JAVA 277 James Gosling Power Or Simplicity 278 a Matter of Taste 281 Concurrency 285 Designing a Language 287 Feedback Loop 291
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Super Family
Super Family (Chaim Freedman, Petah Tikvah, Israel, September 2008) Yehoash (Heibish/Gevush) Super, born c.1760, died before 1831 in Latvia. He married unknown. I. Shmuel Super, born 1781,1 died by 1855 in Lutzin (now Ludza), Latvia,2 occupation alcohol trader. Appears in a list from 1837 of tax litigants who were alcohol traders in Lutzin. (1) He married Brokha ?, born 1781 in Lutzin (now Ludza), Latvia,3 died before 1831 in Lutzin (now Ludza), Latvia.3 (2) He married Elka ?, born 1794.4 A. Payka Super, (daughter of Shmuel Super and Brokha ?) born 1796/1798 in Lutzin (now Ludza), Latvia,3 died 1859 in Lutzin (now Ludza), Latvia.5 She married Yaakov-Keifman (Kivka) Super, born 1798,6,3 (son of Sholom "Super" ?) died 1874 in Lutzin (now Ludza), Latvia.7 Yaakov-Keifman: Oral tradition related by his descendants claims that Koppel's surname was actually Weinstock and that he married into the Super family. The name change was claimed to have taken place to evade military service. But this story seems to be invalid as all census records for him and his sons use the name Super. 1. Moshe Super, born 1828 in Lutzin (now Ludza), Latvia.8 He married Sara Goda ?, born 1828.8 a. Bentsion Super, born 1851 in Lutzin (now Ludza), Latvia.9 He married Khana ?, born 1851.9 b. Payka Super, born 1854 in Lutzin (now Ludza), Latvia.10 c. Rassa Super, born 1857 in Lutzin (now Ludza), Latvia.11 d. Riva Super, born 1860 in Lutzin (now Ludza), Latvia.12 e. Mushke Super, born 1865 in Lutzin (now Ludza), Latvia.13 f. -
CRN What It Was Doing and Why It Was Cognitive Systems Vision Doing It, and to Recover from Mental Continued on Page 8 Expanding the Pipeline
COMPUTING RESEARCH NEWS Computing Research Association, Celebrating 30 Years of Service to the Computing Research Community November 2002 Vol. 14/No. 5 DARPA’s New Cognitive Systems Vision By Ron Brachman and IPTO’s goal is to create a new to cope with systems both keep Zachary Lemnios generation of cognitive systems. growing. In order to make our systems more reliable, more secure, The impact of the Defense Mired in Moore’s Law? and more understandable, and to Advanced Research Projects Agency One benefit of such cognitive continue making substantial contri- (DARPA) on computing over the systems would be their help in butions to society, we need to do past 40 years has been profound. Led extracting us from a corner into something dramatically different. by the visionary J.C.R. Licklider and which our success seems to have his innovative successors in the painted us. The research that has The Promise of Cognitive Information Processing Techniques helped the industry follow Moore’s Systems Office (IPTO), DARPA initiated “Law” has created processors that are IPTO is attacking this problem by work that ultimately put personal remarkably fast and small, and data driving a fundamental change in computers on millions of desktops storage capabilities that are vast and computing systems. By giving systems Ron Brachman and made the global Internet a cheap. Unfortunately, these incred- more cognitive capabilities, we reality. In fact, the original IPTO, ible developments have cut two ways. believe we can make them more which lasted from 1962 to 1985, was While today’s computers are more responsible for their own behavior in large part responsible for estab- powerful than ever, we have been and maintenance. -
The AWK Programming Language
