COMMON LISP: a Gentle Introduction to Symbolic Computation COMMON LISP: a Gentle Introduction to Symbolic Computation
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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 -
CSC 242: Artificial Intelligence
CSC 242: Artificial Intelligence Course website: www.cs.rochester.edu/u/kyros/courses/csc242 Instructor: Kyros Kutulakos Office: 623 CSB Extension: x5-5860 Email: [email protected] Hours: TR 3:30-4:30 (or by appointment) TA: Joel Tetreault Email: [email protected] Hours: M 1:00-2:00 Recitations: TBA Textbooks: Russell & Norvig, Artificial Intelligence Wilensky, Common LISPcraft Another very good LISP textbook: Winston & Horn, LISP (Addison-Wesley) Common Lisp • LISP is one of the most common “AI programming languages” • LISP (=LISt Processing) is a language whose main power is in manipulating lists of symbols: (a b c (d e f (g h))) arithmetic operations are also included (sqrt (+ (* 3 3) (* 4 4))) • Lisp is a general-purpose, interpreter-based language • All computation consists of expression evaluations: lisp-prompt>(sqrt (+ (* 3 3) (* 4 4))) lisp-prompt> 25 • Since data are list structures and programs are list structures, we can manipulate programs just like data • Lisp is the second-oldest high-level programming language (after Fortran) Getting Started • Command-line invocation unix-prompt>cl system responds with loading & initialization messages followed by a Lisp prompt USER(1): whenever you have balanced parentheses & hit return, the value of the expression (or an error message) are returned USER(1): (+ 1 2) 3 saying “hello” USER(2): ‘hello HELLO USER(3): “Hello” “Hello” • Exiting Lisp: USER(2):(exit) unix-prompt> Getting Started (cont.) • Reading a file f that is in the same directory from which you are running Lisp: -
UNIX Workshop Series: Quick-Start Objectives
Part I UNIX Workshop Series: Quick-Start Objectives Overview – Connecting with ssh Command Window Anatomy Command Structure Command Examples Getting Help Files and Directories Wildcards, Redirection and Pipe Create and edit files Overview Connecting with ssh Open a Terminal program Mac: Applications > Utilities > Terminal ssh –Y [email protected] Linux: In local shell ssh –Y [email protected] Windows: Start Xming and PuTTY Create a saved session for the remote host name centos.css.udel.edu using username Connecting with ssh First time you connect Unix Basics Multi-user Case-sensitive Bash shell, command-line Commands Command Window Anatomy Title bar Click in the title bar to bring the window to the front and make it active. Command Window Anatomy Login banner Appears as the first line of a login shell. Command Window Anatomy Prompts Appears at the beginning of a line and usually ends in $. Command Window Anatomy Command input Place to type commands, which may have options and/or arguments. Command Window Anatomy Command output Place for command response, which may be many lines long. Command Window Anatomy Input cursor Typed text will appear at the cursor location. Command Window Anatomy Scroll Bar Will appear as needed when there are more lines than fit in the window. Command Window Anatomy Resize Handle Use the mouse to change the window size from the default 80x24. Command Structure command [arguments] Commands are made up of the actual command and its arguments. command -options [arguments] The arguments are further broken down into the command options which are single letters prefixed by a “-” and other arguments that identify data for the command. -
CIS 90 - Lesson 2
CIS 90 - Lesson 2 Lesson Module Status • Slides - draft • Properties - done • Flash cards - NA • First minute quiz - done • Web calendar summary - done • Web book pages - gillay done • Commands - done • Lab tested – done • Print latest class roster - na • Opus accounts created for students submitting Lab 1 - • CCC Confer room whiteboard – done • Check that headset is charged - done • Backup headset charged - done • Backup slides, CCC info, handouts on flash drive - done 1 CIS 90 - Lesson 2 [ ] Has the phone bridge been added? [ ] Is recording on? [ ] Does the phone bridge have the mike? [ ] Share slides, putty, VB, eko and Chrome [ ] Disable spelling on PowerPoint 2 CIS 90 - Lesson 2 Instructor: Rich Simms Dial-in: 888-450-4821 Passcode: 761867 Emanuel Tanner Merrick Quinton Christopher Zachary Bobby Craig Jeff Yu-Chen Greg L Tommy Eric Dan M Geoffrey Marisol Jason P David Josh ? ? ? ? Leobardo Gabriel Jesse Tajvia Daniel W Jason W Terry? James? Glenn? Aroshani? ? ? ? ? ? ? = need to add (with add code) to enroll in Ken? Luis? Arturo? Greg M? Ian? this course Email me ([email protected]) a relatively current photo of your face for 3 points extra credit CIS 90 - Lesson 2 First Minute Quiz Please close your books, notes, lesson materials, forum and answer these questions in the order shown: 1. What command shows the other users logged in to the computer? 2. What is the lowest level, inner-most component of a UNIX/Linux Operating System called? 3. What part of UNIX/Linux is both a user interface and a programming language? email answers to: [email protected] 4 CIS 90 - Lesson 2 Commands Objectives Agenda • Understand how the UNIX login • Quiz operation works. -
The Copyright Law of the United States (Title 17, U.S
NOTICE WARNING CONCERNING COPYRIGHT RESTRICTIONS: The copyright law of the United States (title 17, U.S. Code) governs the making of photocopies or other reproductions of copyrighted material. Any copying of this document without permission of its author may be prohibited by law. CMU Common Lisp User's Manual Mach/IBM RT PC Edition David B. McDonald, Editor April 1989 CMU-CS-89-132 . School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 This is a revised version of Technical Report CMU-CS-87-156. Companion to Common Lisp: The Language Abstract CMU Common Lisp is an implementation of Common Lisp that currently runs on the IBM RT PC under Mach, a Berkeley Unix 4.3 binary compatible operating system. This document describes the implementation dependent choices made in developing this implementation of Common Lisp. Also, several extensions have been added, including the proposed error system, a stack crawling debugger, a stepper, an interface to Mach system calls, a foreign function call interface, the ability to write assembler language routines, and other features that provide a good environment for developing Lisp code. This research was sponsored by the Defense Advanced Research Projects Agency (DOD), ARPA Order No. 4976 under contract F33615-87-C-1499 and monitored by the Avionics Laboratory, Air Force Wright Aeronautical Laboratories, Aeronautical Systems Division (AFSC), Wright-Patterson AFB, OHIO 45433-6543. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the U.S. -
