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Latest Results from the Procedure Calling Test, Ackermann's Function
Latest results from the procedure calling test, Ackermann’s function B A WICHMANN National Physical Laboratory, Teddington, Middlesex Division of Information Technology and Computing March 1982 Abstract Ackermann’s function has been used to measure the procedure calling over- head in languages which support recursion. Two papers have been written on this which are reproduced1 in this report. Results from further measurements are in- cluded in this report together with comments on the data obtained and codings of the test in Ada and Basic. 1 INTRODUCTION In spite of the two publications on the use of Ackermann’s Function [1, 2] as a mea- sure of the procedure-calling efficiency of programming languages, there is still some interest in the topic. It is an easy test to perform and the large number of results ob- tained means that an implementation can be compared with many other systems. The purpose of this report is to provide a listing of all the results obtained to date and to show their relationship. Few modern languages do not provide recursion and hence the test is appropriate for measuring the overheads of procedure calls in most cases. Ackermann’s function is a small recursive function listed on page 2 of [1] in Al- gol 60. Although of no particular interest in itself, the function does perform other operations common to much systems programming (testing for zero, incrementing and decrementing integers). The function has two parameters M and N, the test being for (3, N) with N in the range 1 to 6. Like all tests, the interpretation of the results is not without difficulty. -
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Minimax estimation in regression and random censorship models Citation for published version (APA): Belitser, E. N. (2000). Minimax estimation in regression and random censorship models. (CWI tracts; Vol. 127). Centrum voor Wiskunde en Informatica. Document status and date: Published: 01/01/2000 Document Version: Publisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers) Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. -
Writing Cybersecurity Job Descriptions for the Greatest Impact
Writing Cybersecurity Job Descriptions for the Greatest Impact Keith T. Hall U.S. Department of Homeland Security Welcome Writing Cybersecurity Job Descriptions for the Greatest Impact Disclaimers and Caveats • Content Not Officially Adopted. The content of this briefing is mine personally and does not reflect any position or policy of the United States Government (USG) or of the Department of Homeland Security. • Note on Terminology. Will use USG terminology in this brief (but generally translatable towards Private Sector equivalents) • Job Description Usage. For the purposes of this presentation only, the Job Description for the Position Description (PD) is used synonymously with the Job Opportunity Announcement (JOA). Although there are potential differences, it is not material to the concepts presented today. 3 Key Definitions and Concepts (1 of 2) • What do you want the person to do? • Major Duties and Responsibilities. “A statement of the important, regular, and recurring duties and responsibilities assigned to the position” SOURCE: https://www.opm.gov/policy-data- oversight/classification-qualifications/classifying-general-schedule-positions/classifierhandbook.pdf • Major vs. Minor Duties. “Major duties are those that represent the primary reason for the position's existence, and which govern the qualification requirements. Typically, they occupy most of the employee's time. Minor duties generally occupy a small portion of time, are not the primary purpose for which the position was established, and do not determine qualification requirements” SOURCE: https://www.opm.gov/policy-data- oversight/classification-qualifications/classifying-general-schedule-positions/positionclassificationintro.pdf • Tasks. “Activities an employee performs on a regular basis in order to carry out the functions of the job.” SOURCE: https://www.opm.gov/policy-data-oversight/assessment-and-selection/job-analysis/job_analysis_presentation.pdf 4 Key Definitions and Concepts (2 of 2) • What do you want to see on resumes that qualifies them to do this work? • Competency. -
Comparative Programming Languages CM20253
