Elmulating Javascript
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
An Empirical Study on Program Comprehension with Reactive Programming
Jens Knoop, Uwe Zdun (Hrsg.): Software Engineering 2016, Lecture Notes in Informatics (LNI), Gesellschaft fur¨ Informatik, Bonn 2016 69 An Emirical Study on Program Comrehension with Reactive Programming Guido Salvaneschi, Sven Amann, Sebastian Proksch, and Mira Mezini1 Abstract: Starting from the first investigations with strictly functional languages, reactive programming has been proposed as the programming paradigm for reactive applications. The advantages of designs based on this style overdesigns based on the Observer design pattern have been studied for along time. Over the years, researchers have enriched reactive languages with more powerful abstractions, embedded these abstractions into mainstream languages –including object-oriented languages –and applied reactive programming to several domains, likeGUIs, animations, Webapplications, robotics, and sensor networks. However, an important assumption behind this line of research –that, beside other advantages, reactive programming makes awide class of otherwise cumbersome applications more comprehensible –has neverbeen evaluated. In this paper,wepresent the design and the results of the first empirical study that evaluates the effect of reactive programming on comprehensibility compared to the traditional object-oriented style with the Observer design pattern. Results confirm the conjecture that comprehensibility is enhanced by reactive programming. In the experiment, the reactive programming group significantly outperforms the other group. Keywords: Reactive Programming, Controlled -
Learning React Functional Web Development with React and Redux
Learning React Functional Web Development with React and Redux Alex Banks and Eve Porcello Beijing Boston Farnham Sebastopol Tokyo Learning React by Alex Banks and Eve Porcello Copyright © 2017 Alex Banks and Eve Porcello. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com/safari). For more information, contact our corporate/insti‐ tutional sales department: 800-998-9938 or [email protected]. Editor: Allyson MacDonald Indexer: WordCo Indexing Services Production Editor: Melanie Yarbrough Interior Designer: David Futato Copyeditor: Colleen Toporek Cover Designer: Karen Montgomery Proofreader: Rachel Head Illustrator: Rebecca Demarest May 2017: First Edition Revision History for the First Edition 2017-04-26: First Release See http://oreilly.com/catalog/errata.csp?isbn=9781491954621 for release details. The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Learning React, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. While the publisher and the authors have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights. -
CADET: Computer Assisted Discovery Extraction and Translation
CADET: Computer Assisted Discovery Extraction and Translation Benjamin Van Durme, Tom Lippincott, Kevin Duh, Deana Burchfield, Adam Poliak, Cash Costello, Tim Finin, Scott Miller, James Mayfield Philipp Koehn, Craig Harman, Dawn Lawrie, Chandler May, Max Thomas Annabelle Carrell, Julianne Chaloux, Tongfei Chen, Alex Comerford Mark Dredze, Benjamin Glass, Shudong Hao, Patrick Martin, Pushpendre Rastogi Rashmi Sankepally, Travis Wolfe, Ying-Ying Tran, Ted Zhang Human Language Technology Center of Excellence, Johns Hopkins University Abstract Computer Assisted Discovery Extraction and Translation (CADET) is a workbench for helping knowledge workers find, la- bel, and translate documents of interest. It combines a multitude of analytics together with a flexible environment for customiz- Figure 1: CADET concept ing the workflow for different users. This open-source framework allows for easy development of new research prototypes using a micro-service architecture based atop Docker and Apache Thrift.1 1 Introduction CADET is an integrated workbench for helping knowledge workers discover, extract, and translate Figure 2: Discovery user interface useful information. The user interface (Figure1) is based on a domain expert starting with a large information in structured form. To do so, she ex- collection of data, wishing to discover the subset ports the search results to our Extraction interface, that is most salient to their goals, and exporting where she can provide annotations to help train an the results to tools for either extraction of specific information extraction system. The Extraction in- information of interest or interactive translation. terface allows the user to label any text span using For example, imagine a humanitarian aid any schema, and also incorporates active learning worker with a large collection of social media to complement the discovery process in selecting messages obtained in the aftermath of a natural data to annotate. -
Flapjax: Functional Reactive Web Programming
