Dijkstra's Crisis
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Typology of Programming Languages E Early Languages E
Typology of programming languages e Early Languages E Typology of programming languages Early Languages 1 / 71 The Tower of Babel Typology of programming languages Early Languages 2 / 71 Table of Contents 1 Fortran 2 ALGOL 3 COBOL 4 The second wave 5 The finale Typology of programming languages Early Languages 3 / 71 IBM Mathematical Formula Translator system Fortran I, 1954-1956, IBM 704, a team led by John Backus. Typology of programming languages Early Languages 4 / 71 IBM 704 (1956) Typology of programming languages Early Languages 5 / 71 IBM Mathematical Formula Translator system The main goal is user satisfaction (economical interest) rather than academic. Compiled language. a single data structure : arrays comments arithmetics expressions DO loops subprograms and functions I/O machine independence Typology of programming languages Early Languages 6 / 71 FORTRAN’s success Because: programmers productivity easy to learn by IBM the audience was mainly scientific simplifications (e.g., I/O) Typology of programming languages Early Languages 7 / 71 FORTRAN I C FIND THE MEAN OF N NUMBERS AND THE NUMBER OF C VALUES GREATER THAN IT DIMENSION A(99) REAL MEAN READ(1,5)N 5 FORMAT(I2) READ(1,10)(A(I),I=1,N) 10 FORMAT(6F10.5) SUM=0.0 DO 15 I=1,N 15 SUM=SUM+A(I) MEAN=SUM/FLOAT(N) NUMBER=0 DO 20 I=1,N IF (A(I) .LE. MEAN) GOTO 20 NUMBER=NUMBER+1 20 CONTINUE WRITE (2,25) MEAN,NUMBER 25 FORMAT(11H MEAN = ,F10.5,5X,21H NUMBER SUP = ,I5) STOP TypologyEND of programming languages Early Languages 8 / 71 Fortran on Cards Typology of programming languages Early Languages 9 / 71 Fortrans Typology of programming languages Early Languages 10 / 71 Table of Contents 1 Fortran 2 ALGOL 3 COBOL 4 The second wave 5 The finale Typology of programming languages Early Languages 11 / 71 ALGOL, Demon Star, Beta Persei, 26 Persei Typology of programming languages Early Languages 12 / 71 ALGOL 58 Originally, IAL, International Algebraic Language. -
1 Oral History Interview with Brian Randell January 7, 2021 Via Zoom
Oral History Interview with Brian Randell January 7, 2021 Via Zoom Conducted by William Aspray Charles Babbage Institute 1 Abstract Brian Randell tells about his upbringing and his work at English Electric, IBM, and Newcastle University. The primary topic of the interview is his work in the history of computing. He discusses his discovery of the Irish computer pioneer Percy Ludgate, the preparation of his edited volume The Origins of Digital Computers, various lectures he has given on the history of computing, his PhD supervision of Martin Campbell-Kelly, the Computer History Museum, his contribution to the second edition of A Computer Perspective, and his involvement in making public the World War 2 Bletchley Park Colossus code- breaking machines, among other topics. This interview is part of a series of interviews on the early history of the history of computing. Keywords: English Electric, IBM, Newcastle University, Bletchley Park, Martin Campbell-Kelly, Computer History Museum, Jim Horning, Gwen Bell, Gordon Bell, Enigma machine, Curta (calculating device), Charles and Ray Eames, I. Bernard Cohen, Charles Babbage, Percy Ludgate. 2 Aspray: This is an interview on the 7th of January 2021 with Brian Randell. The interviewer is William Aspray. We’re doing this interview via Zoom. Brian, could you briefly talk about when and where you were born, a little bit about your growing up and your interests during that time, all the way through your formal education? Randell: Ok. I was born in 1936 in Cardiff, Wales. Went to school, high school, there. In retrospect, one of the things I missed out then was learning or being taught Welsh. -
COM 113 INTRO to COMPUTER PROGRAMMING Theory Book
1 [Type the document title] UNESCO -NIGERIA TECHNICAL & VOCATIONAL EDUCATION REVITALISATION PROJECT -PHASE II NATIONAL DIPLOMA IN COMPUTER TECHNOLOGY Computer Programming COURSE CODE: COM113 YEAR I - SE MESTER I THEORY Version 1: December 2008 2 [Type the document title] Table of Contents WEEK 1 Concept of programming ................................................................................................................ 6 Features of a good computer program ............................................................................................ 7 System Development Cycle ............................................................................................................ 9 WEEK 2 Concept of Algorithm ................................................................................................................... 11 Features of an Algorithm .............................................................................................................. 11 Methods of Representing Algorithm ............................................................................................ 11 Pseudo code .................................................................................................................................. 12 WEEK 3 English-like form .......................................................................................................................... 15 Flowchart ..................................................................................................................................... -
