between terms" –#Conclusion :- Conditions" –#Read as: If Conditions then Conclusion" •# Examples: Prolog, Parlog" 3 R R Object-Oriented Programming" R •# Describe " –#A set of user-defined objects " –#And communications among them to produce a (user-defined) result" •# Basic features" –#Encapsulation" –#Inheritance" –#Polymorphism " R R OOP (cont$d)" R •# Example languages" –#First OOP language: SIMULA-67 (1970)" –#Smalltalk, C++, Java" –#Many other:" •# Ada, Object Pascal, Objective C, DRAGOON, BETA, Emerald, POOL, Eiffel, Self, Oblog, ESP, POLKA, Loops, Perl, VB" •# Are OOP languages procedural? " 4 R R We Need More" R •# Major advantage of OOP" –# Modular structure" •# Potential problems with OOP" –# Issues distributed in different modules result in tangled code." –# Example: error logging, failure handling, performance -
Introduction to Programming in Lisp
Introduction to Programming in Lisp Supplementary handout for 4th Year AI lectures · D W Murray · Hilary 1991 1 Background There are two widely used languages for AI, viz. Lisp and Prolog. The latter is the language for Logic Programming, but much of the remainder of the work is programmed in Lisp. Lisp is the general language for AI because it allows us to manipulate symbols and ideas in a commonsense manner. Lisp is an acronym for List Processing, a reference to the basic syntax of the language and aim of the language. The earliest list processing language was in fact IPL developed in the mid 1950’s by Simon, Newell and Shaw. Lisp itself was conceived by John McCarthy and students in the late 1950’s for use in the newly-named field of artificial intelligence. It caught on quickly in MIT’s AI Project, was implemented on the IBM 704 and by 1962 to spread through other AI groups. AI is still the largest application area for the language, but the removal of many of the flaws of early versions of the language have resulted in its gaining somewhat wider acceptance. One snag with Lisp is that although it started out as a very pure language based on mathematic logic, practical pressures mean that it has grown. There were many dialects which threaten the unity of the language, but recently there was a concerted effort to develop a more standard Lisp, viz. Common Lisp. Other Lisps you may hear of are FranzLisp, MacLisp, InterLisp, Cambridge Lisp, Le Lisp, ... Some good things about Lisp are: • Lisp is an early example of an interpreted language (though it can be compiled). -
High-Level Language Features Not Found in Ordinary LISP. the GLISP
DOCUMENT RESUME ED 232 860 SE 042 634 AUTHOR Novak, Gordon S., Jr. TITLE GLISP User's Manual. Revised. INSTITUTION Stanford Univ., Calif. Dept. of Computer Science. SPONS AGENCY Advanced Research Projects Agency (DOD), Washington, D.C.; National Science Foundation, Washington, D.C. PUB DATE 23 Nov 82 CONTRACT MDA-903-80-c-007 GRANT SED-7912803 NOTE 43p.; For related documents, see SE 042 630-635. PUB TYPE Guides General (050) Reference Materials General (130) EDRS PRICE MF01/PCO2 Plus Postage. DESCRIPTORS *Computer Programs; *Computer Science; Guides; *Programing; *Programing Languages; *Resource Materials IDENTIFIERS *GLISP Programing Language; National Science Foundation ABSTRACT GLISP is a LISP-based language which provides high-level language features not found in ordinary LISP. The GLISP language is implemented by means of a compiler which accepts GLISP as input and produces ordinary LISP as output. This output can be further compiled to machine code by the LISP compiler. GLISP is available for several ISP dialects, including Interlisp, Maclisp, UCI Lisp, ELISP, Franz Lisp, and Portable Standard Lisp. The goal of GLISP is to allow structured objects to be referenced in a convenient, succinct language and to allow the structures of objects to be changed without changing the code which references the objects. GLISP provides both PASCAL-like and English-like syntaxes; much of the power and brevity of GLISP derive from the compiler features necessary to support the relatively informal, English-like language constructs. Provided in this manual is the documentation necessary for using GLISP. The documentation is presented in the following sections: introduction; object descriptions; reference to objects; GLISP program syntax; messages; context rules and reference; GLISP and knowledge representation languages; obtaining and using GLISP; GLISP hacks (some ways of doing things in GLISP which might not be entirely obvious at first glance); and examples of GLISP object declarations and programs. -
