Csc 520 Principles of Programming Languages 4: Scheme — History
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Hal Abelson Education: Princeton AB (Summa Cum Laude)
Hal Abelson Education: Princeton A.B. (summa cum laude) 1969 MIT Ph.D. (Mathematics) 1973 Professional Appointments: 1994–present MIT Class of 1922 Professor MIT 1991–present Full Professor of Computer Sci. and Eng. MIT 1982–1991 Associate Professor of Electrical Eng. and Computer Sci. MIT 1979–1982 Associate Professor, Dept. of EECS and Division for Study and Res. in Education MIT 1977–1979 Assistant Professor, Dept. of EECS and DSRE MIT 1974–1979 Lecturer, Dept. of Mathematics and DSRE MIT 1974–1979 Instructor, Dept. of Mathematics and DSRE MIT Selected publications relevant to this proposal: 1. “Transparent Accountable Data Mining: New Strategies for Privacy Protection,” with T. Berners- Lee, C. Hanson, J, Hendler, L. Kagal, D. McGuinness, G.J. Sussman, K. Waterman, and D. Weitzner. MIT CSAIL Technical Report, 2006-007, January 2006. 2. “Information Accountability,” with Daniel J. Weitzner, Tim Berners-Lee, Joan Feigenbaum, James Hendler, and Gerald Jay Sussman, MIT CSAIL Technical Report, 2007-034, June 2007. Available at http://hdl.handle.net/1721.1/37600. 3. “The Creation of OpenCourseWare at MIT,” J. Science Education and Technology, May, 2007. 4. Structure and Interpretation of Computer Programs, Hal Abelson, Gerald Jay Sussman and Julie Sussman, MIT Press and McGraw-Hill, 1985, (published translations in French, Polish, Chinese, Japanese, Spanish, and German). Second Edition, 1996. 5. “The Risks of Key Recovery, Key Escrow, and Trusted Third-Party Encryption,” with Ross Ander- son, Steven Bellovin, Josh Benaloh, Matt Blaze, Whitfield Diffie, John Gilmore, Peter Neumann, Ronald Rivest, Jeffrey Schiller, and Bruce Schneier, in World Wide Web Journal, vol. 2, no. -
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. -
Reflexive Interpreters 1 the Problem of Control
Reset reproduction of a Ph.D. thesis proposal submitted June 8, 1978 to the Massachusetts Institute of Technology Electrical Engineering and Computer Science Department. Reset in LaTeX by Jon Doyle, December 1995. c 1978, 1995 Jon Doyle. All rights reserved.. Current address: MIT Laboratory for Computer Science. Available via http://www.medg.lcs.mit.edu/doyle Reflexive Interpreters Jon Doyle [email protected] Massachusetts Institute of Technology, Artificial Intelligence Laboratory Cambridge, Massachusetts 02139, U.S.A. Abstract The goal of achieving powerful problem solving capabilities leads to the “advice taker” form of program and the associated problem of control. This proposal outlines an approach to this problem based on the construction of problem solvers with advanced self-knowledge and introspection capabilities. 1 The Problem of Control Self-reverence, self-knowledge, self-control, These three alone lead life to sovereign power. Alfred, Lord Tennyson, OEnone Know prudent cautious self-control is wisdom’s root. Robert Burns, A Bard’s Epitath The woman that deliberates is lost. Joseph Addison, Cato A major goal of Artificial Intelligence is to construct an “advice taker”,1 a program which can be told new knowledge and advised about how that knowledge may be useful. Many of the approaches towards this goal have proposed constructing additive formalisms for trans- mitting knowledge to the problem solver.2 In spite of considerable work along these lines, formalisms for advising problem solvers about the uses and properties of knowledge are rela- tively undeveloped. As a consequence, the nondeterminism resulting from the uncontrolled application of many independent pieces of knowledge leads to great inefficiencies. -
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. -
Getting Started Computing at the Al Lab by Christopher C. Stacy Abstract
MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLI..IGENCE LABORATORY WORKING PAPER 235 7 September 1982 Getting Started Computing at the Al Lab by Christopher C. Stacy Abstract This document describes the computing facilities at the M.I.T. Artificial Intelligence Laboratory, and explains how to get started using them. It is intended as an orientation document for newcomers to the lab, and will be updated by the author from time to time. A.I. Laboratory Working Papers are produced for internal circulation. and may contain information that is, for example, too preliminary or too detailed for formal publication. It is not intended that they should be considered papers to which reference can be made in the literature. a MASACHUSETS INSTITUTE OF TECHNOLOGY 1982 Getting Started Table of Contents Page i Table of Contents 1. Introduction 1 1.1. Lisp Machines 2 1.2. Timesharing 3 1.3. Other Computers 3 1.3.1. Field Engineering 3 1.3.2. Vision and Robotics 3 1.3.3. Music 4 1,3.4. Altos 4 1.4. Output Peripherals 4 1.5. Other Machines 5 1.6. Terminals 5 2. Networks 7 2.1. The ARPAnet 7 2.2. The Chaosnet 7 2.3. Services 8 2.3.1. TELNET/SUPDUP 8 2.3.2. FTP 8 2.4. Mail 9 2.4.1. Processing Mail 9 2.4.2. Ettiquette 9 2.5. Mailing Lists 10 2.5.1. BBoards 11 2.6. Finger/Inquire 11 2.7. TIPs and TACs 12 2.7.1. ARPAnet TAC 12 2.7.2. Chaosnet TIP 13 3. -
Fostering Learning in the Networked World: the Cyberlearning Opportunity and Challenge
Inquiries or comments on this report may be directed to the National Science Foundation by email to: [email protected] “Any opinions, findings, conclusions and recommendations expressed in this report are those of the Task Force and do not necessarily reflect or represent the views of the National Science Foundation.” Fostering Learning in the Networked World: The Cyberlearning Opportunity and Challenge A 21st Century Agenda for the National Science Foundation1 Report of the NSF Task Force on Cyberlearning June 24, 2008 Christine L. Borgman (Chair), Hal Abelson, Lee Dirks, Roberta Johnson, Kenneth R. Koedinger, Marcia C. Linn, Clifford A. Lynch, Diana G. Oblinger, Roy D. Pea, Katie Salen, Marshall S. Smith, Alex Szalay 1 We would like to acknowledge and give special thanks for the continued support and advice from National Science Foundation staff Daniel Atkins, Cora Marrett, Diana Rhoten, Barbara Olds, and Jim Colby. Andrew Lau of the University of California at Los Angeles provided exceptional help and great spirit in making the distributed work of our Task Force possible. Katherine Lawrence encapsulated the Task Force’s work in a carefully crafted Executive Summary. Fostering Learning in the Networked World: The Cyberlearning Opportunity and Challenge A 21st Century Agenda for the National Science Foundation Science Foundation the National for A 21st Century Agenda Report of the NSF Task Force on Cyberlearning Table of Contents Executive Summary...............................................................................................................................................................................................................................5 -
A Critique of Abelson and Sussman Why Calculating Is Better Than
A critique of Abelson and Sussman - or - Why calculating is better than scheming Philip Wadler Programming Research Group 11 Keble Road Oxford, OX1 3QD Abelson and Sussman is taught [Abelson and Sussman 1985a, b]. Instead of emphasizing a particular programming language, they emphasize standard engineering techniques as they apply to programming. Still, their textbook is intimately tied to the Scheme dialect of Lisp. I believe that the same approach used in their text, if applied to a language such as KRC or Miranda, would result in an even better introduction to programming as an engineering discipline. My belief has strengthened as my experience in teaching with Scheme and with KRC has increased. - This paper contrasts teaching in Scheme to teaching in KRC and Miranda, particularly with reference to Abelson and Sussman's text. Scheme is a "~dly-scoped dialect of Lisp [Steele and Sussman 19781; languages in a similar style are T [Rees and Adams 19821 and Common Lisp [Steele 19821. KRC is a functional language in an equational style [Turner 19811; its successor is Miranda [Turner 1985k languages in a similar style are SASL [Turner 1976, Richards 19841 LML [Augustsson 19841, and Orwell [Wadler 1984bl. (Only readers who know that KRC stands for "Kent Recursive Calculator" will have understood the title of this There are four language features absent in Scheme and present in KRC/Miranda that are important: 1. Pattern-matching. 2. A syntax close to traditional mathematical notation. 3. A static type discipline and user-defined types. 4. Lazy evaluation. KRC and SASL do not have a type discipline, so point 3 applies only to Miranda, Philip Wadhr Why Calculating is Better than Scheming 2 b LML,and Orwell. -
