Common Lisp As an Embedded Extension Language
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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. -
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. -
Allegro CL User Guide
Allegro CL User Guide Volume 1 (of 2) version 4.3 March, 1996 Copyright and other notices: This is revision 6 of this manual. This manual has Franz Inc. document number D-U-00-000-01-60320-1-6. Copyright 1985-1996 by Franz Inc. All rights reserved. No part of this pub- lication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means electronic, mechanical, by photocopying or recording, or otherwise, without the prior and explicit written permission of Franz incorpo- rated. Restricted rights legend: Use, duplication, and disclosure by the United States Government are subject to Restricted Rights for Commercial Software devel- oped at private expense as specified in DOD FAR 52.227-7013 (c) (1) (ii). Allegro CL and Allegro Composer are registered trademarks of Franz Inc. Allegro Common Windows, Allegro Presto, Allegro Runtime, and Allegro Matrix are trademarks of Franz inc. Unix is a trademark of AT&T. The Allegro CL software as provided may contain material copyright Xerox Corp. and the Open Systems Foundation. All such material is used and distrib- uted with permission. Other, uncopyrighted material originally developed at MIT and at CMU is also included. Appendix B is a reproduction of chapters 5 and 6 of The Art of the Metaobject Protocol by G. Kiczales, J. des Rivieres, and D. Bobrow. All this material is used with permission and we thank the authors and their publishers for letting us reproduce their material. Contents Volume 1 Preface 1 Introduction 1.1 The language 1-1 1.2 History 1-1 1.3 Format -
Writing a Best-Effort Portable Code Walker in Common Lisp
Writing a best-effort portable code walker in Common Lisp Michael Raskin∗ LaBRI, University of Bordeaux [email protected] ABSTRACT ACM Reference format: One of the powerful features of the Lisp language family is Michael Raskin. 2017. Writing a best-effort portable code walker possibility to extend the language using macros. Some of in Common Lisp. In Proceedings of 10th European Lisp Simpo- sium, Vrije Universiteit Brussel, Belgium, April 2017 (ELS2017), possible extensions would benefit from a code walker, i.e. a 8 pages. library for processing code that keeps track of the status DOI: 10.5281/zenodo.3254669 of different part of code, for their implementation. But in practice code walking is generally avoided. In this paper, we study facilities useful to code walkers 1 INTRODUCTION provided by \Common Lisp: the Language" (2nd edition) and the Common Lisp standard. We will show that the Much of the power of Common Lisp comes from its extensibil- features described in the standard are not sufficient to write ity. Abstractions that cannot be expressed by functions can a fully portable code walker. still be expressed by macros; actually, many of the features One of the problems is related to a powerful but rarely described in the standard must be implemented as macros. discussed feature. The macrolet special form allows a macro Whilst macros are powerful on their own, some ways of function to pass information easily to other macro invocations extending Lisp would benefit from using higher-level code inside the lexical scope of the expansion. transformation abstractions. For many such abstractions the Another problem for code analysis is related to the usage of most natural way to implement them includes code walk- non-standard special forms in expansions of standard macros. -
A Lisp Oriented Architecture by John W.F
A Lisp Oriented Architecture by John W.F. McClain Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degrees of Master of Science in Electrical Engineering and Computer Science and Bachelor of Science in Electrical Engineering at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY September 1994 © John W.F. McClain, 1994 The author hereby grants to MIT permission to reproduce and to distribute copies of this thesis document in whole or in part. Signature of Author ...... ;......................... .............. Department of Electrical Engineering and Computer Science August 5th, 1994 Certified by....... ......... ... ...... Th nas F. Knight Jr. Principal Research Scientist 1,,IA £ . Thesis Supervisor Accepted by ....................... 3Frederic R. Morgenthaler Chairman, Depattee, on Graduate Students J 'FROM e ;; "N MfLIT oARIES ..