An Implementation of Python for Racket
An Implementation of Python for Racket Pedro Palma Ramos António Menezes Leitão INESC-ID, Instituto Superior Técnico, INESC-ID, Instituto Superior Técnico, Universidade de Lisboa Universidade de Lisboa Rua Alves Redol 9 Rua Alves Redol 9 Lisboa, Portugal Lisboa, Portugal [email protected] [email protected] ABSTRACT Keywords Racket is a descendent of Scheme that is widely used as a Python; Racket; Language implementations; Compilers first language for teaching computer science. To this end, Racket provides DrRacket, a simple but pedagogic IDE. On the other hand, Python is becoming increasingly popular 1. INTRODUCTION in a variety of areas, most notably among novice program- The Racket programming language is a descendent of Scheme, mers. This paper presents an implementation of Python a language that is well-known for its use in introductory for Racket which allows programmers to use DrRacket with programming courses. Racket comes with DrRacket, a ped- Python code, as well as adding Python support for other Dr- agogic IDE [2], used in many schools around the world, as Racket based tools. Our implementation also allows Racket it provides a simple and straightforward interface aimed at programs to take advantage of Python libraries, thus signif- inexperienced programmers. Racket provides different lan- icantly enlarging the number of usable libraries in Racket. guage levels, each one supporting more advanced features, that are used in different phases of the courses, allowing Our proposed solution involves compiling Python code into students to benefit from a smoother learning curve. Fur- semantically equivalent Racket source code. For the run- thermore, Racket and DrRacket support the development of time implementation, we present two different strategies: additional programming languages [13]. -
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. -
Common Lispworks User Guide
LispWorks® for the Windows® Operating System Common LispWorks User Guide Version 5.1 Copyright and Trademarks Common LispWorks User Guide (Windows version) Version 5.1 February 2008 Copyright © 2008 by LispWorks Ltd. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of LispWorks Ltd. The information in this publication is provided for information only, is subject to change without notice, and should not be construed as a commitment by LispWorks Ltd. LispWorks Ltd assumes no responsibility or liability for any errors or inaccuracies that may appear in this publication. The software described in this book is furnished under license and may only be used or copied in accordance with the terms of that license. LispWorks and KnowledgeWorks are registered trademarks of LispWorks Ltd. Adobe and PostScript are registered trademarks of Adobe Systems Incorporated. Other brand or product names are the registered trade- marks or trademarks of their respective holders. The code for walker.lisp and compute-combination-points is excerpted with permission from PCL, Copyright © 1985, 1986, 1987, 1988 Xerox Corporation. The XP Pretty Printer bears the following copyright notice, which applies to the parts of LispWorks derived therefrom: Copyright © 1989 by the Massachusetts Institute of Technology, Cambridge, Massachusetts. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, pro- vided that this copyright and permission notice appear in all copies and supporting documentation, and that the name of M.I.T. -
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. -
How Lisp Systems Look Different in Proceedings of European Conference on Software Maintenance and Reengineering (CSMR 2008)
How Lisp Systems Look Different In Proceedings of European Conference on Software Maintenance and Reengineering (CSMR 2008) Adrian Dozsa Tudor Gˆırba Radu Marinescu Politehnica University of Timis¸oara University of Berne Politehnica University of Timis¸oara Romania Switzerland Romania [email protected] [email protected] [email protected] Abstract rently used in a variety of domains, like bio-informatics (BioBike), data mining (PEPITe), knowledge-based en- Many reverse engineering approaches have been devel- gineering (Cycorp or Genworks), video games (Naughty oped to analyze software systems written in different lan- Dog), flight scheduling (ITA Software), natural language guages like C/C++ or Java. These approaches typically processing (SRI International), CAD (ICAD or OneSpace), rely on a meta-model, that is either specific for the language financial applications (American Express), web program- at hand or language independent (e.g. UML). However, one ming (Yahoo! Store or reddit.com), telecom (AT&T, British language that was hardly addressed is Lisp. While at first Telecom Labs or France Telecom R&D), electronic design sight it can be accommodated by current language inde- automation (AMD or American Microsystems) or planning pendent meta-models, Lisp has some unique features (e.g. systems (NASA’s Mars Pathfinder spacecraft mission) [16]. macros, CLOS entities) that are crucial for reverse engi- neering Lisp systems. In this paper we propose a suite of Why Lisp is Different. In spite of its almost fifty-year new visualizations that reveal the special traits of the Lisp history, and of the fact that other programming languages language and thus help in understanding complex Lisp sys- borrowed concepts from it, Lisp still presents some unique tems. -
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.