Thorn—Robust, Concurrent, Extensible Scripting on the JVM
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Application-Level Virtual Memory for Object-Oriented Systems Mariano Martinez Peck
Application-Level Virtual Memory for Object-Oriented Systems Mariano Martinez Peck To cite this version: Mariano Martinez Peck. Application-Level Virtual Memory for Object-Oriented Systems. Program- ming Languages [cs.PL]. Université des Sciences et Technologie de Lille - Lille I, 2012. English. tel-00764991 HAL Id: tel-00764991 https://tel.archives-ouvertes.fr/tel-00764991 Submitted on 26 Dec 2012 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. N° d’ordre : 40886 THESE présentée en vue d’obtenir le grade de DOCTEUR en Spécialité : informatique par Mariano MARTINEZ PECK DOCTORAT DELIVRE CONJOINTEMENT PAR MINES DOUAI ET L’UNIVERSITE DE LILLE 1 Titre de la thèse : Application-Level Virtual Memory for Object-Oriented Systems Soutenue le 29/10/2012 à 10h devant le jury d’examen : Président Jean-Bernard STEFANI (Directeur de recherche – INRIA Grenoble- Rhône-Alpes) Directeur de thèse Stéphane DUCASSE (Directeur de recherche – INRIA Lille) Rapporteur Robert HIRSCHFELD (Professeur – Hasso-Plattner-Institut, Universität Potsdam, Allemagne) Rapporteur Christophe DONY (Professeur – Université Montpellier 2) Examinateur Roel WUYTS (Professeur – IMEC & Katholieke Universiteit Leuven, Belgique) co-Encadrant Noury BOURAQADI (Maître-Assistant – Mines de Douai) co-Encadrant Marcus DENKER (Chargé de recherche – INRIA Lille) co-Encadrant Luc FABRESSE (Maître-Assistant – Mines de Douai) Laboratoire(s) d’accueil : Dépt. -
SETL for Internet Data Processing
SETL for Internet Data Processing by David Bacon A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Computer Science New York University January, 2000 Jacob T. Schwartz (Dissertation Advisor) c David Bacon, 1999 Permission to reproduce this work in whole or in part for non-commercial purposes is hereby granted, provided that this notice and the reference http://www.cs.nyu.edu/bacon/phd-thesis/ remain prominently attached to the copied text. Excerpts less than one PostScript page long may be quoted without the requirement to include this notice, but must attach a bibliographic citation that mentions the author’s name, the title and year of this disser- tation, and New York University. For my children ii Acknowledgments First of all, I would like to thank my advisor, Jack Schwartz, for his support and encour- agement. I am also grateful to Ed Schonberg and Robert Dewar for many interesting and helpful discussions, particularly during my early days at NYU. Terry Boult (of Lehigh University) and Richard Wallace have contributed materially to my later work on SETL through grants from the NSF and from ARPA. Finally, I am indebted to my parents, who gave me the strength and will to bring this labor of love to what I hope will be a propitious beginning. iii Preface Colin Broughton, a colleague in Edmonton, Canada, first made me aware of SETL in 1980, when he saw the heavy use I was making of associative tables in SPITBOL for data processing in a protein X-ray crystallography laboratory. -
Edsger W. Dijkstra: a Commemoration
Edsger W. Dijkstra: a Commemoration Krzysztof R. Apt1 and Tony Hoare2 (editors) 1 CWI, Amsterdam, The Netherlands and MIMUW, University of Warsaw, Poland 2 Department of Computer Science and Technology, University of Cambridge and Microsoft Research Ltd, Cambridge, UK Abstract This article is a multiauthored portrait of Edsger Wybe Dijkstra that consists of testimo- nials written by several friends, colleagues, and students of his. It provides unique insights into his personality, working style and habits, and his influence on other computer scientists, as a researcher, teacher, and mentor. Contents Preface 3 Tony Hoare 4 Donald Knuth 9 Christian Lengauer 11 K. Mani Chandy 13 Eric C.R. Hehner 15 Mark Scheevel 17 Krzysztof R. Apt 18 arXiv:2104.03392v1 [cs.GL] 7 Apr 2021 Niklaus Wirth 20 Lex Bijlsma 23 Manfred Broy 24 David Gries 26 Ted Herman 28 Alain J. Martin 29 J Strother Moore 31 Vladimir Lifschitz 33 Wim H. Hesselink 34 1 Hamilton Richards 36 Ken Calvert 38 David Naumann 40 David Turner 42 J.R. Rao 44 Jayadev Misra 47 Rajeev Joshi 50 Maarten van Emden 52 Two Tuesday Afternoon Clubs 54 2 Preface Edsger Dijkstra was perhaps the best known, and certainly the most discussed, computer scientist of the seventies and eighties. We both knew Dijkstra |though each of us in different ways| and we both were aware that his influence on computer science was not limited to his pioneering software projects and research articles. He interacted with his colleagues by way of numerous discussions, extensive letter correspondence, and hundreds of so-called EWD reports that he used to send to a select group of researchers. -