The Programming ~" ·. Language PolyAWK- The Toolbox Language· Auru:o V. AHo BRIAN W.I<ERNIGHAN PETER J. WEINBERGER TheAWK4 Programming~ Language TheAWI(. Programming~ Language ALFRED V. AHo BRIAN w. KERNIGHAN PETER J. WEINBERGER AT& T Bell Laboratories Murray Hill, New Jersey A ADDISON-WESLEY•• PUBLISHING COMPANY Reading, Massachusetts • Menlo Park, California • New York Don Mills, Ontario • Wokingham, England • Amsterdam • Bonn Sydney • Singapore • Tokyo • Madrid • Bogota Santiago • San Juan This book is in the Addison-Wesley Series in Computer Science Michael A. Harrison Consulting Editor Library of Congress Cataloging-in-Publication Data Aho, Alfred V. The AWK programming language. Includes index. I. AWK (Computer program language) I. Kernighan, Brian W. II. Weinberger, Peter J. III. Title. QA76.73.A95A35 1988 005.13'3 87-17566 ISBN 0-201-07981-X This book was typeset in Times Roman and Courier by the authors, using an Autologic APS-5 phototypesetter and a DEC VAX 8550 running the 9th Edition of the UNIX~ operating system. -~- ATs.T Copyright c 1988 by Bell Telephone Laboratories, Incorporated. 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, photocopy ing, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Published simultaneously in Canada. UNIX is a registered trademark of AT&T. DEFGHIJ-AL-898 PREFACE Computer users spend a lot of time doing simple, mechanical data manipula tion - changing the format of data, checking its validity, finding items with some property, adding up numbers, printing reports, and the like. -
APL Literature Review
APL Literature Review Roy E. Lowrance February 22, 2009 Contents 1 Falkoff and Iverson-1968: APL1 3 2 IBM-1994: APL2 8 2.1 APL2 Highlights . 8 2.2 APL2 Primitive Functions . 12 2.3 APL2 Operators . 18 2.4 APL2 Concurrency Features . 19 3 Dyalog-2008: Dyalog APL 20 4 Iverson-1987: Iverson's Dictionary for APL 21 5 APL Implementations 21 5.1 Saal and Weiss-1975: Static Analysis of APL1 Programs . 21 5.2 Breed and Lathwell-1968: Implementation of the Original APLn360 25 5.3 Falkoff and Orth-1979: A BNF Grammar for APL1 . 26 5.4 Girardo and Rollin-1987: Parsing APL with Yacc . 27 5.5 Tavera and other-1987, 1998: IL . 27 5.6 Brown-1995: Rationale for APL2 Syntax . 29 5.7 Abrams-1970: An APL Machine . 30 5.8 Guibas and Wyatt-1978: Optimizing Interpretation . 31 5.9 Weiss and Saal-1981: APL Syntax Analysis . 32 5.10 Weigang-1985: STSC's APL Compiler . 33 5.11 Ching-1986: APL/370 Compiler . 33 5.12 Ching and other-1989: APL370 Prototype Compiler . 34 5.13 Driscoll and Orth-1986: Compile APL2 to FORTRAN . 35 5.14 Grelck-1999: Compile APL to Single Assignment C . 36 6 Imbed APL in Other Languages 36 6.1 Burchfield and Lipovaca-2002: APL Arrays in Java . 36 7 Extensions to APL 37 7.1 Brown and Others-2000: Object-Oriented APL . 37 1 8 APL on Parallel Computers 38 8.1 Willhoft-1991: Most APL2 Primitives Can Be Parallelized . 38 8.2 Bernecky-1993: APL Can Be Parallelized . -
Understanding Code Forking in Open Source Software
EKONOMI OCH SAMHÄLLE ECONOMICS AND SOCIETY LINUS NYMAN – UNDERSTANDING CODE FORKING IN OPEN SOURCE SOFTWARE SOURCE OPEN IN FORKING CODE UNDERSTANDING – NYMAN LINUS UNDERSTANDING CODE FORKING IN OPEN SOURCE SOFTWARE AN EXAMINATION OF CODE FORKING, ITS EFFECT ON OPEN SOURCE SOFTWARE, AND HOW IT IS VIEWED AND PRACTICED BY DEVELOPERS LINUS NYMAN Ekonomi och samhälle Economics and Society Skrifter utgivna vid Svenska handelshögskolan Publications of the Hanken School of Economics Nr 287 Linus Nyman Understanding Code Forking in Open Source Software An examination of code forking, its effect on open source software, and how it is viewed and practiced by developers Helsinki 2015 < Understanding Code Forking in Open Source Software: An examination of code forking, its effect on open source software, and how it is viewed and practiced by developers Key words: Code forking, fork, open source software, free software © Hanken School of Economics & Linus Nyman, 2015 Linus Nyman Hanken School of Economics Information Systems Science, Department of Management and Organisation P.O.Box 479, 00101 Helsinki, Finland Hanken School of Economics ISBN 978-952-232-274-6 (printed) ISBN 978-952-232-275-3 (PDF) ISSN-L 0424-7256 ISSN 0424-7256 (printed) ISSN 2242-699X (PDF) Edita Prima Ltd, Helsinki 2015 i ACKNOWLEDGEMENTS There are many people who either helped make this book possible, or at the very least much more enjoyable to write. Firstly I would like to thank my pre-examiners Imed Hammouda and Björn Lundell for their insightful suggestions and remarks. Furthermore, I am grateful to Imed for also serving as my opponent. I would also like to express my sincere gratitude to Liikesivistysrahasto, the Hanken Foundation, the Wallenberg Foundation, and the Finnish Unix User Group. -