The Machine That Builds Itself: How the Strengths of Lisp Family
Khomtchouk et al. OPINION NOTE The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models Bohdan B. Khomtchouk1*, Edmund Weitz2 and Claes Wahlestedt1 *Correspondence: [email protected] Abstract 1Center for Therapeutic Innovation and Department of We address the need for expanding the presence of the Lisp family of Psychiatry and Behavioral programming languages in bioinformatics and computational biology research. Sciences, University of Miami Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA creation of powerful and flexible software models that are required for complex 33136 and rapidly evolving domains like biology. We will point out several important key Full list of author information is features that distinguish languages of the Lisp family from other programming available at the end of the article languages and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSL): languages which are specialized to a particular area and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the “programmable programming language.” We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and AI research in bioinformatics and computational biology. -
Bringing GNU Emacs to Native Code
Bringing GNU Emacs to Native Code Andrea Corallo Luca Nassi Nicola Manca [email protected] [email protected] [email protected] CNR-SPIN Genoa, Italy ABSTRACT such a long-standing project. Although this makes it didactic, some Emacs Lisp (Elisp) is the Lisp dialect used by the Emacs text editor limitations prevent the current implementation of Emacs Lisp to family. GNU Emacs can currently execute Elisp code either inter- be appealing for broader use. In this context, performance issues preted or byte-interpreted after it has been compiled to byte-code. represent the main bottleneck, which can be broken down in three In this work we discuss the implementation of an optimizing com- main sub-problems: piler approach for Elisp targeting native code. The native compiler • lack of true multi-threading support, employs the byte-compiler’s internal representation as input and • garbage collection speed, exploits libgccjit to achieve code generation using the GNU Com- • code execution speed. piler Collection (GCC) infrastructure. Generated executables are From now on we will focus on the last of these issues, which con- stored as binary files and can be loaded and unloaded dynamically. stitutes the topic of this work. Most of the functionality of the compiler is written in Elisp itself, The current implementation traditionally approaches the prob- including several optimization passes, paired with a C back-end lem of code execution speed in two ways: to interface with the GNU Emacs core and libgccjit. Though still a work in progress, our implementation is able to bootstrap a func- • Implementing a large number of performance-sensitive prim- tional Emacs and compile all lexically scoped Elisp files, including itive functions (also known as subr) in C. -
Continuation Join Points
Continuation Join Points Yusuke Endoh, Hidehiko Masuhara, Akinori Yonezawa (University of Tokyo) 1 Background: Aspects are reusable in AspectJ (1) Example: A generic logging aspect can log user inputs in a CUI program by defining a pointcut Login Generic Logging id = readLine(); Aspect Main CUI Aspect cmd = readLine(); pointcut input(): call(readLine()) logging return value 2 Background: Aspects are reusable in AspectJ (2) Example: A generic logging aspect can also log environment variable by also defining a pointcut Q. Now, if we want to log environment variable (getEnv) …? Generic Logging Aspect A. Merely concretize an aspect additionally Env Aspect CUI Aspect pointcut input(): pointcut input(): Aspect reusability call(getEnv()) call(readLine()) 3 Problem: Aspects are not as reusable as expected Example: A generic logging aspect can NOT log inputs in a GUI program by defining a pointcut Login Generic Logging void onSubmit(id) Aspect { … } Main void onSubmit(cmd) GUI Aspect { … } pointcut Input(): call(onSubmit(Str)) logging arguments 4 Why can’t we reuse the aspect? Timing of advice execution depends on both advice modifiers and pointcuts Logging Aspect (inner) Generic Logging abstract pointcut: input(); Aspect after() returning(String s) : input() { Log.add(s); } unable to change to before 5 Workaround in AspectJ is awkward: overview Required changes for more reusable aspect: generic aspect (e.g., logging) two abstract pointcuts, two advice decls. and an auxiliary method concrete aspects two concrete pointcuts even if they are not needed 6 Workaround in AspectJ is awkward: how to define generic aspect Simple Logging Aspect 1. define two pointcuts abstract pointcut: inputAfter(); for before and after abstract pointcut: inputBefore(); after() returning(String s) : inputAfter() { log(s); } 2. -