We have briefly covered many aspects of language design And there are many more factors we could talk about in making choices of language The End There are many languages out there, both general purpose and specialist And there are many more factors we could talk about in making choices of language The End There are many languages out there, both general purpose and specialist We have briefly covered many aspects of language design The End There are many languages out there, both general purpose and specialist We have briefly covered many aspects of language design And there are many more factors we could talk about in making choices of language Often a single project can use several languages, each suited to its part of the project And then the interopability of languages becomes important For example, can you easily join together code written in Java and C? The End Or languages And then the interopability of languages becomes important For example, can you easily join together code written in Java and C? The End Or languages Often a single project can use several languages, each suited to its part of the project For example, can you easily join together code written in Java and C? The End Or languages Often a single project can use several languages, each suited to its part of the project And then the interopability of languages becomes important The End Or languages Often a single project can use several languages, each suited to its part of the project And then the interopability of languages becomes important For example, can you easily -
Compiler Construction
Compiler construction PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Sat, 10 Dec 2011 02:23:02 UTC Contents Articles Introduction 1 Compiler construction 1 Compiler 2 Interpreter 10 History of compiler writing 14 Lexical analysis 22 Lexical analysis 22 Regular expression 26 Regular expression examples 37 Finite-state machine 41 Preprocessor 51 Syntactic analysis 54 Parsing 54 Lookahead 58 Symbol table 61 Abstract syntax 63 Abstract syntax tree 64 Context-free grammar 65 Terminal and nonterminal symbols 77 Left recursion 79 Backus–Naur Form 83 Extended Backus–Naur Form 86 TBNF 91 Top-down parsing 91 Recursive descent parser 93 Tail recursive parser 98 Parsing expression grammar 100 LL parser 106 LR parser 114 Parsing table 123 Simple LR parser 125 Canonical LR parser 127 GLR parser 129 LALR parser 130 Recursive ascent parser 133 Parser combinator 140 Bottom-up parsing 143 Chomsky normal form 148 CYK algorithm 150 Simple precedence grammar 153 Simple precedence parser 154 Operator-precedence grammar 156 Operator-precedence parser 159 Shunting-yard algorithm 163 Chart parser 173 Earley parser 174 The lexer hack 178 Scannerless parsing 180 Semantic analysis 182 Attribute grammar 182 L-attributed grammar 184 LR-attributed grammar 185 S-attributed grammar 185 ECLR-attributed grammar 186 Intermediate language 186 Control flow graph 188 Basic block 190 Call graph 192 Data-flow analysis 195 Use-define chain 201 Live variable analysis 204 Reaching definition 206 Three address -
The History of the ALGOL Effort
Technische Universiteit Eindhoven Department of Mathematics and Computer Science The History of the ALGOL Effort by HT de Beer supervisors: C. Hemerik L.M.M. Royakkers Eindhoven, August 2006 Abstract This report studies the importancy of the ALGOL effort for computer science. Therefore the history of the ALGOL effort is told, starting with the compu- tational context of the 1950s when the ALGOL effort was initiated. Second, the development from IAL to ALGOL 60 and the role the BNF played in this development are discussed. Third, the translation of ALGOL 60 and the establishment of the scientific field of translator writing are treated. Finally, the period of ALGOL 60 maintenance and the subsequent period of creating a successor to ALGOL 60 are described. ii Preface This history on the ALGOL effort was written as a Master thesis in Com- puter Science and Engineering (Technische Informatica) at the Eindhoven University of Technology, the Netherlands. iii Contents Abstract ii Preface iii Contents iv 0 Introduction 1 0.0 On the sources used ........................ 2 0.1 My own perspective ........................ 3 0.2 The ALGOL effort: a definition .................. 4 0.3 Notes ................................ 4 1 Creation 5 1.0 The start of the ALGOL effort ................... 5 1.1 The need for a universal algorithmic language ........... 7 1.1.0 The American field of computing ............. 7 1.1.1 The European field of computing ............. 9 1.1.2 The difference between Europe and the USA and the need for universalism ...................... 11 1.2 Why was IAL chosen over other algorithmic languages? ..... 11 1.2.0 IT ............................ -
List of Programming Languages