Glossary of Technical and Scientific Terms (French / English
Glossary of Technical and Scientific Terms (French / English) Version 11 (Alphabetical sorting) Jean-Luc JOULIN October 12, 2015 Foreword Aim of this handbook This glossary is made to help for translation of technical words english-french. This document is not made to be exhaustive but aim to understand and remember the translation of some words used in various technical domains. Words are sorted alphabetically. This glossary is distributed under the licence Creative Common (BY NC ND) and can be freely redistributed. For further informations about the licence Creative Com- mon (BY NC ND), browse the site: http://creativecommons.org If you are interested by updates of this glossary, send me an email to be on my diffusion list : • [email protected] • [email protected] Warning Translations given in this glossary are for information only and their use is under the responsability of the reader. If you see a mistake in this document, thank in advance to report it to me so i can correct it in further versions of this document. Notes Sorting of words Words are sorted by alphabetical order and are associated to their main category. Difference of terms Some words are different between the "British" and the "American" english. This glossary show the most used terms and are generally coming from the "British" english Words coming from the "American" english are indicated with the suffix : US . Difference of spelling There are some difference of spelling in accordance to the country, companies, universities, ... Words finishing by -ise, -isation and -yse can also be written with -ize, Jean-Luc JOULIN1 Glossary of Technical and Scientific Terms -ization and -yze. -
CONFERENCE COMPANION ESUG 2008 - 16Th International Smalltalk Conference
ESUG-2008 CONFERENCE COMPANION ESUG 2008 - 16th International Smalltalk Conference CONTENTS Platinum Sponsors.......................................................................................................... 3 Gold Sponsors................................................................................................................ 4 Conference Location....................................................................................................... 5 Program Overview........................................................................................................... 8 Saturday, August 23...................................................................................................... 10 Sunday, August 24......................................................................................................... 10 Monday, August 25....................................................................................................... 11 Tuesday, August 26....................................................................................................... 16 Wednesday, August 27.................................................................................................. 20 Thursday, August 28...................................................................................................... 23 Friday, August 29........................................................................................................... 27 Program Overview........................................................................................................ -
Lecture 10: Fault Tolerance Fault Tolerant Concurrent Computing
02/12/2014 Lecture 10: Fault Tolerance Fault Tolerant Concurrent Computing • The main principles of fault tolerant programming are: – Fault Detection - Knowing that a fault exists – Fault Recovery - having atomic instructions that can be rolled back in the event of a failure being detected. • System’s viewpoint it is quite possible that the fault is in the program that is attempting the recovery. • Attempting to recover from a non-existent fault can be as disastrous as a fault occurring. CA463 Lecture Notes (Martin Crane 2014) 26 1 02/12/2014 Fault Tolerant Concurrent Computing (cont’d) • Have seen replication used for tasks to allow a program to recover from a fault causing a task to abruptly terminate. • The same principle is also used at the system level to