Event Loops As First-Class Values: a Case Study In
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Little Languages for Little Robots
Little Languages for Little Robots Matthew C. Jadud Brooke N. Chenoweth Jacob Schleter University of Kent Canterbury Indiana University Gibson High School Canterbury, UK Bloomington Fort Branch, IN [email protected] Bloomington, IN [email protected] ABSTRACT where students learn by building personally meaningful With serendipity as our muse, we have created tools that artifacts in the world. allow students to author languages of their own design for robots of their own construction. In developing a Scheme 2. JACKLL: A NEW LANGUAGE compiler for the LEGO Mindstorm we realized that there In building up to the evolution of Jackll and the philoso- is great educational potential in the design and creation phies its creation embodies, we feel it is appropriate to of new languages for small robotics kits. As a side effect first introduce the LEGO Mindstorm, the target for our of bringing Scheme and the Mindstorm together in a cre- Scheme compiler, and situate Jackll with respect to other ative context, we have begun an exploration of teaching languages intended for beginner programmers. language design that is fundamentally different from the treatment of the subject in traditional literature. 2.1 What is the LEGO Mindstorm? The LEGO Mindstorm Robotics Invention System is a 1. INTRODUCTION commercial product from the LEGO Group that provides Jacob Schleter, a rising senior at Gibson High School, Fort an inexpensive, reconfigurable platform for exploring robotics. Branch, Indiana, took part in the Indiana University Col- It comes standard with two motors, two touch sensors, one lege of Arts and Sciences Summer Research Experience for light sensor, and hundreds of pieces for assembling all sorts six weeks during the summer of 2002. -
Compiler Error Messages Considered Unhelpful: the Landscape of Text-Based Programming Error Message Research
Working Group Report ITiCSE-WGR ’19, July 15–17, 2019, Aberdeen, Scotland Uk Compiler Error Messages Considered Unhelpful: The Landscape of Text-Based Programming Error Message Research Brett A. Becker∗ Paul Denny∗ Raymond Pettit∗ University College Dublin University of Auckland University of Virginia Dublin, Ireland Auckland, New Zealand Charlottesville, Virginia, USA [email protected] [email protected] [email protected] Durell Bouchard Dennis J. Bouvier Brian Harrington Roanoke College Southern Illinois University Edwardsville University of Toronto Scarborough Roanoke, Virgina, USA Edwardsville, Illinois, USA Scarborough, Ontario, Canada [email protected] [email protected] [email protected] Amir Kamil Amey Karkare Chris McDonald University of Michigan Indian Institute of Technology Kanpur University of Western Australia Ann Arbor, Michigan, USA Kanpur, India Perth, Australia [email protected] [email protected] [email protected] Peter-Michael Osera Janice L. Pearce James Prather Grinnell College Berea College Abilene Christian University Grinnell, Iowa, USA Berea, Kentucky, USA Abilene, Texas, USA [email protected] [email protected] [email protected] ABSTRACT of evidence supporting each one (historical, anecdotal, and empiri- Diagnostic messages generated by compilers and interpreters such cal). This work can serve as a starting point for those who wish to as syntax error messages have been researched for over half of a conduct research on compiler error messages, runtime errors, and century. Unfortunately, these messages which include error, warn- warnings. We also make the bibtex file of our 300+ reference corpus ing, and run-time messages, present substantial difficulty and could publicly available. -
How to Design Co-Programs
JFP, 15 pages, 2021. c Cambridge University Press 2021 1 doi:10.1017/xxxxx EDUCATIONMATTERS How to Design Co-Programs JEREMY GIBBONS Department of Computer Science, University of Oxford e-mail: [email protected] Abstract The observation that program structure follows data structure is a key lesson in introductory pro- gramming: good hints for possible program designs can be found by considering the structure of the data concerned. In particular, this lesson is a core message of the influential textbook “How to Design Programs” by Felleisen, Findler, Flatt, and Krishnamurthi. However, that book discusses using only the structure of input data for guiding program design, typically leading towards structurally recur- sive programs. We argue that novice programmers should also be taught to consider the structure of output data, leading them also towards structurally corecursive programs. 1 Introduction Where do programs come from? This mystery can be an obstacle to novice programmers, who can become overwhelmed by the design choices presented by a blank sheet of paper, or an empty editor window— where does one start? A good place to start, we tell them, is by analyzing the structure of the data that the program is to consume. For example, if the program h is to process a list of values, one may start by analyzing the structure of that list. Either the list is empty ([]), or it is non-empty (a : x) with a head (a) and a tail (x). This provides a candidate program structure: h [ ] = ::: h (a : x) = ::: a ::: x ::: where for the empty list some result must simply be chosen, and for a non-empty list the result depends on the head a and tail x. -