An Evaluation of Go and Clojure
An evaluation of Go and Clojure A thesis submitted in partial satisfaction of the requirements for the degree Bachelors of Science in Computer Science Fall 2010 Robert Stimpfling Department of Computer Science University of Colorado, Boulder Advisor: Kenneth M. Anderson, PhD Department of Computer Science University of Colorado, Boulder 1. Introduction Concurrent programming languages are not new, but they have been getting a lot of attention more recently due to their potential with multiple processors. Processors have gone from growing exponentially in terms of speed, to growing in terms of quantity. This means processes that are completely serial in execution will soon be seeing a plateau in performance gains since they can only rely on one processor. A popular approach to using these extra processors is to make programs multi-threaded. The threads can execute in parallel and use shared memory to speed up execution times. These multithreaded processes can significantly speed up performance, as long as the number of dependencies remains low. Amdahl‘s law states that these performance gains can only be relative to the amount of processing that can be parallelized [1]. However, the performance gains are significant enough to be looked into. These gains not only come from the processing being divvied up into sections that run in parallel, but from the inherent gains from sharing memory and data structures. Passing new threads a copy of a data structure can be demanding on the processor because it requires the processor to delve into memory and make an exact copy in a new location in memory. Indeed some studies have shown that the problem with optimizing concurrent threads is not in utilizing the processors optimally, but in the need for technical improvements in memory performance [2]. -
Emacspeak User's Guide
Emacspeak User's Guide Jennifer Jobst Revision History Revision 1.3 July 24,2002 Revised by: SDS Updated the maintainer of this document to Sharon Snider, corrected links, and converted to HTML Revision 1.2 December 3, 2001 Revised by: JEJ Changed license to GFDL Revision 1.1 November 12, 2001 Revised by: JEJ Revision 1.0 DRAFT October 19, 2001 Revised by: JEJ This document helps Emacspeak users become familiar with Emacs as an audio desktop and provides tutorials on many common tasks and the Emacs applications available to perform those tasks. Emacspeak User's Guide Table of Contents 1. Legal Notice.....................................................................................................................................................1 2. Introduction.....................................................................................................................................................2 2.1. What is Emacspeak?.........................................................................................................................2 2.2. About this tutorial.............................................................................................................................2 3. Before you begin..............................................................................................................................................3 3.1. Getting started with Emacs and Emacspeak.....................................................................................3 3.2. Emacs Command Conventions.........................................................................................................3 -
Programming with GNU Emacs Lisp
Programming with GNU Emacs Lisp William H. Mitchell (whm) Mitchell Software Engineering (.com) GNU Emacs Lisp Programming Slide 1 Copyright © 2001-2008 by William H. Mitchell GNU Emacs Lisp Programming Slide 2 Copyright © 2001-2008 by William H. Mitchell Emacs Lisp Introduction A little history GNU Emacs Lisp Programming Slide 3 Copyright © 2001-2008 by William H. Mitchell Introduction GNU Emacs is a full-featured text editor that contains a complete Lisp system. Emacs Lisp is used for a variety of things: • Complete applications such as mail and news readers, IM clients, calendars, games, and browsers of various sorts. • Improved interfaces for applications such as make, diff, FTP, shells, and