CONS Y X)))) Which Sets Z to Cdr[X] If Cdr[X] Is Not NIL (Without Recomputing the Value As Woirld Be Necessary in LISP 1.5
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Practical Semantic Web and Linked Data Applications
Practical Semantic Web and Linked Data Applications Common Lisp Edition Uses the Free Editions of Franz Common Lisp and AllegroGraph Mark Watson Copyright 2010 Mark Watson. All rights reserved. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works Version 3.0 United States License. November 3, 2010 Contents Preface xi 1. Getting started . xi 2. Portable Common Lisp Code Book Examples . xii 3. Using the Common Lisp ASDF Package Manager . xii 4. Information on the Companion Edition to this Book that Covers Java and JVM Languages . xiii 5. AllegroGraph . xiii 6. Software License for Example Code in this Book . xiv 1. Introduction 1 1.1. Who is this Book Written For? . 1 1.2. Why a PDF Copy of this Book is Available Free on the Web . 3 1.3. Book Software . 3 1.4. Why Graph Data Representations are Better than the Relational Database Model for Dealing with Rapidly Changing Data Requirements . 4 1.5. What if You Use Other Programming Languages Other Than Lisp? . 4 2. AllegroGraph Embedded Lisp Quick Start 7 2.1. Starting AllegroGraph . 7 2.2. Working with RDF Data Stores . 8 2.2.1. Creating Repositories . 9 2.2.2. AllegroGraph Lisp Reader Support for RDF . 10 2.2.3. Adding Triples . 10 2.2.4. Fetching Triples by ID . 11 2.2.5. Printing Triples . 11 2.2.6. Using Cursors to Iterate Through Query Results . 13 2.2.7. Saving Triple Stores to Disk as XML, N-Triples, and N3 . 14 2.3. AllegroGraph’s Extensions to RDF . -
Document Number Scco24
Stanford University Libraries Dept. of Special Cr*l!«ctkjns &>W Title Box Series I Fol 5C Fo<. Title " LISP/360 REFERENCE MANUAL FOURTH EDITION # CAMPUS COMPUTER FACILITY STANFORD COMPUTATION CENTER STANFORD UNIVERSITY STANFORD, CALIFORNIA DOCUMENT NUMBER SCCO24 " ■ " PREFACE This manual is intended to provide the LISP 1.5 user with a reference manual for the LISP 1.5 interpreter, assembler, and compiler on the Campus Facility 360/67. It assumes that the reader has a working knowledge by of LISP 1.5 as described in the LISP_I.is_Primer Clark Weissman, and that the reader has a general knowledge of the operating environment of OS 360. Beginning users of LISP will find the sections The , Functions, LI SRZIi O_Syst em , Organiz ation_of_St orage tlSP_Job_Set-]i£» and t.tsp/360 System Messages Host helpful in obtaining a basic understanding of the LISP system. Other sections of the manual are intended for users desiring a more extensive knowledge of LISP. The particular implementation to which this reference manual is directed was started by Mr. J. Kent while he was at the University of Waterloo. It is modeled after his implemention of LISP 1.5 for the CDC 3600. Included in this edition is information on the use of the time-shared LISP system available on the 360/67 which was implemented by Mr. Robert Berns of the " Computer staff. Campus Facility " II TABLE OF CONTENTS Section PREFACE " TABLE OF CONTENTS xxx 1. THE LISP/360 SYSTEM 1 2. ORGANIZATION OF STORAGE 3 2.1 Free Cell Storage (FCS) 3 2.1.1 Atoms 5 2.1.2 Numbers 8 2.1.3 Object List 9 2.2 Push-down Stack (PDS) 9 2.3 System Functions 9 2.4 Binary Program Space (BPS) 9 W 2.5 Input/Output Buffers 9 10 3. -
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. -
Implementing a Vau-Based Language with Multiple Evaluation Strategies