Panel: NSF-Sponsored Innovative Approaches to Undergraduate Computer Science
Panel: NSF-Sponsored Innovative Approaches to Undergraduate Computer Science Stephen Bloch (Adelphi University) Amruth Kumar (Ramapo College) Stanislav Kurkovsky (Central CT State University) Clif Kussmaul (Muhlenberg College) Matt Dickerson (Middlebury College), moderator Project Web site(s) Intervention Delivery Supervision Program http://programbydesign.org curriculum with supporting in class; software normally active, but can be by Design http://picturingprograms.org IDE, libraries, & texts and textbook are done other ways Stephen Bloch http://www.ccs.neu.edu/home/ free downloads matthias/HtDP2e/ or web-based NSF awards 0010064 http://racket-lang.org & 0618543 http://wescheme.org Problets http://www.problets.org in- or after-class problem- applet in none - teacher not needed, Amruth Kumar solving exercises on a browser although some adopters use programming concepts it in active mode too NSF award 0817187 Mobile Game http://www.mgdcs.com/ in-class or take-home PC passive - teacher as Development programming projects facilitator to answer Qs Stan Kurkovsky NSF award DUE-0941348 POGIL http://pogil.org in-class activity paper or web passive - teacher as Clif Kussmaul http://cspogil.org facilitator to answer Qs NSF award TUES 1044679 Project Course(s) Language(s) Focus Program Middle school, Usually Scheme-like teaching problem-solving process, by pre-AP CS in HS, languages leading into Java; particularly test-driven DesignStephen CS0, CS1, CS2 has also been done in Python, development and use of data Bloch in college ML, Java, Scala, ... types to guide coding & testing Problets AP-CS, CS I, CS 2. C, C++, Java, C# code tracing, debugging, Amruth Kumar also as refresher or expression evaluation, to switch languages predicting program state in other courses Mobile Game AP-CS, CS1, CS2 Java core OO programming; DevelopmentSt intro to advanced subjects an Kurkovsky such as AI, networks, security POGILClif CS1, CS2, SE, etc. -
Agent-Based Architectures and Algorithms for Energy Management in Smart Gribs : Application to Smart Power Generation and Residential Demand Response Robin Roche
Agent-Based Architectures and Algorithms for Energy Management in Smart Gribs : Application to Smart Power Generation and Residential Demand Response Robin Roche To cite this version: Robin Roche. Agent-Based Architectures and Algorithms for Energy Management in Smart Gribs : Application to Smart Power Generation and Residential Demand Response. Other. Université de Technologie de Belfort-Montbeliard, 2012. English. NNT : 2012BELF0191. tel-00864268 HAL Id: tel-00864268 https://tel.archives-ouvertes.fr/tel-00864268 Submitted on 20 Sep 2013 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Université de Technologie de Belfort–Montbéliard Institut de Recherche sur les Transports, l’Énergie et la Société Laboratoire Systèmes et Transports École Doctorale Sciences pour l’Ingénieur et Microtechniques Algorithmes et Architectures Multi-Agents pour la Gestion de l’Énergie dans les Réseaux Électriques Intelligents Application aux Centrales à Turbines à Gaz et à l’Effacement Diffus Résidentiel Thèse no191 présentée et soutenue publiquement en vue de l’obtention du titre de Docteur en Génie Électrique par Robin Roche le 7 décembre 2012 Membres du jury : M. Mohamed Benbouzid IUT de Brest, LBMS Président M. Nouredine Hadjsaid INP Grenoble, G2Elab Rapporteur M. -
Easybuild Documentation Release 20210706.0 Ghent University
EasyBuild Documentation Release 20210907.0 Ghent University Tue, 07 Sep 2021 08:55:25 Contents 1 What is EasyBuild? 3 2 Concepts and terminology 5 2.1 EasyBuild framework..........................................5 2.2 Easyblocks................................................6 2.3 Toolchains................................................7 2.3.1 system toolchain.......................................7 2.3.2 dummy toolchain (DEPRECATED) ..............................7 2.3.3 Common toolchains.......................................7 2.4 Easyconfig files..............................................7 2.5 Extensions................................................8 3 Typical workflow example: building and installing WRF9 3.1 Searching for available easyconfigs files.................................9 3.2 Getting an overview of planned installations.............................. 10 3.3 Installing a software stack........................................ 11 4 Getting started 13 4.1 Installing EasyBuild........................................... 13 4.1.1 Requirements.......................................... 14 4.1.2 Using pip to Install EasyBuild................................. 14 4.1.3 Installing EasyBuild with EasyBuild.............................. 17 4.1.4 Dependencies.......................................... 19 4.1.5 Sources............................................. 21 4.1.6 In case of installation issues. .................................. 22 4.2 Configuring EasyBuild.......................................... 22 4.2.1 Supported configuration -