debuggers. • Language-specific editing support. • Management of interaction with version control systems such as CVS, Perforce, SourceSafe, and StarTeam. • Implementation of Emacs itself—a substantial amount of Emacs is written in Emacs Lisp. And more... GNU Emacs Lisp Programming Slide 4 Copyright © 2001-2008 by William H. Mitchell A little history1 Lisp: John McCarthy is the father of Lisp. The name Lisp comes from LISt Processing Language. Initial ideas for Lisp were formulated in 1956-1958; some were implemented in FLPL (FORTRAN-based List Processing Language). The first Lisp implementation, for application to AI problems, took place 1958-1962 at MIT. There are many dialects of Lisp. Perhaps the most commonly used dialect is Common Lisp, which includes CLOS, the Common Lisp Object System. See http://www-formal.stanford.edu/jmc/history/lisp/lisp.html for some interesting details on the early history of Lisp. 1 Don't quote me! GNU Emacs Lisp Programming Slide 5 Copyright © 2001-2008 by William H. -
Emacs Speaks Statistics (ESS): a Multi-Platform, Multi-Package Intelligent Environment for Statistical Analysis
Emacs Speaks Statistics (ESS): A multi-platform, multi-package intelligent environment for statistical analysis A.J. Rossini Richard M. Heiberger Rodney A. Sparapani Martin Machler¨ Kurt Hornik ∗ Date: 2003/10/22 17:34:04 Revision: 1.255 Abstract Computer programming is an important component of statistics research and data analysis. This skill is necessary for using sophisticated statistical packages as well as for writing custom software for data analysis. Emacs Speaks Statistics (ESS) provides an intelligent and consistent interface between the user and software. ESS interfaces with SAS, S-PLUS, R, and other statistics packages under the Unix, Microsoft Windows, and Apple Mac operating systems. ESS extends the Emacs text editor and uses its many features to streamline the creation and use of statistical software. ESS understands the syntax for each data analysis language it works with and provides consistent display and editing features across packages. ESS assists in the interactive or batch execution by the statistics packages of statements written in their languages. Some statistics packages can be run as a subprocess of Emacs, allowing the user to work directly from the editor and thereby retain a consistent and constant look- and-feel. We discuss how ESS works and how it increases statistical programming efficiency. Keywords: Data Analysis, Programming, S, SAS, S-PLUS, R, XLISPSTAT,STATA, BUGS, Open Source Software, Cross-platform User Interface. ∗A.J. Rossini is Research Assistant Professor in the Department of Biostatistics, University of Washington and Joint Assis- tant Member at the Fred Hutchinson Cancer Research Center, Seattle, WA, USA mailto:[email protected]; Richard M. -
1 What Is Gimp? 3 2 Default Short Cuts and Dynamic Keybinding 9
GUM The Gimp User Manual version 1.0.0 Karin Kylander & Olof S Kylander legalities Legalities The Gimp user manual may be reproduced and distributed, subject to the fol- lowing conditions: Copyright © 1997 1998 by Karin Kylander Copyright © 1998 by Olof S Kylander E-mail: [email protected] (summer 98 [email protected]) The Gimp User Manual is an open document; you may reproduce it under the terms of the Graphic Documentation Project Copying Licence (aka GDPL) as published by Frozenriver. This document is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANT- ABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the Graphic Documentation Project Copying License for more details. GRAPHIC DOCUMENTATION PROJECT COPYING LICENSE The following copyright license applies to all works by the Graphic Docu- mentation Project. Please read the license carefully---it is similar to the GNU General Public License, but there are several conditions in it that differ from what you may be used to. The Graphic Documentation Project manuals may be reproduced and distrib- uted in whole, subject to the following conditions: The Gimp User Manual Page i Legalities All Graphic Documentation Project manuals are copyrighted by their respective authors. THEY ARE NOT IN THE PUBLIC DOMAIN. • The copyright notice above and this permission notice must be preserved complete. • All work done under the Graphic Documentation Project Copying License must be available in source code for anyone who wants to obtain it. The source code for a work means the preferred form of the work for making modifications to it. -
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.