List of programming languages The aim of this list of programming languages is to include all notable programming languages in existence, both those in current use and historical ones, in alphabetical order. Dialects of BASIC, esoteric programming languages, and markup languages are not included. 0–9ABCDEFGHIJKLMNOPQRSTUVWXYZ Contents: See also A A.NET ALGOL W A-0 System Alice A+ Alma-0 ABAP AmbientTalk ABC Amiga E ABC ALGOL AMOS ACC AMPL Accent AngelScript Ace DASL (Distributed Application Apache Pig latin Specification Language) Apex Action! APL ActionScript App Inventor for Android's visual block Actor language Ada AppleScript Adenine APT Agda Arc Agilent VEE ARexx Agora Argus AIMMS Assembly language Aldor AutoHotkey Alef AutoIt ALF AutoLISP / Visual LISP ALGOL 58 Averest ALGOL 60 AWK ALGOL 68 Axum B B BASIC Babbage Batch file (Windows/MS-DOS) Ballerina bc Bash BCPL BeanShell BlooP Bertrand Boo BETA Boomerang BLISS Bosque Blockly C C – ISO/IEC 9899 CLU C-- (C minus minus) CMS-2 C++ (C plus plus) – ISO/IEC 14882 COBOL – ISO/IEC 1989 C* CobolScript – COBOL Scripting language C# (C sharp) – ISO/IEC 23270 Cobra C/AL CoffeeScript Caché ObjectScript ColdFusion C Shell (csh) COMAL Caml Combined Programming Language (CPL) Cayenne COMIT CDuce Common Intermediate Language (CIL) Cecil Common Lisp (also known as CL) Cesil COMPASS Céu Component Pascal Ceylon Constraint Handling Rules (CHR) CFEngine COMTRAN Cg Cool Ch Coq Chapel Coral 66 Charm CorVision CHILL COWSEL CHIP-8 CPL chomski Cryptol ChucK Crystal Cilk Csound CL (IBM) Cuneiform Claire Curl -
Mathematical Software 5
Copyright © 1977, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. BIBLIOGRAPHY ON NUMERICAL SOFTWARE by Bo Einarsson Permanent affilation: FORSVARETS FORSKNINGSANSTALT (FOA) National Defence Research Institute Department 2/Proving Grounds Box 98, S-147 00 Tumba, Sweden Memorandum No. UCB/ERL M77/19 25 March 1977 » e - % ELECTRONICS RESEARCH LABORATORY College of Engineering University of California, Berkeley 94720 BIBLIOGRAPHY ON NUMERICAL SOFTWARE by Bo Einarsson Permanent affilation: FORSVARETS FORSKNINGSANSTALT (FOA) National Defence Research Institute Department 2/Proving Grounds Box 98, S-147 00 Tumba, Sweden Memorandum No. UCB/ERL M77/19 25 March 1977 BIBLIOGRAPHY ON NUMERICAL SOFTWARE by Bo Einarsson Permanent affilation: FO*RSVARETS FORSKNINGSANSTALT (FOA) National Defence Research Institute Department 2/Proving Grounds Box 98, S-147 00 Tumba, Sweden Memorandum No. UCB/ERL M77/19 25 March 1977 Abstract; This bibliography has been written at the request of the IFIP Working Group on Numerical Software (IFIP WG .2.5), and is intended to serve both members of the working group and others intent on improving numerical software. It has been divided into twenty-one different areas. Within each area the references are given in alphabetical order by the first author. -
Organization of Programming Languages
CMSC 330: Organization of Programming Languages A Brief History of Programming Languages CMSC330 Fall 2020 Babylon • Founded roughly 4000 years ago – Located near the Euphrates River, 56 miles south of Baghdad, Iraq • Historically influential in ancient western world • Cuneiform writing system, written on clay tablets – Some of those tablets survive to this day – Those from Hammurabi dynasty (1800-1600 BC) include mathematical calculations • (Also known for Code of Hammurabi, an early legal code) A Babylonian Algorithm A [rectangular] cistern. The height is 3, 20, and a volume of 27, 46, 40 has been excavated. The length exceeds the width by 50. You should take the reciprocal of the height, 3, 20, obtaining 18. Multiply this by the volume, 27, 46, 40, obtaining 8, 20. Take half of 50 and square it, obtaining 10, 25. Add 8, 20, and you get 8, 30, 25 The square root is 2, 55. Make two copies of this, adding [25] to the one and subtracting from the other. You find that 3, 20 [i.e., 3 1/3] is the length and 2, 30 [i.e., 2 1/2] is the width. This is the procedure. – Donald E. Knuth, Ancient Babylonian Algorithms, CACM July 1972 The number n, m represents n*(60k) + m*(60k-1) for some k More About Algorithms • Euclid’s Algorithm (Alexandria, Egypt, 300 BC) – Appeared in Elements • See http://aleph0.clarku.edu/~djoyce/elements/bookVII/propVII2.html – Computes gcd of two integers let rec gcd a b = if b = 0 then a else gcd b (a mod b) • Al-Khwarizmi (Baghdad, Iraq, 780-850 AD) – Al-Khwarizmi Concerning the Hindu Art of Reckoning – Translated into -
(Pdf) of the School of Squiggol: a History of the Bird−Meertens