Flapjax: Functional Reactive Web Programming Leo Meyerovich Department of Computer Science Brown University [email protected] 1 People whose names should be before mine. Thank you to Shriram Krishnamurthi and Gregory Cooper for ensuring this project’s success. I’m not sure what would have happened if not for the late nights with Michael Greenberg, Aleks Bromfield, and Arjun Guha. Peter Hopkins, Jay McCarthy, Josh Gan, An- drey Skylar, Jacob Baskin, Kimberly Burchett, Noel Welsh, and Lee Butterman provided invaluable input. While not directly involved with this particular project, Kathi Fisler and Michael Tschantz have pushed me along. 1 Contents 4.6. Objects and Collections . 32 4.6.1 Delta Propagation . 32 1. Introduction 3 4.6.2 Shallow vs Deep Binding . 33 1.1 Document Approach . 3 4.6.3 DOM Binding . 33 2. Background 4 4.6.4 Server Binding . 33 2.1. Web Programming . 4 4.6.5 Disconnected Nodes and 2.2. Functional Reactive Programming . 5 Garbage Collection . 33 2.2.1 Events . 6 2.2.2 Behaviours . 7 4.7. Evaluations . 34 2.2.3 Automatic Lifting: Transparent 4.7.1 Demos . 34 Reactivity . 8 4.7.2 Applications . 34 2.2.4 Records and Transparent Reac- 4.8 Errors . 34 tivity . 10 2.2.5 Behaviours and Events: Conver- 4.9 Library vs Language . 34 sions and Event-Based Derivation 10 4.9.1 Dynamic Typing . 34 4.9.2 Optimization . 35 3. Implementation 11 3.1. Topological Evaluation and Glitches . 13 4.9.3 Components . 35 3.1.1 Time Steps . 15 4.9.4 Compilation . -
UNIVERSITY of CALIFORNIA SAN DIEGO Simplifying Datacenter Fault
UNIVERSITY OF CALIFORNIA SAN DIEGO Simplifying datacenter fault detection and localization A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science by Arjun Roy Committee in charge: Alex C. Snoeren, Co-Chair Ken Yocum, Co-Chair George Papen George Porter Stefan Savage Geoff Voelker 2018 Copyright Arjun Roy, 2018 All rights reserved. The Dissertation of Arjun Roy is approved and is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Co-Chair University of California San Diego 2018 iii DEDICATION Dedicated to my grandmother, Bela Sarkar. iv TABLE OF CONTENTS Signature Page . iii Dedication . iv Table of Contents . v List of Figures . viii List of Tables . x Acknowledgements . xi Vita........................................................................ xiii Abstract of the Dissertation . xiv Chapter 1 Introduction . 1 Chapter 2 Datacenters, applications, and failures . 6 2.1 Datacenter applications, networks and faults . 7 2.1.1 Datacenter application patterns . 7 2.1.2 Datacenter networks . 10 2.1.3 Datacenter partial faults . 14 2.2 Partial faults require passive impact monitoring . 17 2.2.1 Multipath hampers server-centric monitoring . 18 2.2.2 Partial faults confuse network-centric monitoring . 19 2.3 Unifying network and server centric monitoring . 21 2.3.1 Load-balanced links mean outliers correspond with partial faults . 22 2.3.2 Centralized network control enables collating viewpoints . 23 Chapter 3 Related work, challenges and a solution . 24 3.1 Fault localization effectiveness criteria . 24 3.2 Existing fault management techniques . 28 3.2.1 Server-centric fault detection . 28 3.2.2 Network-centric fault detection . -
Crawling Code Review Data from Phabricator
Friedrich-Alexander-Universit¨atErlangen-N¨urnberg Technische Fakult¨at,Department Informatik DUMITRU COTET MASTER THESIS CRAWLING CODE REVIEW DATA FROM PHABRICATOR Submitted on 4 June 2019 Supervisors: Michael Dorner, M. Sc. Prof. Dr. Dirk Riehle, M.B.A. Professur f¨urOpen-Source-Software Department Informatik, Technische Fakult¨at Friedrich-Alexander-Universit¨atErlangen-N¨urnberg Versicherung Ich versichere, dass ich die Arbeit ohne fremde Hilfe und ohne Benutzung anderer als der angegebenen Quellen angefertigt habe und dass die Arbeit in gleicher oder ¨ahnlicherForm noch keiner anderen Pr¨ufungsbeh¨ordevorgelegen hat und von dieser als Teil einer Pr¨ufungsleistung angenommen wurde. Alle Ausf¨uhrungen,die w¨ortlich oder sinngem¨aߨubernommenwurden, sind als solche gekennzeichnet. Nuremberg, 4 June 2019 License This work is licensed under the Creative Commons Attribution 4.0 International license (CC BY 4.0), see https://creativecommons.org/licenses/by/4.0/ Nuremberg, 4 June 2019 i Abstract Modern code review is typically supported by software tools. Researchers use data tracked by these tools to study code review practices. A popular tool in open-source and closed-source projects is Phabricator. However, there is no tool to crawl all the available code review data from Phabricator hosts. In this thesis, we develop a Python crawler named Phabry, for crawling code review data from Phabricator instances using its REST API. The tool produces minimal server and client load, reproducible crawling runs, and stores complete and genuine review data. The new tool is used to crawl the Phabricator instances of the open source projects FreeBSD, KDE and LLVM. The resulting data sets can be used by researchers. -
Artificial Intelligence for Understanding Large and Complex