build fault tolerant systems. • Critical systems are replicated, and system action is based on a majority vote of the replicated sub systems. • This redundancy allows the system to successfully continue operating when several sub systems develop faults. CA463 Lecture Notes (Martin Crane 2014) 27 Types of Failures in Concurrent Systems • Initially dead processes ( benign fault ) – A subset of the processes never even start • Crash model ( benign fault ) – Process executes as per its local algorithm until a certain point where it stops indefinitely – Never restarts • Byzantine behaviour (malign fault ) – Algorithm may execute any possible local algorithm – May arbitrarily send/receive messages CA463 Lecture Notes (Martin Crane 2014) 28 2 02/12/2014 A Hierarchy of Failure Types • Dead process – This is a special case of crashed process – Case when the crashed process crashes before it starts executing • Crashed process – This is a special case of Byzantine process – Case when the Byzantine process crashes, and then keeps staying in that state for all future transitions CA463 Lecture Notes (Martin Crane 2014) 29 Types of Fault Tolerance Algorithms • Robust algorithms – Correct processes should continue behaving thus, despite failures. -
Actor-Based Concurrency by Srinivas Panchapakesan
Concurrency in Java and Actor- based concurrency using Scala By, Srinivas Panchapakesan Concurrency Concurrent computing is a form of computing in which programs are designed as collections of interacting computational processes that may be executed in parallel. Concurrent programs can be executed sequentially on a single processor by interleaving the execution steps of each computational process, or executed in parallel by assigning each computational process to one of a set of processors that may be close or distributed across a network. The main challenges in designing concurrent programs are ensuring the correct sequencing of the interactions or communications between different computational processes, and coordinating access to resources that are shared among processes. Advantages of Concurrency Almost every computer nowadays has several CPU's or several cores within one CPU. The ability to leverage theses multi-cores can be the key for a successful high-volume application. Increased application throughput - parallel execution of a concurrent program allows the number of tasks completed in certain time period to increase. High responsiveness for input/output-intensive applications mostly wait for input or output operations to complete. Concurrent programming allows the time that would be spent waiting to be used for another task. More appropriate program structure - some problems and problem domains are well-suited to representation as concurrent tasks or processes. Process vs Threads Process: A process runs independently and isolated of other processes. It cannot directly access shared data in other processes. The resources of the process are allocated to it via the operating system, e.g. memory and CPU time. Threads: Threads are so called lightweight processes which have their own call stack but an access shared data. -
Mastering Concurrent Computing Through Sequential Thinking
review articles DOI:10.1145/3363823 we do not have good tools to build ef- A 50-year history of concurrency. ficient, scalable, and reliable concur- rent systems. BY SERGIO RAJSBAUM AND MICHEL RAYNAL Concurrency was once a specialized discipline for experts, but today the chal- lenge is for the entire information tech- nology community because of two dis- ruptive phenomena: the development of Mastering networking communications, and the end of the ability to increase processors speed at an exponential rate. Increases in performance come through concur- Concurrent rency, as in multicore architectures. Concurrency is also critical to achieve fault-tolerant, distributed services, as in global databases, cloud computing, and Computing blockchain applications. Concurrent computing through sequen- tial thinking. Right from the start in the 1960s, the main way of dealing with con- through currency has been by reduction to se- quential reasoning. Transforming problems in the concurrent domain into simpler problems in the sequential Sequential domain, yields benefits for specifying, implementing, and verifying concur- rent programs. It is a two-sided strategy, together with a bridge connecting the Thinking two sides. First, a sequential specificationof an object (or service) that can be ac- key insights ˽ A main way of dealing with the enormous challenges of building concurrent systems is by reduction to sequential I must appeal to the patience of the wondering readers, thinking. Over more than 50 years, more sophisticated techniques have been suffering as I am from the sequential nature of human developed to build complex systems in communication. this way. 12 ˽ The strategy starts by designing —E.W. -