The Next 700 Semantics: a Research Challenge Shriram Krishnamurthi Brown University [email protected] Benjamin S
The Next 700 Semantics: A Research Challenge Shriram Krishnamurthi Brown University [email protected] Benjamin S. Lerner Northeastern University [email protected] Liam Elberty Unaffiliated Abstract Modern systems consist of large numbers of languages, frameworks, libraries, APIs, and more. Each has characteristic behavior and data. Capturing these in semantics is valuable not only for understanding them but also essential for formal treatment (such as proofs). Unfortunately, most of these systems are defined primarily through implementations, which means the semantics needs to be learned. We describe the problem of learning a semantics, provide a structuring process that is of potential value, and also outline our failed attempts at achieving this so far. 2012 ACM Subject Classification Software and its engineering → General programming languages; Software and its engineering → Language features; Software and its engineering → Semantics; Software and its engineering → Formal language definitions Keywords and phrases Programming languages, desugaring, semantics, testing Digital Object Identifier 10.4230/LIPIcs.SNAPL.2019.9 Funding This work was partially supported by the US National Science Foundation and Brown University while all authors were at Brown University. Acknowledgements The authors thank Eugene Charniak and Kevin Knight for useful conversations. The reviewers provided useful feedback that improved the presentation. © Shriram Krishnamurthi and Benjamin S. Lerner and Liam Elberty; licensed under Creative Commons License CC-BY 3rd Summit on Advances in Programming Languages (SNAPL 2019). Editors: Benjamin S. Lerner, Rastislav Bodík, and Shriram Krishnamurthi; Article No. 9; pp. 9:1–9:14 Leibniz International Proceedings in Informatics Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Germany 9:2 The Next 700 Semantics: A Research Challenge 1 Motivation Semantics is central to the trade of programming language researchers and practitioners. -
Use of Bio-Inspired Techniques to Solve Complex Engineering Problems: Industrial Automation Case Study
Use of Bio-inspired Techniques to Solve Complex Engineering Problems: Industrial Automation Case Study José Fernando Lopes Barbosa Relatório de Projecto para obtenção do grau de Mestre em Engenharia Industrial ramo de especialização em Engenharia Electrotécnica Supervision: Prof. Dr. Paulo Leitão September, 2010 Dedication To Inês and Mariana ii Acknowledgements First of all I want to express my most grateful thanks to Professor Paulo Leitão for his knowledge, patient, support and constant motivation during the development of this work without which the conclusion was not possible. Next, I want to thank all my friends for their support, incentive and motivation. I also want to thank my parents for all the support and love throughout the years. A special thank to my beautiful grandmother that with her love and affection made me feel to be her special grandson. Finally, but not the least, I want to thank my wife Inês for her support and comprehension and to my daughter Mariana just to make me constantly smile. iii Abstract Nowadays local markets have disappeared and the world lives in a global economy. Due to this reality, every company virtually competes with all others companies in the world. In addition to this, markets constantly search products with higher quality at lower costs, with high customization. Also, products tend to have a shorter period of life, making the demanding more intense. With this scenario, companies, to remain competitive, must constantly adapt themselves to the market changes, i.e., companies must exhibit a great degree of self-organization and self-adaptation. Biology with the millions of years of evolution may offer inspiration to develop new algorithms, methods and techniques to solve real complex problems. -
Proceedings of the 8Th European Lisp Symposium Goldsmiths, University of London, April 20-21, 2015 Julian Padget (Ed.) Sponsors
Proceedings of the 8th European Lisp Symposium Goldsmiths, University of London, April 20-21, 2015 Julian Padget (ed.) Sponsors We gratefully acknowledge the support given to the 8th European Lisp Symposium by the following sponsors: WWWLISPWORKSCOM i Organization Programme Committee Julian Padget – University of Bath, UK (chair) Giuseppe Attardi — University of Pisa, Italy Sacha Chua — Toronto, Canada Stephen Eglen — University of Cambridge, UK Marc Feeley — University of Montreal, Canada Matthew Flatt — University of Utah, USA Rainer Joswig — Hamburg, Germany Nick Levine — RavenPack, Spain Henry Lieberman — MIT, USA Christian Queinnec — University Pierre et Marie Curie, Paris 6, France Robert Strandh — University of Bordeaux, France Edmund Weitz — University of Applied Sciences, Hamburg, Germany Local Organization Christophe Rhodes – Goldsmiths, University of London, UK (chair) Richard Lewis – Goldsmiths, University of London, UK Shivi Hotwani – Goldsmiths, University of London, UK Didier Verna – EPITA Research and Development Laboratory, France ii Contents Acknowledgments i Messages from the chairs v Invited contributions Quicklisp: On Beyond Beta 2 Zach Beane µKanren: Running the Little Things Backwards 3 Bodil Stokke Escaping the Heap 4 Ahmon Dancy Unwanted Memory Retention 5 Martin Cracauer Peer-reviewed papers Efficient Applicative Programming Environments for Computer Vision Applications 7 Benjamin Seppke and Leonie Dreschler-Fischer Keyboard? How quaint. Visual Dataflow Implemented in Lisp 15 Donald Fisk P2R: Implementation of -
