Simply Scheme : Introducing Computer Science / Brian Harvey, Matthew Wright; Foreword by Harold Abelson.—2Nd Ed
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Dictionary Users Do Look up Frequent Words. a Logfile Analysis
Erschienen in: Müller-Spitzer, Carolin (Hrsg.): Using Online Dictionaries. Berlin/ Boston: de Gruyter, 2014. (Lexicographica: Series Maior 145), S. 229-249. Alexander Koplenig, Peter Meyer, Carolin Müller-Spitzer Dictionary users do look up frequent words. A logfile analysis Abstract: In this paper, we use the 2012 log files of two German online dictionaries (Digital Dictionary of the German Language1 and the German Version of Wiktionary) and the 100,000 most frequent words in the Mannheim German Reference Corpus from 2009 to answer the question of whether dictionary users really do look up fre- quent words, first asked by de Schryver et al. (2006). By using an approach to the comparison of log files and corpus data which is completely different from that of the aforementioned authors, we provide empirical evidence that indicates - contra - ry to the results of de Schryver et al. and Verlinde/Binon (2010) - that the corpus frequency of a word can indeed be an important factor in determining what online dictionary users look up. Finally, we incorporate word dass Information readily available in Wiktionary into our analysis to improve our results considerably. Keywords: log file, frequency, corpus, headword list, monolingual dictionary, multi- lingual dictionary Alexander Koplenig: Institut für Deutsche Sprache, R 5, 6-13, 68161 Mannheim, +49-(0)621-1581- 435, [email protected] Peter Meyer: Institut für Deutsche Sprache, R 5, 6-13, 68161 Mannheim, +49-(0)621-1581-427, [email protected] Carolin Müller-Spitzer: Institut für Deutsche Sprache, R 5, 6-13, 68161 Mannheim, +49-(0)621-1581- 429, [email protected] Introduction We would like to Start this chapter by asking one of the most fundamental questions for any general lexicographical endeavour to describe the words of one (or more) language(s): which words should be included in a dictionary? At first glance, the answer seems rather simple (especially when the primary objective is to describe a language as completely as possible): it would be best to include every word in the dictionary. -
Design Principles Behind Beauty and Joy of Computing
Paper Session: CS0 SIGCSE ’20, March 11–14, 2020, Portland, OR, USA Design Principles behind Beauty and Joy of Computing Paul Goldenberg June Mark Brian Harvey Al Cuoco Mary Fries EDC EDC UCB EDC EDC Waltham, MA, USA Waltham, MA, USA Berkeley, CA, USA Waltham, MA, USA Waltham, MA, USA [email protected] [email protected] [email protected] [email protected] [email protected] ABSTRACT Technical Symposium on Computer Science Education (SIGCSE’20), March 11–14, 2020, Portland, OR, USA. ACM, NewYork, NY, USA, 7 pages. ACM, This paper shares the design principles of one Advanced Placement New York, NY, USA, 7 pages https://doi.org/10.1145/3328778.3366794 Computer Science Principles (AP CSP) course, Beauty and Joy of Computing (BJC), both for schools considering curriculum, and for 1 Introduction developers in this still-new field. BJC students not only learn about The National Science Foundation (NSF) and College Board (CB) in- CS, but do some and analyze its social implications; we feel that the troduced the Advanced Placement Computer Science Principles (AP job of enticing students into the field isn’t complete until students CSP) course to broaden participation in CS by appealing to high find programming, itself, something they enjoy and know they can school students who didn’t see CS as an inviting option—especially do, and its key ideas accessible. Students must feel invited to use female, black, and Latinx students who have been typically un- their own creativity and logic, and enjoy the power of their logic derrepresented in computing. The AP CSP course was the center- and the beauty and elegance of the code by which they express it. -
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. -