Kathleen Fisher Question: Interesting Answer in Algol
10/21/08 cs242! Lisp! Algol 60! Algol 68! Pascal! Kathleen Fisher! ML! Modula! Reading: “Concepts in Programming Languages” Chapter 5 except 5.4.5! Haskell! “Real World Haskell”, Chapter 0 and Chapter 1! (http://book.realworldhaskell.org/)! Many other languages:! Algol 58, Algol W, Euclid, EL1, Mesa (PARC), …! Thanks to John Mitchell and Simon Peyton Jones for some of these slides. ! Modula-2, Oberon, Modula-3 (DEC)! Basic Language of 1960! Simple imperative language + functions! Successful syntax, BNF -- used by many successors! real procedure average(A,n); statement oriented! real array A; integer n; No array bounds.! begin … end blocks (like C { … } )! begin if … then … else ! real sum; sum := 0; Recursive functions and stack storage allocation! for i = 1 step 1 until n Fewer ad hoc restrictions than Fortran! do General array references: A[ x + B[3] * y ] sum := sum + A[i]; Type discipline was improved by later languages! average := sum/n No “;” here.! Very influential but not widely used in US! end; Tony Hoare: “Here is a language so far ahead of its time that it was not only an improvement on its predecessors Set procedure return value by assignment.! but also on nearly all of its successors.”! Question:! Holes in type discipline! Is x := x equivalent to doing nothing?! Parameter types can be arrays, but! No array bounds! Interesting answer in Algol:! Parameter types can be procedures, but! No argument or return types for procedure parameters! integer procedure p; begin Problems with parameter passing mechanisms! -
Edsger Dijkstra: the Man Who Carried Computer Science on His Shoulders
INFERENCE / Vol. 5, No. 3 Edsger Dijkstra The Man Who Carried Computer Science on His Shoulders Krzysztof Apt s it turned out, the train I had taken from dsger dijkstra was born in Rotterdam in 1930. Nijmegen to Eindhoven arrived late. To make He described his father, at one time the president matters worse, I was then unable to find the right of the Dutch Chemical Society, as “an excellent Aoffice in the university building. When I eventually arrived Echemist,” and his mother as “a brilliant mathematician for my appointment, I was more than half an hour behind who had no job.”1 In 1948, Dijkstra achieved remarkable schedule. The professor completely ignored my profuse results when he completed secondary school at the famous apologies and proceeded to take a full hour for the meet- Erasmiaans Gymnasium in Rotterdam. His school diploma ing. It was the first time I met Edsger Wybe Dijkstra. shows that he earned the highest possible grade in no less At the time of our meeting in 1975, Dijkstra was 45 than six out of thirteen subjects. He then enrolled at the years old. The most prestigious award in computer sci- University of Leiden to study physics. ence, the ACM Turing Award, had been conferred on In September 1951, Dijkstra’s father suggested he attend him three years earlier. Almost twenty years his junior, I a three-week course on programming in Cambridge. It knew very little about the field—I had only learned what turned out to be an idea with far-reaching consequences. a flowchart was a couple of weeks earlier. -
A Politico-Social History of Algolt (With a Chronology in the Form of a Log Book)
A Politico-Social History of Algolt (With a Chronology in the Form of a Log Book) R. w. BEMER Introduction This is an admittedly fragmentary chronicle of events in the develop ment of the algorithmic language ALGOL. Nevertheless, it seems perti nent, while we await the advent of a technical and conceptual history, to outline the matrix of forces which shaped that history in a political and social sense. Perhaps the author's role is only that of recorder of visible events, rather than the complex interplay of ideas which have made ALGOL the force it is in the computational world. It is true, as Professor Ershov stated in his review of a draft of the present work, that "the reading of this history, rich in curious details, nevertheless does not enable the beginner to understand why ALGOL, with a history that would seem more disappointing than triumphant, changed the face of current programming". I can only state that the time scale and my own lesser competence do not allow the tracing of conceptual development in requisite detail. Books are sure to follow in this area, particularly one by Knuth. A further defect in the present work is the relatively lesser availability of European input to the log, although I could claim better access than many in the U.S.A. This is regrettable in view of the relatively stronger support given to ALGOL in Europe. Perhaps this calmer acceptance had the effect of reducing the number of significant entries for a log such as this. Following a brief view of the pattern of events come the entries of the chronology, or log, numbered for reference in the text. -
Advancing Automatic Programming: Regeneration, Meta-Circularity, and Two-Sided Interfaces