The School of Squiggol A History of the Bird{Meertens Formalism Jeremy Gibbons University of Oxford Abstract. The Bird{Meertens Formalism, colloquially known as \Squig- gol", is a calculus for program transformation by equational reasoning in a function style, developed by Richard Bird and Lambert Meertens and other members of IFIP Working Group 2.1 for about two decades from the mid 1970s. One particular characteristic of the development of the Formalism is fluctuating emphasis on novel `squiggly' notation: sometimes favouring notational exploration in the quest for conciseness and precision, and sometimes reverting to simpler and more rigid nota- tional conventions in the interests of accessibility. This paper explores that historical ebb and flow. 1 Introduction In 1962, IFIP formed Working Group 2.1 to design a successor to the seminal algorithmic language Algol 60 [4]. WG2.1 eventually produced the specification for Algol 68 [63, 64]|a sophisticated language, presented using an elaborate two- level description notation, which received a mixed reception. WG2.1 continues to this day; technically, it retains responsibility for the Algol languages, but practi- cally it takes on a broader remit under the current name Algorithmic Languages and Calculi. Over the years, the Group has been through periods of focus and periods of diversity. But after the Algol 68 project, the period of sharpest focus covered the two decades from the mid 1970s to the early 1990s, when what later became known as the Bird{Meertens Formalism (BMF) drew the whole group together again. It is the story of those years that is the subject of this paper. -
Facing up to Faults Brian Randell
ReminiscencesReminiscences ofof WhetstoneWhetstone ALGOLALGOL Brian Randell DIKU, 30 September 2010 1 In Summer 1957 I had a vacation job at IBMIBM’s’s offices at 101 Wigmore Street, London These offices housed (and proudly displayed) an IBM 650 – their only computer in the UK DIKU, 30 September 2010 2 IBM 650 – a very successful and easy to program drumdrum-based-based decimal computer DIKU, 30 September 2010 3 In Autumn 1957 Mike Kelly and I arrived (from Imperial College) at English Electric Atomic Power Division, Whetstone, Leicestershire DIKU, 30 September 2010 4 Frank Whittle, inventor of the jet engine – whose Power Jet Company’sCompany’s factory was at Whetstone in WW2 DIKU, 30 September 2010 5 By the 1960s Whetstone was the site of EEEE’s’s Atomic Power Division (APD) and their Mechanical Engineering Laboratory (MEL) DIKU, 30 September 2010 6 In APD analogue computing was (at this time) ““king”king” – and the 15001500-amplifier-amplifier SATURN was being developed DIKU, 30 September 2010 7 We were hired to program nuclear reactor codes for APDAPD’s’s and MEL’sMEL’s first digital computer, a DEUCE DIKU, 30 September 2010 8 DEUCE was based on Pilot ACE, so inherited Alan TuringTuring’s’s cleverclever “optimum”“optimum” programming scheme DIKU, 30 September 2010 9 EASICODEEASICODE • DEUCE was difficult to program (well), and even more difficult to compile for. • Numerous interpreters were produced – and we invented a compromise scheme of “automatic programming” – EASICODE. • We nearly got fired because of it, but its success led to my becoming head of an Automatic Programming Section, with authority to “do something” for the upcoming KDF9. -
Evolution of the Major Programming Languages Genealogy of Common Languages Zuse’S Plankalkül
CHAPTER 2 Evolution of the Major Programming Languages Genealogy of Common Languages Zuse’s Plankalkül • Designed in 1945, but not published until 1972 • Never implemented • Advanced data structures • floating point, arrays, records • Invariants Plankalkül Syntax • An assignment statement to assign the expression A[4] + 1 to A[5] | A + 1 => A V | 4 5 (subscripts) S | 1.n 1.n (data types) Minimal Hardware Programming: Pseudocodes • What was wrong with using machine code? • Poor readability • Poor modifiability • Expression coding was tedious • Machine deficiencies--no indexing or floating point Pseudocodes: Short Code • Short Code developed by Mauchly in 1949 for BINAC computers • Expressions were coded, left to right • Example of operations: 01 – 06 abs value 1n (n+2)nd power 02 ) 07 + 2n (n+2)nd root 03 = 08 pause 4n if <= n 04 / 09 ( 58 print and tab Pseudocodes: Speedcoding • Speedcoding developed by Backus in 1954 for IBM 701 • Pseudo ops for arithmetic and math functions • Conditional and unconditional branching • Auto-increment registers for array access • Slow! • Only 700 words left for user program Pseudocodes: Related Systems • The UNIVAC Compiling System • Developed by a team led by Grace Hopper • Pseudocode expanded into machine code • David J. Wheeler (Cambridge University) • developed a method of using blocks of re-locatable addresses to solve the problem of absolute addressing IBM 704 and Fortran • Fortran 0: 1954 - not implemented • Fortran I:1957 • Designed for the new IBM 704, which had index registers and floating point