AB42.4.8 REMARKS on ABSTRACTO Leo Geurts Lambert
AB42 p. 56 AB42.4.8 REMARKS ON ABSTRACTO Leo Geurts Lambert Meertens Mathematlsch Centrum, Amsterdam I. ABSTRACTO LIVES If an author wants to describe an algorithm, he has to choose a vehicle to express himself. The "traditional" way is to give a description in some natural language, such as English. This vehicle has some obvious drawbacks. The most striking one is that of the sloppyness of natural languages. Hill [|] gives a convincing (and hilarious) exposition of ambiguities in ordinary English, quoting many examples from actual texts for instructional or similar purposes. The problem is often not so much that of syntactical ambiguities ("You would not recognise little Johnny now. He has grown another foot.") as that of unintended possible interpretations ("How many times can you take 6 away from a million? [...] I can do this as many times as you like."). A precise and unambiguous description may require lengthy and repetitious phrases. The more precise the description, the more difficult it is to understand for many, if not most, people. Another drawback of natural languages is the inadequacy of referencing or grouping methods (the latter for lack of non-parenthetical parentheses). This tends to give rise to GOTO-like instructions. With the advent of modern computing automata, programming languages have been invented to communicate algorithms to these computers. Programming languages are almost by definition precise and unambiguous. Nevertheless, they do not provide an ideal vehicle for presenting algorithms to human beings. The reason for this is that programming languages require the specification of many details which are relevant for the computing equipment but not for the algorithm proper. -
Sensory Information Processing (1 January 1976
Im plem enting Functional Program s Using M utable Abstract Data Types Ganesh C. Gopalakrishnan, Department of Computer Science, Univ. of Utah, Salt Lake City, Utah 84112 and Mandayam K. Srivas, Department of Computer Science, SUNY, Stony Brook, N Y 11794 W e study the following problem in this paper. Suppose we have a purely functional program that uses a set of abstract data types by invoking their operations. Is there an order of evaluation of the operations in the program that preserves the applicative order of evaluation semantics of the program even when the abstract data types behave as mutable modules. An abstract data type is mutable if one of its operations destructively updates the object rather than returning a new object as a result. This problem is important for several reasons. It can help eliminate unnecessary copying of data structure states. It supports a methodology in which one can program in a purely functional notation for purposes of verification and clarity, and then automatically transform the program into one in an object oriented, imperative language, such as CLU, A D A , Smalltalk, etc., that supports abstract data types. It allows accruing both the benefits of using abstract data types in programming, and allows modularity and verifiability. Keywords: Functional Program Implementation, Mutable Modules, Abstract Data Types, Syntactic Conditions. C o n t e n t s 1 Introduction 1 1.1 Related W o r k ........................................................................................................................... 2 1.2 Terminology, Assumptions, and Problem Statement............................................... 2 2 Syntactic Characterization of In Situ Evaluability 3 2.1 Syntactic Conditions for Straight-line Expressions.................................................. -
301669474.Pdf