- A Lisp Oriented Architecture by John W.F. McClain Submitted to the Department of Electrical Engineering and Computer Science on August 5th, 1994, in partial fulfillment of the requirements for the degrees of Master of Science in Electrical Engineering and Computer Science and Bachelor of Science in Electrical Engineering Abstract In this thesis I describe LOOP, a new architecture for the efficient execution of pro- grams written in Lisp like languages. LOOP allows Lisp programs to run at high speed without sacrificing safety or ease of programming. LOOP is a 64 bit, long in- struction word architecture with support for generic arithmetic, 64 bit tagged IEEE floats, low cost fine grained read and write barriers, and fast traps. I make estimates for how much these Lisp specific features cost and how much they may speed up the execution of programs written in Lisp. -
Common Lisp Ultraspec – a Project for Modern Common Lisp Documentation
Common Lisp UltraSpec – A Project For Modern Common Lisp Documentation Michał „phoe” Herda #lisp-pl @ Freenode Jagiellonian University, Cracow, Poland Previously on European Lisp Symposium 2016 Yet Another Rant About The State Of Common Lisp Documentation Michał „phoe” Herda Presenting the European Lisp Symposium 2017 Exclusive: Yet Another Rant About The State Of Common Lisp Documentation, Part 2 Michał „phoe” Herda http://www.lispworks.com/documentation/HyperSpec/... http://www.sbcl.org/manual/... http://ccl.clozure.com/manual/... http://www.clisp.org/... http://bauhh.dyndns.org:8000/clim-spec/... http://bauhh.de/clxman/... http://metamodular.com/CLOS-MOP/... 50+(?) more websites with library-specific docs Fin, Part 2 (...except it’s not) A Possible Solution To The State Of Common Lisp Documentation, Part 2 Michał „phoe” Herda Parsing dpANS with RegEx Parsing HTML (context-free grammar) with RegEx (regular grammar): Parsing TeX (context-sensitive grammar) with RegEx (regular grammar): Parsing a known subset of TeX used in dpANS with RegEx (regular grammar): (with proper care) What’s done so far? ● Done ● All Dictionaries (e.g. MAPCAR, ADJOIN, …) ● Glossary ● Not done / TODO ● Concepts (e.g. 2.2 Reader Algorithm) ● Linking (esp. glossary entries) What’s done so far? ● Done ● All Dictionaries (e.g. MAPCAR, ADJOIN, …) ● Glossary ● Not done / TODO ● Concepts (e.g. 2.2 Reader Algorithm) ● Linking (esp. glossary entries) ● Review ● Diffs to the original dpANS ● Once it’s finished, SHIP IT! What am I aiming for? Editable Complete Downloadable -
A Note on the Optimal Allocation of Spaces in MACLISP by Henry C
MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY Al Working Paper 142 March 16, 1977 A Note on the Optimal Allocation of Spaces in MACLISP by Henry C. Baker, Jr. This note describes a method for allocating storage among the various spaces in the MACLISP Implementation of LISP. The optimal strategy which minimizes garbage collector effort allocates free storage among the various spaces in snch a way that they all run out at the same time. In an equilibrium situation, this corresponds to allocating free storage to the spaces in proportion to their usage. Methods are investigated by which the rates of usage can be inferred, and a ge-daemon interrupt handler is developed which implements an approximately optimal strategy in MACLISP. Finally, the sensitivity of this method to rapidly varying differential rates of cell usage is discussed. Key Words and Phrases: garbage collection, list processing, virtual memory, storage management, storage allocation, LISP. CR Categories: 3.50, 3.60, 3.73, 3.80, 4.13, 422, 4.32, 4.33, 4.35, 4.49 This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0522. Working Papers are informal papers intended for internal use. March 16, 1977 A Note on the Optimal Allocation of Spaces in MACLISP Henry C. Baker, Jr. MACLISP [11 unlike some other implementations of. LISP, allocates storage for different types of objects in non-contiguous areas called spaces. -
Commonloops Merging Lisp and Object-Oriented Programming Daniel G