Implementing a Vau-based Language With Multiple Evaluation Strategies Logan Kearsley Brigham Young University Introduction Vau expressions can be simply defined as functions which do not evaluate their argument expressions when called, but instead provide access to a reification of the calling environment to explicitly evaluate arguments later, and are a form of statically-scoped fexpr (Shutt, 2010). Control over when and if arguments are evaluated allows vau expressions to be used to simulate any evaluation strategy. Additionally, the ability to choose not to evaluate certain arguments to inspect the syntactic structure of unevaluated arguments allows vau expressions to simulate macros at run-time and to replace many syntactic constructs that otherwise have to be built-in to a language implementation. In principle, this allows for significant simplification of the interpreter for vau expressions; compared to McCarthy's original LISP definition (McCarthy, 1960), vau's eval function removes all references to built-in functions or syntactic forms, and alters function calls to skip argument evaluation and add an implicit env parameter (in real implementations, the name of the environment parameter is customizable in a function definition, rather than being a keyword built-in to the language). McCarthy's Eval Function Vau Eval Function (transformed from the original M-expressions into more familiar s-expressions) (define (eval e a) (define (eval e a) (cond (cond ((atom e) (assoc e a)) ((atom e) (assoc e a)) ((atom (car e)) ((atom (car e)) (cond (eval (cons (assoc (car e) a) ((eq (car e) 'quote) (cadr e)) (cdr e)) ((eq (car e) 'atom) (atom (eval (cadr e) a))) a)) ((eq (car e) 'eq) (eq (eval (cadr e) a) ((eq (caar e) 'vau) (eval (caddr e) a))) (eval (caddar e) ((eq (car e) 'car) (car (eval (cadr e) a))) (cons (cons (cadar e) 'env) ((eq (car e) 'cdr) (cdr (eval (cadr e) a))) (append (pair (cadar e) (cdr e)) ((eq (car e) 'cons) (cons (eval (cadr e) a) a)))))) (eval (caddr e) a))) ((eq (car e) 'cond) (evcon. -
Obstacles to Compilation of Rebol Programs
Obstacles to Compilation of Rebol Programs Viktor Pavlu TU Wien Institute of Computer Aided Automation, Computer Vision Lab A-1040 Vienna, Favoritenstr. 9/183-2, Austria [email protected] Abstract. Rebol’s syntax has no explicit delimiters around function arguments; all values in Rebol are first-class; Rebol uses fexprs as means of dynamic syntactic abstraction; Rebol thus combines the advantages of syntactic abstraction and a common language concept for both meta-program and object-program. All of the above are convenient attributes from a programmer’s point of view, yet at the same time pose severe challenges when striving to compile Rebol into reasonable code. An approach to compiling Rebol code that is still in its infancy is sketched, expected outcomes are presented. Keywords: first-class macros, dynamic syntactic abstraction, $vau calculus, fexpr, Ker- nel, Rebol 1 Introduction A meta-program is a program that can analyze (read), transform (read/write), or generate (write) another program, called the object-program. Static techniques for syntactic abstraction (macro systems, preprocessors) resolve all abstraction during compilation, so the expansion of abstractions incurs no cost at run-time. Static techniques are, however, conceptionally burdensome as they lead to staged systems with phases that are isolated from each other. In systems where different syntax is used for the phases (e. g., C++), it results in a multitude of programming languages following different sets of rules. In systems where the same syntax is shared between phases (e. g., Lisp), the separa- tion is even more unnatural: two syntactically largely identical-looking pieces of code cannot interact with each other as they are assigned to different execution stages. -
1960 1970 1980 1990 Japan California………………… UT IL in PA NJ NY Massachusetts………… Europe Lisp 1.5 TX
Japan UT IL PA NY Massachusetts………… Europe California………………… TX IN NJ Lisp 1.5 1960 1970 1980 1990 Direct Relationships Lisp 1.5 LISP Family Graph Lisp 1.5 LISP 1.5 Family Lisp 1.5 Basic PDP-1 LISP M-460 LISP 7090 LISP 1.5 BBN PDP-1 LISP 7094 LISP 1.5 Stanford PDP-1 LISP SDS-940 LISP Q-32 LISP PDP-6 LISP LISP 2 MLISP MIT PDP-1 LISP Stanford LISP 1.6 Cambridge LISP Standard LISP UCI-LISP MacLisp Family PDP-6 LISP MacLisp Multics MacLisp CMU SAIL MacLisp MacLisp VLISP Franz Lisp Machine Lisp LISP S-1 Lisp NIL Spice Lisp Zetalisp IBM Lisp Family 7090 LISP 1.5 Lisp360 Lisp370 Interlisp Illinois SAIL MacLisp VM LISP Interlisp Family SDS-940 LISP BBN-LISP Interlisp 370 Spaghetti stacks Interlisp LOOPS