Centrum voor Wiskunde en Informatica Centre for Mathematics and Computer Science L.G.L.T. Meertens Paramorphisms Computer Science/ Department of Algorithmics & Architecture Report CS-R9005 February Dib'I( I, 1fle.'1 Cootrumvoor ~', ;""'" ,,., tn!o.-1 Y.,'~• Am.,t,..-(,';if'! The Centre for Mathematics and Computer Science is a research institute of the Stichting Mathematisch Centrum, which was founded on February 11, 1946, as a nonprofit institution aiming at the promotion of mathematics, com puter science, and their applications. It is sponsored by the Dutch Govern ment through the Netherlands Organization for the Advancement of Research (N.W.O.). Copyright © Stichting Mathematisch Centrum, Amsterdam Paramorphisms Lambert Meertens CWI, Amsterdam, & University of Utrecht 0 Context This paper is a small contribution in the context of an ongoing effort directed towards the design of a calculus for constructing programs. Typically, the development of a program contains many parts that are quite standard, re quiring no invention and posing no intellectual challenge of any kind. If, as is indeed the aim, this calculus is to be usable for constructing programs by completely formal manipulation, a major concern is the amount of labour currently required for such non-challenging parts. On one level this concern can be addressed by building more or less spe cialised higher-level theories that can be drawn upon in a derivation, as is usual in almost all branches of mathematics, and good progress is being made here. This leaves us still with much low-level laboriousness, like admin istrative steps with little or no algorithmic content. Until now, the efforts in reducing the overhead in low-level formal labour have concentrated on using equational reasoning together with specialised notations to avoid the introduction of dummy variables, in particular for "canned induction" in the form of promotion properties for homomorphisms- which have turned out to be ubiquitous. -
Kenneth E. Iverson
Kenneth E. Iverson Born December 17, 1920, Camrose, Alberta, Canada; with Adin Falkoff, inventor and implementer of the programming language APL. Education: BA, mathematics, Queen's University at Kingston, Ont., 1950; MA, mathematics, Harvard University, 1951; PhD, applied mathematics, Harvard University, 1954. Professional Experience: assistant professor, Harvard University, 1955-1960; research division, IBM Corp., 1960-1980; I.P. Sharp Associates, 1980-1987. Honors and Awards: IBM Fellow, 1970; AFIPS Harry Goode Award, 1975; ACM Turing Award, 1979; IEEE Computer Pioneer Award, 1982; National Medal of Technology, 1991; member, National Academy of Engineering. Iverson has been one of those lucky individuals who has been able to start his career with a success and for over 35 years build on that success by adding to it, enhancing it, and seeing it develop into a successful commercial property. His book A Programming Language set the stage for a concept whose peculiar character set would have appeared to eliminate it from consideration for implementation on any computer. Adin Falkoff is credited by Iverson for picking the name APL for the programming language implementation, and the introduction of the IBM “golf-ball” typewriter, with the replacement typehead, which provided the character set to represent programs. The programming language became the language of enthusiasts (some would say fanatics) and the challenge of minimalists to contain as much processing as possible within one line of code. APL has outlived many other languages and its enthusiasts range from elementary school students to research scientists. BIBLIOGRAPHY Biographical Falkoff, Adin D., and Kenneth E. Iverson, “The Evolution of APL,” in Wexelblat, Richard L., ed., History of Programming Languages, Academic Press, New York, 1981, Chapter 14. -
Understanding Programming Languages