Artificial Intelligence for Understanding Large and Complex Datacenters by Pengfei Zheng Department of Computer Science Duke University Date: Approved: Benjamin C. Lee, Advisor Bruce M. Maggs Jeffrey S. Chase Jun Yang Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science in the Graduate School of Duke University 2020 Abstract Artificial Intelligence for Understanding Large and Complex Datacenters by Pengfei Zheng Department of Computer Science Duke University Date: Approved: Benjamin C. Lee, Advisor Bruce M. Maggs Jeffrey S. Chase Jun Yang An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science in the Graduate School of Duke University 2020 Copyright © 2020 by Pengfei Zheng All rights reserved except the rights granted by the Creative Commons Attribution-Noncommercial Licence Abstract As the democratization of global-scale web applications and cloud computing, under- standing the performance of a live production datacenter becomes a prerequisite for making strategic decisions related to datacenter design and optimization. Advances in monitoring, tracing, and profiling large, complex systems provide rich datasets and establish a rigorous foundation for performance understanding and reasoning. But the sheer volume and complexity of collected data challenges existing techniques, which rely heavily on human intervention, expert knowledge, and simple statistics. In this dissertation, we address this challenge using artificial intelligence and make the case for two important problems, datacenter performance diagnosis and datacenter workload characterization. The first thrust of this dissertation is the use of statistical causal inference and Bayesian probabilistic model for datacenter straggler diagnosis. -
Coleman-Coding-Freedom.Pdf
Coding Freedom !" Coding Freedom THE ETHICS AND AESTHETICS OF HACKING !" E. GABRIELLA COLEMAN PRINCETON UNIVERSITY PRESS PRINCETON AND OXFORD Copyright © 2013 by Princeton University Press Creative Commons Attribution- NonCommercial- NoDerivs CC BY- NC- ND Requests for permission to modify material from this work should be sent to Permissions, Princeton University Press Published by Princeton University Press, 41 William Street, Princeton, New Jersey 08540 In the United Kingdom: Princeton University Press, 6 Oxford Street, Woodstock, Oxfordshire OX20 1TW press.princeton.edu All Rights Reserved At the time of writing of this book, the references to Internet Web sites (URLs) were accurate. Neither the author nor Princeton University Press is responsible for URLs that may have expired or changed since the manuscript was prepared. Library of Congress Cataloging-in-Publication Data Coleman, E. Gabriella, 1973– Coding freedom : the ethics and aesthetics of hacking / E. Gabriella Coleman. p. cm. Includes bibliographical references and index. ISBN 978-0-691-14460-3 (hbk. : alk. paper)—ISBN 978-0-691-14461-0 (pbk. : alk. paper) 1. Computer hackers. 2. Computer programmers. 3. Computer programming—Moral and ethical aspects. 4. Computer programming—Social aspects. 5. Intellectual freedom. I. Title. HD8039.D37C65 2012 174’.90051--dc23 2012031422 British Library Cataloging- in- Publication Data is available This book has been composed in Sabon Printed on acid- free paper. ∞ Printed in the United States of America 1 3 5 7 9 10 8 6 4 2 This book is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE !" We must be free not because we claim freedom, but because we practice it. -
Unicorn: a System for Searching the Social Graph
Unicorn: A System for Searching the Social Graph Michael Curtiss, Iain Becker, Tudor Bosman, Sergey Doroshenko, Lucian Grijincu, Tom Jackson, Sandhya Kunnatur, Soren Lassen, Philip Pronin, Sriram Sankar, Guanghao Shen, Gintaras Woss, Chao Yang, Ning Zhang Facebook, Inc. ABSTRACT rative of the evolution of Unicorn's architecture, as well as Unicorn is an online, in-memory social graph-aware index- documentation for the major features and components of ing system designed to search trillions of edges between tens the system. of billions of users and entities on thousands of commodity To the best of our knowledge, no other online graph re- servers. Unicorn is based on standard concepts in informa- trieval system has ever been built with the scale of Unicorn tion retrieval, but it includes features to promote results in terms of both data volume and query volume. The sys- with good social proximity. It also supports queries that re- tem serves tens of billions of nodes and trillions of edges quire multiple round-trips to leaves in order to retrieve ob- at scale while accounting for per-edge privacy, and it must jects that are more than one edge away from source nodes. also support realtime updates for all edges and nodes while Unicorn is designed to answer billions of queries per day at serving billions of daily queries at low latencies. latencies in the hundreds of milliseconds, and it serves as an This paper includes three main contributions: infrastructural building block for Facebook's Graph Search • We describe how we applied common information re- product. In this paper, we describe the data model and trieval architectural concepts to the domain of the so- query language supported by Unicorn. -
2.3 Apache Chemistry