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. -
BERKELEY LOGO 6.1 Berkeley Logo User Manual
BERKELEY LOGO 6.1 Berkeley Logo User Manual Brian Harvey i Short Contents 1 Introduction :::::::::::::::::::::::::::::::::::::::::: 1 2 Data Structure Primitives::::::::::::::::::::::::::::::: 9 3 Communication :::::::::::::::::::::::::::::::::::::: 19 4 Arithmetic :::::::::::::::::::::::::::::::::::::::::: 29 5 Logical Operations ::::::::::::::::::::::::::::::::::: 35 6 Graphics:::::::::::::::::::::::::::::::::::::::::::: 37 7 Workspace Management ::::::::::::::::::::::::::::::: 49 8 Control Structures :::::::::::::::::::::::::::::::::::: 67 9 Macros ::::::::::::::::::::::::::::::::::::::::::::: 83 10 Error Processing ::::::::::::::::::::::::::::::::::::: 87 11 Special Variables ::::::::::::::::::::::::::::::::::::: 89 12 Internationalization ::::::::::::::::::::::::::::::::::: 93 INDEX :::::::::::::::::::::::::::::::::::::::::::::::: 97 iii Table of Contents 1 Introduction ::::::::::::::::::::::::::::::::::::: 1 1.1 Overview ::::::::::::::::::::::::::::::::::::::::::::::::::::::: 1 1.2 Getter/Setter Variable Syntax :::::::::::::::::::::::::::::::::: 2 1.3 Entering and Leaving Logo ::::::::::::::::::::::::::::::::::::: 5 1.4 Tokenization:::::::::::::::::::::::::::::::::::::::::::::::::::: 6 2 Data Structure Primitives :::::::::::::::::::::: 9 2.1 Constructors ::::::::::::::::::::::::::::::::::::::::::::::::::: 9 word ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 9 list ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 9 sentence :::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 9 fput :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: -
The Types, Roles, and Practices of Documentation in Data Analytics Open Source Software Libraries
Computer Supported Cooperative Work (CSCW) https://doi.org/10.1007/s10606-018-9333-1 © The Author(s) 2018 The Types, Roles, and Practices of Documentation in Data Analytics Open Source Software Libraries A Collaborative Ethnography of Documentation Work R. Stuart Geiger1 , Nelle Varoquaux1,2 , Charlotte Mazel-Cabasse1 & Chris Holdgraf1,3 1Berkeley Institute for Data Science, University of California, Berkeley, 190 Doe Library, Berkeley, CA, 94730, USA (E-mail: [email protected]); 2Department of Statistics, Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA, USA; 3Berkeley Institute for Data Science, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA Abstract. Computational research and data analytics increasingly relies on complex ecosystems of open source software (OSS) “libraries” – curated collections of reusable code that programmers import to perform a specific task. Software documentation for these libraries is crucial in helping programmers/analysts know what libraries are available and how to use them. Yet documentation for open source software libraries is widely considered low-quality. This article is a collaboration between CSCW researchers and contributors to data analytics OSS libraries, based on ethnographic fieldwork and qualitative interviews. We examine several issues around the formats, practices, and challenges around documentation in these largely volunteer-based projects. There are many dif- ferent kinds and formats of documentation that exist around such libraries, which play a variety of educational, promotional, and organizational roles. The work behind documentation is similarly multifaceted, including writing, reviewing, maintaining, and organizing documentation. Different aspects of documentation work require contributors to have different sets of skills and overcome various social and technical barriers. -
Alan M. Turing – Simplification in Intelligent Computing Theory and Algorithms”