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 -
Knowledge Based Engineering: Between AI and CAD
Advanced Engineering Informatics 26 (2012) 159–179 Contents lists available at SciVerse ScienceDirect Advanced Engineering Informatics journal homepage: www.elsevier.com/locate/aei Knowledge based engineering: Between AI and CAD. Review of a language based technology to support engineering design ⇑ Gianfranco La Rocca Faculty of Aerospace Engineering, Delft University of Technology, Chair of Flight Performance and Propulsion, Kluyverweg 1, 2629HS Delft, The Netherlands article info abstract Article history: Knowledge based engineering (KBE) is a relatively young technology with an enormous potential for Available online 16 March 2012 engineering design applications. Unfortunately the amount of dedicated literature available to date is quite low and dispersed. This has not promoted the diffusion of KBE in the world of industry and acade- Keywords: mia, neither has it contributed to enhancing the level of understanding of its technological fundamentals. Knowledge based engineering The scope of this paper is to offer a broad technological review of KBE in the attempt to fill the current Knowledge engineering information gap. The artificial intelligence roots of KBE are briefly discussed and the main differences and Engineering design similarities with respect to classical knowledge based systems and modern general purpose CAD systems Generative design highlighted. The programming approach, which is a distinctive aspect of state-of-the-art KBE systems, is Knowledge based design Rule based design discussed in detail, to illustrate its effectiveness in capturing and re-using engineering knowledge to automate large portions of the design process. The evolution and trends of KBE systems are investigated and, to conclude, a list of recommendations and expectations for the KBE systems of the future is provided. -
IBM 1401 System Summary
File No. 1401-00 Form A24-1401-1 Systems Reference Library IBM 1401 System Summary This reference publication contains brief descriptions of the machine features, components, configurations, and special features. Also included is a section on pro grams and programming systems. Publications providing detailed information on sub jects discussed in this summary are listed in IB~I 1401 and 1460 Bibliography, Form A24-1495. Major Revision (September 1964) This publication, Form A24-1401-1, is a major revision of and obsoletes Form A24-1401-0. Significant changes have been made throughout the publication. Reprinted April 1966 Copies of this and other IBM publications can be obtained through IBM Branch Offices. Address comments concerning the content of this publication to IBM Product Publications, Endicott, New York 13764. Contents IBM 1401 System Summary . ........... 5 System Concepts . ................ 6 Card-Oriented System .... ......... 11 Physical Features. 11 Interleaving. .. .................................... 14 Data Flow.... ... ... ... ... .. ... ... .. ................... 14 Checking ................................................... 15 Word Mark.. ... ... ... ... ... ... .. ... ... ... ........... 15 Stored-Program Instructions. .................. 15 Operation Codes . .. 18 Editing. .. ............ 18 IBM 1401 Console ............................................ 19 IBM 1406 Storage Unit. ........................... 20 Magnetic-Tape-Oriented System . ........................... 22 Data Flow .................................................