UNIVERSITY OF DUBLIN TRINITY COLLEGE DISSERTATION PRESENTED TO THE UNIVERSITY OF DUBLIN,TRINITY COLLEGE IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MAGISTER IN ARTE INGENIARIA Content Interoperability and Open Source Content Management Systems An implementation of the CMIS standard as a PHP library Author: Supervisor: MATTHEW NICHOLSON DAVE LEWIS Submitted to the University of Dublin, Trinity College, May, 2015 Declaration I, Matthew Nicholson, declare that the following dissertation, except where otherwise stated, is entirely my own work; that it has not previously been submitted as an exercise for a degree, either in Trinity College Dublin, or in any other University; and that the library may lend or copy it or any part thereof on request. May 21, 2015 Matthew Nicholson i Summary This paper covers the design, implementation and evaluation of PHP li- brary to aid in use of the Content Management Interoperability Services (CMIS) standard. The standard attempts to provide a language indepen- dent and platform specific mechanisms to better allow content manage- ment systems (CM systems) work together. There is currently no PHP implementation of CMIS server framework available, at least not widely. The name given to the library is Elaphus CMIS. The implementation should remove a barrier for making PHP CM sys- tems CMIS compliant. Aswell testing how language independent the stan- dard is and look into the features of PHP programming language. The technologies that are the focus of this report are: CMIS A standard that attempts to structure the data within a wide range of CM systems and provide standardised API for interacting with this data. -
ATLAS Operational Monitoring Data Archival and Visualization
EPJ Web of Conferences 245, 01020 (2020) https://doi.org/10.1051/epjconf/202024501020 CHEP 2019 ATLAS Operational Monitoring Data Archival and Visualiza- tion Igor Soloviev1;∗, Giuseppe Avolio2, Andrei Kazymov3, and Matei Vasile4 1University of California, Irvine, CA 92697-4575, US 2European Laboratory for Particle Physics, CERN, Geneva 23, CH-1211, Switzerland 3Joint Institute for Nuclear Research, JINR, Dubna, Russian Federation 4Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania Abstract. The Information Service (IS) is an integral part of the Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The IS allows online publication of opera- tional monitoring data, and it is used by all sub-systems and sub-detectors of the experiment to constantly monitor their hardware and software components including more than 25000 applications running on more than 3000 comput- ers. The Persistent Back-End for the ATLAS Information System (PBEAST) service stores all raw operational monitoring data for the lifetime of the ex- periment and provides programming and graphical interfaces to access them including Grafana dashboards and notebooks based on the CERN SWAN plat- form. During the ATLAS data taking sessions (for the full LHC Run 2 period) PBEAST acquired data at an average information update rate of 200 kHz and stored 20 TB of highly compacted and compressed data per year. This paper reports how over six years PBEAST became an essential piece of the experi- ment operations including details of the challenging requirements, the failures and successes of the various attempted implementations, the new types of mon- itoring data and the results of the time-series database technology evaluations for the improvements towards LHC Run 3. -
Characterizing Callbacks in Javascript
Don’t Call Us, We’ll Call You: Characterizing Callbacks in JavaScript Keheliya Gallaba Ali Mesbah Ivan Beschastnikh University of British Columbia University of British Columbia University of British Columbia Vancouver, BC, Canada Vancouver, BC, Canada Vancouver, BC, Canada [email protected] [email protected] [email protected] Abstract—JavaScript is a popular language for developing 1 var db = require(’somedatabaseprovider’); web applications and is increasingly used for both client-side 2 http.get(’/recentposts’, function(req, res){ and server-side application logic. The JavaScript runtime is 3 db.openConnection(’host’, creds, function(err, conn){ inherently event-driven and callbacks are a key language feature. 4 res.param[’posts’]. forEach(function(post) { 5 conn.query(’select * from users where id=’ + post Unfortunately, callbacks induce a non-linear control flow and can [’user’], function(err, results){ be deferred to execute asynchronously, declared anonymously, 6 conn.close(); and may be nested to arbitrary levels. All of these features make 7 res.send(results[0]); callbacks difficult to understand and maintain. 8 }); 9 }); We perform an empirical study to characterize JavaScript 10 }); callback usage across a representative corpus of 138 JavaScript 11 }); programs, with over 5 million lines of JavaScript code. We Listing 1. A representative JavaScript snippet illustrating the comprehension find that on average, every 10th function definition takes a and maintainability challenges associated with nested, anonymous callbacks callback argument, and that over 43% of all callback-accepting and asynchronous callback scheduling. function callsites are anonymous. Furthermore, the majority of callbacks are nested, more than half of all callbacks are asynchronous, and asynchronous callbacks, on average, appear more frequently in client-side code (72%) than server-side (55%).