“Alan Turing Centenary Year - India Celebrations” 3-Day Faculty Development Program on “Alan M. Turing – Simplification in Intelligent Computing Theory and Algorithms” Organized by Foundation for Advancement of Education and Research In association with Computer Society of India - Division II [Software] NASSCOM, IFIP TC - 1 & TC -2, ACM India Council Co-sponsored by P.E.S Institute of Technology Venue PES Institute of Technology, Hoskerehalli, Bangalore Date : 18 - 20 December 2012 Compiled by : Prof. K. Rajanikanth Trustee, FAER “Alan Turing Centenary Year - India Celebrations” 3-Day Faculty Development Program on “Alan M. Turing – Simplification in Intelligent Computing Theory and Algorithms” Organized by Foundation for Advancement of Education and Research In association with Computer Society of India - Division II [Software], NASSCOM, IFIP TC - 1 & TC -2, ACM India Council Co-sponsored by P.E.S Institute of Technology December 18 – 20, 2012 Compiled by : Prof. K. Rajanikanth Trustee, FAER Foundation for Advancement of Education and Research G5, Swiss Complex, 33, Race Course Road, Bangalore - 560001 E-mail: [email protected] Website: www.faer.ac.in PREFACE Alan Mathison Turing was born on June 23rd 1912 in Paddington, London. Alan Turing was a brilliant original thinker. He made original and lasting contributions to several fields, from theoretical computer science to artificial intelligence, cryptography, biology, philosophy etc. He is generally considered as the father of theoretical computer science and artificial intelligence. His brilliant career came to a tragic and untimely end in June 1954. In 1945 Turing was awarded the O.B.E. for his vital contribution to the war effort. In 1951 Turing was elected a Fellow of the Royal Society. -
PROWORD (Procedure WORD) There Are Many Users of Prowords
PROWORD (PROcedure WORD) There are many users of ProWords, Armed Forces, Aviation, Commercial & Recreational boat traffic & Amateur Radio In addition to the obvious list of environments you will find “codes”, that are used to convey special meanings, in private (business) nets or Policing (10-? codes). The following is a list of sources that have been used . This list is not all encompassing but comprises a list of prowords that will be understood by most of the radio operators you will encounter. Be flexible when DX-ing. English-Canadian may not be their first language. The goal is to communicate. Source Documents 1. Generally I like the US Coastguard Radiotelephone Handbook Appendix B https://www.dhs.gov/sites/default/files/publications/ CGTTP_6-01_1A_Radiotelephone_Handbook-%20508%20compliant%20v2.pdf 2. The RAC-ARES Operations Training manual is “reasonable” but contains prowords with duplicate meanings. http://wp.rac.ca/wp-content/uploads/files/ares/ ARES%20Complete_manual_revised%20Aug%202015.pdf 3. Wikipedia https://en.wikipedia.org/wiki/Procedure_word 4. Maritime Mobile Service Network Has some great examples http://www.mmsn.org/about-us/prowords.html 5. International Telecommunication Union - A valuable document https://www.itu.int/en/ITU-D/Emergency-Telecommunications/Documents/ET- OnlineToolkit/tools/ 019%20A%20Guide%20To%20Radio%20Communications%20Standards%20For %20Emergency%20Responders.pdf ACKNOWLEDGE - Let me know you have received and understood this message AFFIRMATIVE/YES - Permission granted, or I agree ALL STATIONS - This message is for all stations BREAK - I hereby indicate the separation between portions of the message CONFIRM - My version is ... is that correct? CORRECTION or WRONG - An error has been made in this transmission (message indicated). -
What I Wish I Knew When Learning Haskell
What I Wish I Knew When Learning Haskell Stephen Diehl 2 Version This is the fifth major draft of this document since 2009. All versions of this text are freely available onmywebsite: 1. HTML Version http://dev.stephendiehl.com/hask/index.html 2. PDF Version http://dev.stephendiehl.com/hask/tutorial.pdf 3. EPUB Version http://dev.stephendiehl.com/hask/tutorial.epub 4. Kindle Version http://dev.stephendiehl.com/hask/tutorial.mobi Pull requests are always accepted for fixes and additional content. The only way this document will stayupto date and accurate through the kindness of readers like you and community patches and pull requests on Github. https://github.com/sdiehl/wiwinwlh Publish Date: March 3, 2020 Git Commit: 77482103ff953a8f189a050c4271919846a56612 Author This text is authored by Stephen Diehl. 