Common LOOPS Lisp Machines Spice Lisp Machine Lisp Interlisp Lisp (MIT CONS) (Xerox (BBN Jericho) (PERQ) (MIT CADR) Alto, Dorado, (LMI Lambda) Dolphin, Dandelion) Lisp Zetalisp TAO (3600) (ELIS) Machine Lisp (TI Explorer) Common Lisp Family APL APL\360 ECL Interlisp ARPA S-1 Lisp Scheme Meeting Spice at SRI, Lisp April 1991 PSL KCL NIL CLTL1 Zetalisp X3J13 CLTL2 CLOS ISLISP X3J13 Scheme Extended Family COMIT Algol 60 SNOBOL METEOR CONVERT Simula 67 Planner LOGO DAISY, Muddle Scheme 311, Microplanner Scheme 84 Conniver PLASMA (actors) Scheme Revised Scheme T 2 CLTL1 Revised Scheme Revised2 Scheme 3 CScheme Revised Scheme MacScheme PC Scheme Chez Scheme IEEE Revised4 Scheme Scheme Object-Oriented Influence Simula 67 Smalltalk-71 LOGO Smalltalk-72 CLU PLASMA (actors) Flavors Common Objects LOOPS ObjectLisp CommonLOOPS EuLisp New Flavors CLTL2 CLOS Dylan X3J13 ISLISP Lambda Calculus Church, 1941 λ Influence Lisp 1.5 Landin (SECD, ISWIM) Evans (PAL) Reynolds (Definitional Interpreters) Lisp370 Scheme HOPE ML Standard ML Standard ML of New Jersey Haskell FORTRAN Influence FORTRAN FLPL Lisp 1.5 S-1 Lisp Lisp Machine Lisp CLTL1 Revised3 Zetalisp Scheme X3J13 CLTL2 IEEE Scheme X3J13 John McCarthy Lisp 1.5 Danny Bobrow Richard Gabriel Guy Steele Dave Moon Jon L White. -
Lisp: Program Is Data
LISP: PROGRAM IS DATA A HISTORICAL PERSPECTIVE ON MACLISP Jon L White Laboratory for Computer Science, M.I.T.* ABSTRACT For over 10 years, MACLISP has supported a variety of projects at M.I.T.'s Artificial Intelligence Laboratory, and the Laboratory for Computer Science (formerly Project MAC). During this time, there has been a continuing development of the MACLISP system, spurred in great measure by the needs of MACSYMAdevelopment. Herein are reported, in amosiac, historical style, the major features of the system. For each feature discussed, an attempt will be made to mention the year of initial development, andthe names of persons or projectsprimarily responsible for requiring, needing, or suggestingsuch features. INTRODUCTION In 1964,Greenblatt and others participated in thecheck-out phase of DigitalEquipment Corporation's new computer, the PDP-6. This machine had a number of innovative features that were thought to be ideal for the development of a list processing system, and thus it was very appropriate that thefirst working program actually run on thePDP-6 was anancestor of thecurrent MACLISP. This earlyLISP was patterned after the existing PDP-1 LISP (see reference l), and was produced by using the text editor and a mini-assembler on the PDP-1. That first PDP-6 finally found its way into M.I.T.'s ProjectMAC for use by theArtificial lntelligence group (the A.1. grouplater became the M.I.T. Artificial Intelligence Laboratory, and Project MAC became the Laboratory for Computer Science). By 1968, the PDP-6 wasrunning the Incompatible Time-sharing system, and was soon supplanted by the PDP-IO.Today, the KL-I 0, anadvanced version of thePDP-10, supports a variety of time sharing systems, most of which are capable of running a MACLISP. -
Directly Reflective Meta-Programming
Directly Reflective Meta-Programming ∗ Aaron Stump Computer Science and Engineering Washington University in St. Louis St. Louis, Missouri, USA [email protected] Abstract Existing meta-programming languages operate on encodings of pro- grams as data. This paper presents a new meta-programming language, based on an untyped lambda calculus, in which structurally reflective pro- gramming is supported directly, without any encoding. The language fea- tures call-by-value and call-by-name lambda abstractions, as well as novel reflective features enabling the intensional manipulation of arbitrary pro- gram terms. The language is scope safe, in the sense that variables can neither be captured nor escape their scopes. The expressiveness of the language is demonstrated by showing how to implement quotation and evaluation operations, as proposed by Wand. The language's utility for meta-programming is further demonstrated through additional represen- tative examples. A prototype implementation is described and evaluated. Keywords: lambda calculus, reflection, meta-programming, Church en- coding, Mogensen-Scott encoding, Wand-style fexprs, alpha equivalence, language implementation. 