CommonLoops Merging Lisp and Object-Oriented Programming Daniel G. Bobrow, Kenneth Kahn, Gregor Kiczales, Larry Masinter, Mark Stefik, and Frank Zdybel Xerox Palo Alto Research Center Palo Alto, California 94304 CommonLoops blends object-oriented programming Within the procedure-oriented paradigm, Lisp smoothly and tightly with the procedure-oriented provides an important approach for factoring design of Lisp. Functions and methods are combined programs that is'different from common practice in in a more general abstraction. Message passing is object-oriented programming. In this paper we inuoked via normal Lisp function call. Methods are present the linguistic mechanisms that we have viewed as partial descriptions of procedures. Lisp data developed for integrating these styles. We argue that types are integrated with object classes. With these the unification results in something greater than the integrations, it is easy to incrementally move a program sum of the parts, that is, that the mechanisms needed between the procedure and object -oriented styles. for integrating object-oriented and procedure-oriented approaches give CommonLoops surprising strength. One of the most important properties of CommonLoops is its extenswe use of meta-objects. We discuss three We describe a smooth integration of these ideas that kinds of meta-objects: objects for classes, objects for can work efficiently in Lisp systems implemented on a methods, and objects for discriminators. We argue that wide variety of machines. We chose the Common Lisp these meta-objects make practical both efficient dialect as a base on which to bui|d CommonLoops (a implementation and experimentation with new ideas Common Lisp Object-Oriented Programming System). -
Successful Lisp - Contents
Successful Lisp - Contents Table of Contents ● About the Author ● About the Book ● Dedication ● Credits ● Copyright ● Acknowledgments ● Foreword ● Introduction 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 Appendix A ● Chapter 1 - Why Bother? Or: Objections Answered Chapter objective: Describe the most common objections to Lisp, and answer each with advice on state-of-the-art implementations and previews of what this book will explain. ❍ I looked at Lisp before, and didn't understand it. ❍ I can't see the program for the parentheses. ❍ Lisp is very slow compared to my favorite language. ❍ No one else writes programs in Lisp. ❍ Lisp doesn't let me use graphical interfaces. ❍ I can't call other people's code from Lisp. ❍ Lisp's garbage collector causes unpredictable pauses when my program runs. ❍ Lisp is a huge language. ❍ Lisp is only for artificial intelligence research. ❍ Lisp doesn't have any good programming tools. ❍ Lisp uses too much memory. ❍ Lisp uses too much disk space. ❍ I can't find a good Lisp compiler. ● Chapter 2 - Is this Book for Me? Chapter objective: Describe how this book will benefit the reader, with specific examples and references to chapter contents. ❍ The Professional Programmer http://psg.com/~dlamkins/sl/contents.html (1 of 13)11/3/2006 5:46:04 PM Successful Lisp - Contents ❍ The Student ❍ The Hobbyist ❍ The Former Lisp Acquaintance ❍ The Curious ● Chapter 3 - Essential Lisp in Twelve Lessons Chapter objective: Explain Lisp in its simplest form, without worrying about the special cases that can confuse beginners. -
Special Topics: Programming Languages
Lecture #11 • 0 V22.0490.001 Special Topics: Programming Languages B. Mishra New York University. Lecture # 11 Programming Languages • MISHRA 2008 Lecture #11 • 1 —Slide 1— Common Lisp Language Survey 4 Functional Programming • Pure Functional Programming: Implicit Principle ◦ The value of an expression depends only on the values of its subexpressions, if any. – No side-effect. (No State—No assignment) – An expression has the same value, every time. – Implicit Storage Management: Allocation on Demand + Garbage Collection. – Functions are First Class Objects: 1) As value of an expression 2) As parameters 3) As data Objects. Programming Languages • MISHRA 2008 Lecture #11 • 2 —Slide 2— Common Lisp • LISP: LIst Processing Language Not— Lots of Insidious Sill Parentheses • Second oldest Programming Language (Af- ter Fortran) • Application Areas: 1. Theorem Proving 2. Symbolic Algebra 3. AI (Artificial Intelligence) (Natural Language Processing, Com- puter Vision, Robot Control Systems, Ex- pert Systems, Neural Networks, Automatic Programming) Programming Languages • MISHRA 2008 Lecture #11 • 3 —Slide 3— HISTORY • Developed at MIT AI Lab—1959. LISP 1.5 running on an IBM machine. • BBN LISP (PDP 1/SDS 940) became → INTERLISP (PDP 10) • MACLISP (MIT Project MAC) • LISP 1.6—A version of MACLISP ◦ UCI-LISP (Univ. of Cal. at Irvine) ◦ Standard Lisp (Univ. of Utah) • Lisp Machine Lisp Large Personal Lisp Machine built at MIT • FranzLISP for Vax/UNIX (UC Berkeley) • NIL for Vax/VMS (MIT) • Scheme at MIT • T Lisp at Yale Programming Languages • MISHRA 2008 Lecture #11 • 4 —Slide 4— Common Lisp • 1981/Carnegie-Mellon/Guy L. Steele • Clean Lisp Inconsistencies and illogical conventions were resolved • Transportable Programs written in Common Lisp and debugged in one implementation should run on another ma- chine/implementation without change.