Application and Interpretation
Programming Languages: Application and Interpretation Shriram Krishnamurthi Brown University Copyright c 2003, Shriram Krishnamurthi This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License. If you create a derivative work, please include the version information below in your attribution. This book is available free-of-cost from the author’s Web site. This version was generated on 2007-04-26. ii Preface The book is the textbook for the programming languages course at Brown University, which is taken pri- marily by third and fourth year undergraduates and beginning graduate (both MS and PhD) students. It seems very accessible to smart second year students too, and indeed those are some of my most successful students. The book has been used at over a dozen other universities as a primary or secondary text. The book’s material is worth one undergraduate course worth of credit. This book is the fruit of a vision for teaching programming languages by integrating the “two cultures” that have evolved in its pedagogy. One culture is based on interpreters, while the other emphasizes a survey of languages. Each approach has significant advantages but also huge drawbacks. The interpreter method writes programs to learn concepts, and has its heart the fundamental belief that by teaching the computer to execute a concept we more thoroughly learn it ourselves. While this reasoning is internally consistent, it fails to recognize that understanding definitions does not imply we understand consequences of those definitions. For instance, the difference between strict and lazy evaluation, or between static and dynamic scope, is only a few lines of interpreter code, but the consequences of these choices is enormous. -
Cellular Automata Are Models of Distributed Dynamical Systems
IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 3, Ver. IV (May-Jun. 2016), PP 92-101 www.iosrjournals.org A New Multi-Agent Game Solver Miklos N Szilagyi Department of Electrical and Computer Engineering University of Arizona, Tucson, AZ 85721 Abstract: A new N-person game solver is presented in this work. The new software is an advance in the whole sate of art for the investigation of N-person games. It is now possible to investigate entire classes of games almost automatically. Moreover, this software makes it trivial to perform a systematic investigation of any game with a multidimensional parameter space. In addition, the payoff functions are no longer limited to quadratic expressions; any elementary mathematical function can easily be used, even in parameterized form. The experimental results are interesting and they very strongly depend on the initial conditions. Keywords: N-person games, Netlogo, Agent-based simulation, Prisoners’ Dilemma, Chicken Dilemma, Complexity. I. Introduction Many complex phenomena can be represented as N-person games in which the participating agents all interact with all the other agents directly or indirectly [1-4]. In the latter case the agents immediately interact only with their immediate neighbors. In this case the agents are simply cells in a cellular automaton. Cellular automata [5-7] are powerful tools for the study of simultaneous operation of a large number of agents, i. e. for the investigation of complex systems and phenomena. Therefore, they are quite suitable for the study of spatial N-person games. -
Essentials of Compilation an Incremental Approach
Essentials of Compilation An Incremental Approach Jeremy G. Siek, Ryan R. Newton Indiana University with contributions from: Carl Factora Andre Kuhlenschmidt Michael M. Vitousek Michael Vollmer Ryan Scott Cameron Swords April 2, 2019 ii This book is dedicated to the programming language wonks at Indiana University. iv Contents 1 Preliminaries 5 1.1 Abstract Syntax Trees and S-expressions . .5 1.2 Grammars . .7 1.3 Pattern Matching . .9 1.4 Recursion . 10 1.5 Interpreters . 12 1.6 Example Compiler: a Partial Evaluator . 14 2 Integers and Variables 17 2.1 The R1 Language . 17 2.2 The x86 Assembly Language . 20 2.3 Planning the trip to x86 via the C0 language . 24 2.3.1 The C0 Intermediate Language . 27 2.3.2 The dialects of x86 . 28 2.4 Uniquify Variables . 28 2.5 Remove Complex Operators and Operands . 30 2.6 Explicate Control . 31 2.7 Uncover Locals . 32 2.8 Select Instructions . 32 2.9 Assign Homes . 33 2.10 Patch Instructions . 34 2.11 Print x86 . 35 3 Register Allocation 37 3.1 Registers and Calling Conventions . 38 3.2 Liveness Analysis . 39 3.3 Building the Interference Graph . 40 3.4 Graph Coloring via Sudoku . 42 3.5 Print x86 and Conventions for Registers . 48 v vi CONTENTS 3.6 Challenge: Move Biasing∗ .................... 48 4 Booleans and Control Flow 53 4.1 The R2 Language . 54 4.2 Type Checking R2 Programs . 55 4.3 Shrink the R2 Language . 58 4.4 XOR, Comparisons, and Control Flow in x86 . 58 4.5 The C1 Intermediate Language .