1 Introduction This paper presents a new meta-programming language called Archon, in which programs can operate directly on other programs as data. Existing meta- programming languages suffer from defects such as encoding programs at too low a level of abstraction, or in a way that bloats the encoded program terms. Other issues include the possibility for variables either to be captured or escape their static scopes. Archon rectifies these defects by trading the complexity of the reflective encoding for additional programming constructs. We adopt ∗This work is supported by funding from the U.S. -
Lisp and Prolog Background
Lisp and Prolog Background Thank you to Prof. Roosen-Runge for the slides on background and history. Edited by Gunnar Gotshalks BH2-1 Lisp History •Lisp--invented (about 1958) by the logician and AI researcher John McCarthy •Widely used in for applications in AI every since •Used in industry » To develop expert systems & other AI applications » For Rapid Application Development (RAD) Edited by Gunnar Gotshalks BH2-2 Lisp Use •Lisp is used as an embedded language •Found inside applications like Emacs (MLisp) and AutoCAD (AutoLisp). » Emacs supports Lisp as a language for developing programs » As well as embedded language for controlling and customizing the editor itself Edited by Gunnar Gotshalks BH2-3 Lisp availability •On all major and many minor platforms. •Numerous free- and shareware versions. • Standard: Common Lisp Edited by Gunnar Gotshalks BH2-4 Prolog history •Prolog invented (≈1972) » Used at York in the by the AI researcher Student Information Alan Colmeraurer System to check applications for input errors •Widely used to develop » Early ideas developed expert systems & other at University of AI applications including Montreal; then natural language University of Marseilles processing Edited by Gunnar Gotshalks BH2-5 Prolog Use & Availability •Prolog rumored to be embedded in MS Office •On all major and many minor platforms •Several free and shareware versions •Standard: ‘Edinburgh-style’ Edited by Gunnar Gotshalks BH2-6 Survival Value McCarthy's Lisp versus Newell's IPL (Information Processing Language) » Both proposed » Both men pioneers languages at about the in AI and computer same time for symbolic science computing to be used in AI research Edited by Gunnar Gotshalks BH2-7 And the winner is ? McCarthy? Newell? Why? Edited by Gunnar Gotshalks BH2-8 & the winner is .. -
On Abstraction and the Expressive Power of Programming Languages
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Science of Computer Programming 21 (1993) 141-163 141 Elsevier On abstraction and the expressive power of programming languages John C. Mitchell* Departmentof Computer Science, Stanford University, Stanford, CA 94305, UsA Communicated by M. Hagiya Revised October 1992 Abstract Mitchell, J.C., On abstraction and the expressive power of programming languages, Science of Computer Programming 21 (1993) 141-163. This paper presents a tentative theory of programming language expressiveness based on reductions (language translations) that preserve observational equivalence. These are called “abstraction- preserving” reductions because of a connection with a definition of “abstraction” or “information- hiding” mechanisms. If there is an abstraction-preserving reduction from one language to another, then (essentially) every function on natural numbers that is definable in the first is also definable in the second. Moreover, an abstraction-preserving reduction must map every abstraction construct in the source language to a construct that hides analogous distinctions in the target language. Several examples and counterexamples to abstraction-preserving reductions are given. It is not known whether any language is universal with respect to abstraction-preserving reduction. 1. Introduction This paper presents a tentative theory of programming language expressiveness, originally described in unpublished notes that were circulated in 1986. The original motivation was to compare languages according to their ability to make sections of a program “abstract” by hiding some details of the internal workings of the code. This led to the definition of abstraction-preserving reductions, which are syntax-directed (homomorphic) language translations that preserve observational equivalence. -