SOFTNET 2019 Advancing Automatic Programming: Regeneration, Meta-circularity, and Two-Sided Interfaces HERWIGMANNAERT NOVEMBER 2 7 , 2 0 1 9 • Automatic Programming • Toward Automatic Regeneration • Creating Meta-Circular Regeneration • On Meta-Programming Interfaces ADVANCING AUTOMATIC PROGRAMMING • Concluding Facts and Thoughts Overview • Questions and Discussion • Automatic Programming • Concept and Trends • Remaining Challenges • Toward Automatic Regeneration ADVANCING AUTOMATIC PROGRAMMING • Creating Meta-Circular Regeneration • On Meta-Programming Interfaces Overview • Concluding Facts and Thoughts • Questions and Discussion Automatic Programming • Automatic programming: • The act of automatically generating source code from a model or template • Sometimes distinguished from code generation, as performed by a compiler • Has always been a euphemism for programming in a higher-level language than was then available to the programmer [David Parnas] • Also referred to a generative or meta-programming • To manufacture software components in an automated way • It is as old as programming itself: System.out.println(“Hello world.”); System.out.println(“System.out.println(\“Hello world.\”);”); The Need for Automatic Programming • Goal is and has always been to improve programmer productivity • In general, to manufacture software components in an automated way, in the same way as automation in the industrial revolution, would: • Increase programming productivity • Consolidate programming knowledge • Eliminate human programming errors • Such -
Reinventing Education Based on Data and What Works • Since 1955
Reinventing Education Based on Data and What Works • Since 1955 Carnegie Mellon is reinventing education and the way we think about leveraging technology through its study of the science of learning – an interdisciplinary effort that we’ve been tackling for more than 50 years with both computer scientists and psychologists. CMU's educational technology innovations have inspired numerous startup companies, which are helping students to learn more effectively and efficiently. 1955: Allen Newell (TPR ’57) joins 1995: Prof. Kenneth R. Koedinger (HSS Prof. Herbert Simon’s research team as ’88,’90) and Anderson develop Practical a Ph.D. student. Algebra Tutor. The program pioneers a new form of computer-aided instruction for high 1956: CMU creates one of the world’s first school students based on cognitive tutors. university computation centers. With Prof. Alan Perlis (MCS ’42) as its head, it is a joint 1995: Prof. Jack Mostow (SCS ’81) undertaking of faculty from the business, develops Project LISTEN, an intelligent tutor Simon, Newell psychology, electrical engineering and that helps children learn to read. The National mathematics departments, and the Science Foundation included Project precursor to computer science. LISTEN’s speech recognition system as one of its top 50 innovations from 1950-2000. 1956: Simon creates a “thinking machine”—enacting a mental process 1995: The Center for Automated by breaking it down into its simplest Learning and Discovery is formed, led steps. Later that year, the term “artificial by Prof. Thomas M. Mitchell. intelligence” is coined by a small group Perlis including Newell and Simon. 1998: Spinoff company Carnegie Learning is founded by CMU scientists to expand 1956: Simon, Newell and J. -
The Advent of Recursion & Logic in Computer Science
The Advent of Recursion & Logic in Computer Science MSc Thesis (Afstudeerscriptie) written by Karel Van Oudheusden –alias Edgar G. Daylight (born October 21st, 1977 in Antwerpen, Belgium) under the supervision of Dr Gerard Alberts, and submitted to the Board of Examiners in partial fulfillment of the requirements for the degree of MSc in Logic at the Universiteit van Amsterdam. Date of the public defense: Members of the Thesis Committee: November 17, 2009 Dr Gerard Alberts Prof Dr Krzysztof Apt Prof Dr Dick de Jongh Prof Dr Benedikt Löwe Dr Elizabeth de Mol Dr Leen Torenvliet 1 “We are reaching the stage of development where each new gener- ation of participants is unaware both of their overall technological ancestry and the history of the development of their speciality, and have no past to build upon.” J.A.N. Lee in 1996 [73, p.54] “To many of our colleagues, history is only the study of an irrele- vant past, with no redeeming modern value –a subject without useful scholarship.” J.A.N. Lee [73, p.55] “[E]ven when we can't know the answers, it is important to see the questions. They too form part of our understanding. If you cannot answer them now, you can alert future historians to them.” M.S. Mahoney [76, p.832] “Only do what only you can do.” E.W. Dijkstra [103, p.9] 2 Abstract The history of computer science can be viewed from a number of disciplinary perspectives, ranging from electrical engineering to linguistics. As stressed by the historian Michael Mahoney, different `communities of computing' had their own views towards what could be accomplished with a programmable comput- ing machine. -
Turing's Influence on Programming — Book Extract from “The Dawn of Software Engineering: from Turing to Dijkstra”