1. Web: www.stephendiehl.com 2. Twitter: https://twitter.com/smdiehl 3. Github: https://github.com/sdiehl Special thanks to Erik Aker for copyediting assistance. Copyright © 20092020 Stephen Diehl This code included in the text is dedicated to the public domain. You can copy, modify, distribute and perform thecode, even for commercial purposes, all without asking permission. You may distribute this text in its full form freely, but may not reauthor or sublicense this work. Any reproductions of major portions of the text must include attribution. The software is provided ”as is”, without warranty of any kind, express or implied, including But not limitedtothe warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authorsor copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, Arising from, out of or in connection with the software or the use or other dealings in the software. -
Not All Patterns, but Enough
Not All Patterns, But Enough Neil Mitchell, Colin Runciman York University Catch An Example • Is the following code safe?* risers :: Ord α→[α] → [[α]] risers [] = [] risers [x] = [[x]] risers (x:y:etc) = if x ≤ y then (x:s) : ss else [x] : (s : ss) where s:ss = risers (y : etc) > risers “Haskell” = [“Has”,“k”,“ell”] * Only people who haven’t seen this example in the paper! Using Catch > catch risers.hs Incomplete pattern on line 6 Program is safe • Catch is the associated implementation • Catch has proven the program is safe • Without any annotations The Pattern-Matching problem • Will a program crash when run? • May call error directly: error “doh!” • May call error indirectly: head [] • Partial pattern match: case False of True → 1 • GHC can warn on partial patterns • Catch conservatively checks a program will not crash at runtime • Even in the presence of partial patterns How Catch works First convert Haskell to first-order Core, using Yhc and Firstify Checker Exact Operates on first-order (ignoring laziness) Core language 3 constraint operators Constraint Language Conservative Describes a (possibly infinite) set of values Can replace constraint language Checker Terms • A constraint describes a set of values • x is a (:)-constructed value • A precondition is a constraint on arguments • In head x, x must be (:)-constructed • An entailment is a constraint on arguments to ensure a constraint on the result • If x is (:)-constructed, null x is False Checker Types • Opaque constraint type • data Constraint = … • Does an expression satisfy -
Haddock User Guide I
Haddock User Guide i Haddock User Guide Haddock User Guide ii Copyright © 2004 Simon Marlow Haddock User Guide iii COLLABORATORS TITLE : Haddock User Guide ACTION NAME DATE SIGNATURE WRITTEN BY Simon Marlow 2004-08-02 REVISION HISTORY NUMBER DATE DESCRIPTION NAME Haddock User Guide iv Contents 1 Introduction 1 1.1 Obtaining Haddock . .1 1.2 License . .2 1.3 Acknowledgements . .2 2 Invoking Haddock 3 2.1 Using literate or pre-processed source . .6 3 Documentation and Markup 7 3.1 Documenting a top-level declaration . .7 3.2 Documenting parts of a declaration . .8 3.2.1 Class methods . .8 3.2.2 Constructors and record fields . .8 3.2.3 Function arguments . .9 3.3 The module description . .9 3.4 Controlling the documentation structure . .9 3.4.1 Re-exporting an entire module . 10 3.4.2 Omitting the export list . 10 3.5 Named chunks of documentation . 11 3.6 Hyperlinking and re-exported entities . 11 3.7 Module Attributes . 12 3.8 Markup . 12 3.8.1 Paragraphs . 12 3.8.2 Special characters . 12 3.8.3 Character references . 13 3.8.4 Code Blocks . 13 3.8.5 Hyperlinked Identifiers . 13 3.8.6 Emphasis and Monospaced text . 13 3.8.7 Linking to modules . 14 3.8.8 Itemized and Enumerated lists . 14 3.8.9 Definition lists . 14 3.8.10 URLs . 14 3.8.11 Anchors . 14 Haddock User Guide v 4 Index 15 Abstract This document describes Haddock version 2.6.1, a Haskell documentation tool. Haddock User Guide 1 / 15 Chapter 1 Introduction This is Haddock, a tool for automatically generating documentation from annotated Haskell source code.