' MACSYMA Users' Conference
' MACSYMA Users'Conference Held at University of California Berkeley, California July 27-29, 1977 I TECH LIBRARY KAFB, NY NASA CP-2012 Proceedings of the 1977 MACSYMA Users’ Conference Sponsored by Massachusetts Institute of Technology, University of California at Berkeley, NASA Langley Research Center and held at Berkeley, California July 27-29, 1977 Scientific and TechnicalInformation Office 1977 NATIONALAERONAUTICS AND SPACE ADMINISTRATION NA5A Washington, D.C. FOREWORD The technical programof the 1977 MACSPMA Users' Conference, held at Berkeley,California, from July 27 to July 29, 1977, consisted of the 45 contributedpapers reported in.this publicationand of a workshop.The work- shop was designed to promote an exchange of information between implementers and users of the MACSYMA computersystem and to help guide future developments. I The response to the call for papers has well exceeded the early estimates of the conference organizers; and the high quality and broad ra.ngeof topics of thepapers submitted has been most satisfying. A bibliography of papers concerned with the MACSYMA system is included at the endof this publication. We would like to thank the members of the programcommittee, the many referees, and the secretarial and technical staffs at the University of California at Berkeley and at the Laboratory for Computer Science, Massachusetts Instituteof Technology, for shepherding the many papersthrough the submission- to-publicationprocess. We are especiallyappreciative of theburden. carried by .V. Ellen Lewis of M. I. T. for serving as expert in document preparation from computer-readableto camera-ready copy for several papers. This conference originated as the result of an organizing session called by Joel Moses of M.I.T. -
CLISP - Conversational LISP
Session 25 Hardware and Software for Artificial Intelligence CLISP - Conversational LISP Warren Teitelman Xerox Palo Alto Research center Palo Alto, California 94304 Abstract CLISP is an attempt to make LISP programs The syntax for a conditional expression is easier to read and write by extending the correspondingly simple:* syntax of LISP to include infix operators, IF-THEN statements, FOR-DO-WHILE statements, Figure 2 and similar ALGOL-like constructs, without Syntax of a conditional Expression changing the structure or representation of the language. CLISP is implemented through <conditional expression> ::x LISP's error handling machinery, rather than (COND <clause> ... <clause>) by modifying the interpreter: when an <clause> :;= (<form> <form>) expression is encountered whose evaluation causes an error, the expression is scanned Note that there are no IF's, THEN's, for possible CLISP constructs, which are BEGIN's, END'S, or semi-colons. LISP avoids then converted to the equivalent LISP the problem of parsing the conditional expressions. Thus, users can freely expression, i.e., delimiting the individual intermix LISP and CLISP without having to clauses, and delimiting the predicates and distinguish which is which. Emphasis in the consequents within the clauses, by requiring design and development of CLISP has been on that each clause be a separate element in the system aspects of such a facility, with the conditional expression, namely a the goal in mind of producing a useful tool, sublist, of which the predicate is always not just another language. To this end, the first element, and the consequent the CLISP includes interactive error correction second element- As an example, let us and many 'Do-what-I-Mean* features.