Understanding Programming Languages M. Ben-Ari Weizmann Institute of Science Originally published by John Wiley & Sons, Chichester, 1996. Copyright °c 2006 by M. Ben-Ari. You may download, display and print one copy for your personal use in non-commercial academic research and teaching. Instructors in non-commerical academic institutions may make one copy for each student in his/her class. All other rights reserved. In particular, posting this document on web sites is prohibited without the express permission of the author. Contents Preface xi I Introduction to Programming Languages 1 1 What Are Programming Languages? 2 1.1 The wrong question . 2 1.2 Imperative languages . 4 1.3 Data-oriented languages . 7 1.4 Object-oriented languages . 11 1.5 Non-imperative languages . 12 1.6 Standardization . 13 1.7 Computer architecture . 13 1.8 * Computability . 16 1.9 Exercises . 17 2 Elements of Programming Languages 18 2.1 Syntax . 18 2.2 * Semantics . 20 2.3 Data . 21 2.4 The assignment statement . 22 2.5 Type checking . 23 2.6 Control statements . 24 2.7 Subprograms . 24 2.8 Modules . 25 2.9 Exercises . 26 v Contents vi 3 Programming Environments 27 3.1 Editor . 28 3.2 Compiler . 28 3.3 Librarian . 30 3.4 Linker . 31 3.5 Loader . 32 3.6 Debugger . 32 3.7 Profiler . 33 3.8 Testing tools . 33 3.9 Configuration tools . 34 3.10 Interpreters . 34 3.11 The Java model . 35 3.12 Exercises . 37 II Essential Concepts 38 4 Elementary Data Types 39 4.1 Integer types . -
CWI Scanprofile/PDF/300
Centrum voor Wiskunde en lnformatica Centre for Mathematics and Computer Science L.G.L.T. Meertens, S. Pemberton An implementation of the B programming language Department of Computer Science Note CS-N8406 June Biblioiiie.:;I( ~'~'l'i't'Hm.n<' Wi~f.i;r;de- c11 !nform;:,;i:i.C<a - Ams1errJar11 AN IMPLEMENTATION OF THE B PROGRAMMING LANGUAGE L.G.L.T. MEERTENS, S. PEMBERTON CentPe foP Mathematics and ComputeP Science~ AmstePdam Bis a new programming language designed for personal computing. We describe some of the decisions taken in implementing the language, and the problems involved. Note: B is a working title until the language is finally frozen. Then it will acquire its definitive name. The language is entirely unrelated to the predecessor of C. A version of this paper will appear in the proceedings of the Washington USENIX Conference (January 1984). 1982 CR CATEGORIES: 69D44. KEY WORDS & PHRASES: programming language implementation, progrannning envi ronments, B. Note CS-N8406 Centre f~r Mathematics and Computer Science P.O. Box 4079, 1009 AB Amsterdam, The Netherlands I The programming language B B is a programming language being designed and implemented at the CWI. It was originally started in 1975 in an attempt to design a language for beginners as a suitable replacement for BASIC. While the emphasis of the project has in the intervening years shifted from "beginners" to "personal computing", the main design objectives have remained the same: · • simplicity; • suitability for conversational use; • availability of tools for structured programming. The design of the language has proceeded iteratively, and the language as it now stands is the third iteration of this process. -
A Development of APL2 Syntax
A development by James A. Brown of APL2 syntax This paper develops the rules governing the When language extensions are proposed we find that the writing of APL2 expressions and discusses the familiar rules do not cover all cases. For example, A PL 1 principles that motivated design decisions. has the concept of an operator (for example, /) applying to a function (for example, +) and producing a new function (called summation). In APL 2 operators are generalized so 1. introduction that they can apply to all functions—including those IBM has numerous products which follow the IBM internal produced by other operators. Therefore a syntactic decision standard for 4PL {VSAPL, APLSV, PC APL, SlOO has to be made about the meaning of a statement like A PL). In this paper this level of the A PL language is referred to as A PL 1. + .X/ APL2 is based on this writer's Ph.D. thesis [1], the array theory of Trenchard More [2], and most of all on APLl. It (where " . " is the matrix product operator). This could incorporates extensions to data structures, to primitive mean either operations, and to syntax. Those wishing a complete ( + .x)/or + .(x/) description of A PL 2 may refer to the A PL 2 publications library listed in the general references. The only extensions Operators are extended so that they take arrays as covered here are those which have an effect on the syntax of operands. Therefore, if "Z)OP" is a dyadic operator taking the language and those implied by the simplifications of an array right operand, syntax.