Turing's Influence on Programming | Book extract from \The Dawn of Software Engineering: from Turing to Dijkstra" Edgar G. Daylight∗ Eindhoven University of Technology, The Netherlands [email protected] Abstract Turing's involvement with computer building was popularized in the 1970s and later. Most notable are the books by Brian Randell (1973), Andrew Hodges (1983), and Martin Davis (2000). A central question is whether John von Neumann was influenced by Turing's 1936 paper when he helped build the EDVAC machine, even though he never cited Turing's work. This question remains unsettled up till this day. As remarked by Charles Petzold, one standard history barely mentions Turing, while the other, written by a logician, makes Turing a key player. Contrast these observations then with the fact that Turing's 1936 paper was cited and heavily discussed in 1959 among computer programmers. In 1966, the first Turing award was given to a programmer, not a computer builder, as were several subsequent Turing awards. An historical investigation of Turing's influence on computing, presented here, shows that Turing's 1936 notion of universality became increasingly relevant among programmers during the 1950s. The central thesis of this paper states that Turing's in- fluence was felt more in programming after his death than in computer building during the 1940s. 1 Introduction Many people today are led to believe that Turing is the father of the computer, the father of our digital society, as also the following praise for Martin Davis's bestseller The Universal Computer: The Road from Leibniz to Turing1 suggests: At last, a book about the origin of the computer that goes to the heart of the story: the human struggle for logic and truth. -
Standards for Computer Aided Manufacturing
//? VCr ~ / Ct & AFML-TR-77-145 )R^ yc ' )f f.3 Standards for Computer Aided Manufacturing Office of Developmental Automation and Control Technology Institute for Computer Sciences and Technology National Bureau of Standards Washington, D.C. 20234 January 1977 Final Technical Report, March— December 1977 Distribution limited to U.S. Government agencies only; Test and Evaluation Data; Statement applied November 1976. Other requests for this document must be referred to AFML/LTC, Wright-Patterson AFB, Ohio 45433 Manufacturing Technology Division Air Force Materials Laboratory Wright-Patterson Air Force Base, Ohio 45433 . NOTICES When Government drawings, specifications, or other data are used for any purpose other than in connection with a definitely related Government procurement opera- tion, the United States Government thereby incurs no responsibility nor any obligation whatsoever; and the fact that the Government may have formulated, furnished, or in any way supplied the said drawing, specification, or other data, is not to be regarded by implication or otherwise as in any manner licensing the holder or any person or corporation, or conveying any rights or permission to manufacture, use, or sell any patented invention that may in any way be related thereto Copies of this report should not be returned unless return is required by security considerations, contractual obligations, or notice on a specified document This final report was submitted by the National Bureau of Standards under military interdepartmental procurement request FY1457-76 -00369 , "Manufacturing Methods Project on Standards for Computer Aided Manufacturing." This technical report has been reviewed and is approved for publication. FOR THE COMMANDER: DtiWJNlb L. -
Defining Computer Program Parts Under Learned Hand's Abstractions Test in Software Copyright Infringement Cases
Michigan Law Review Volume 91 Issue 3 1992 Defining Computer Program Parts Under Learned Hand's Abstractions Test in Software Copyright Infringement Cases John W.L. Ogilive University of Michigan Law School Follow this and additional works at: https://repository.law.umich.edu/mlr Part of the Computer Law Commons, Intellectual Property Law Commons, and the Judges Commons Recommended Citation John W. Ogilive, Defining Computer Program Parts Under Learned Hand's Abstractions Test in Software Copyright Infringement Cases, 91 MICH. L. REV. 526 (1992). Available at: https://repository.law.umich.edu/mlr/vol91/iss3/5 This Note is brought to you for free and open access by the Michigan Law Review at University of Michigan Law School Scholarship Repository. It has been accepted for inclusion in Michigan Law Review by an authorized editor of University of Michigan Law School Scholarship Repository. For more information, please contact [email protected]. NOTE Defining Computer Program Parts Under Learned Hand's Abstractions Test in Software Copyright Infringement Cases John W.L. Ogilvie INTRODUCTION Although computer programs enjoy copyright protection as pro tectable "literary works" under the federal copyright statute, 1 the case law governing software infringement is confused, inconsistent, and even unintelligible to those who must interpret it.2 A computer pro gram is often viewed as a collection of different parts, just as a book or play is seen as an amalgamation of plot, characters, and other familiar parts. However, different courts recognize vastly different computer program parts for copyright infringement purposes. 3 Much of the dis array in software copyright law stems from mutually incompatible and conclusory program part definitions that bear no relation to how a computer program is actually designed and created.