Nested Class Modularity in Squeak/Smalltalk
Springer, Nested Class Modularity in Squeak/Smalltalk Nested Class Modularity in Squeak/Smalltalk Modularität mit geschachtelten Klassen in Squeak/Smalltalk by Matthias Springer A thesis submitted to the Hasso Plattner Institute at the University of Potsdam, Germany in partial fulfillment of the requirements for the degree of Master of Science in ITSystems Engineering Supervisor Prof. Dr. Robert Hirschfeld Software Architecture Group Hasso Plattner Institute University of Potsdam, Germany August 17, 2015 Abstract We present the concept, the implementation, and an evaluation of Matriona, a module system for and written in Squeak/Smalltalk. Matriona is inspired by Newspeak and based on class nesting: classes are members of other classes, similarly to class instance variables. Top-level classes (modules) are globals and nested classes can be accessed using message sends to the corresponding enclosing class. Class nesting effec- tively establishes a global and hierarchical namespace, and allows for modular decomposition, resulting in better understandability, if applied properly. Classes can be parameterized, allowing for external configuration of classes, a form of dependency management. Furthermore, parameterized classes go hand in hand with mixin modularity. Mixins are a form of inter-class code reuse and based on single inheritance. We show how Matriona can be used to solve the problem of duplicate classes in different modules, to provide a versioning and dependency management mech- anism, and to improve understandability through hierarchical decomposition. v Zusammenfassung Diese Arbeit beschreibt das Konzept, die Implementierung und die Evaluierung von Matriona, einem Modulsystem für und entwickelt in Squeak/Smalltalk. Ma- triona ist an Newspeak angelehnt und basiert auf geschachtelten Klassen: Klassen, die, wie zum Beispiel auch klassenseitige Instanzvariablen, zu anderen Klassen gehören. -
Concurrent Computing
Concurrent Computing CSCI 201 Principles of Software Development Jeffrey Miller, Ph.D. [email protected] Outline • Threads • Multi-Threaded Code • CPU Scheduling • Program USC CSCI 201L Thread Overview ▪ Looking at the Windows taskbar, you will notice more than one process running concurrently ▪ Looking at the Windows task manager, you’ll see a number of additional processes running ▪ But how many processes are actually running at any one time? • Multiple processors, multiple cores, and hyper-threading will determine the actual number of processes running • Threads USC CSCI 201L 3/22 Redundant Hardware Multiple Processors Single-Core CPU ALU Cache Registers Multiple Cores ALU 1 Registers 1 Cache Hyper-threading has firmware logic that appears to the OS ALU 2 to contain more than one core when in fact only one physical core exists Registers 2 4/22 Programs vs Processes vs Threads ▪ Programs › An executable file residing in memory, typically in secondary storage ▪ Processes › An executing instance of a program › Sometimes this is referred to as a Task ▪ Threads › Any section of code within a process that can execute at what appears to be simultaneously › Shares the same resources allotted to the process by the OS kernel USC CSCI 201L 5/22 Concurrent Programming ▪ Multi-Threaded Programming › Multiple sections of a process or multiple processes executing at what appears to be simultaneously in a single core › The purpose of multi-threaded programming is to add functionality to your program ▪ Parallel Programming › Multiple sections of -
1. with Examples of Different Programming Languages Show How Programming Languages Are Organized Along the Given Rubrics: I
AGBOOLA ABIOLA CSC302 17/SCI01/007 COMPUTER SCIENCE ASSIGNMENT 1. With examples of different programming languages show how programming languages are organized along the given rubrics: i. Unstructured, structured, modular, object oriented, aspect oriented, activity oriented and event oriented programming requirement. ii. Based on domain requirements. iii. Based on requirements i and ii above. 2. Give brief preview of the evolution of programming languages in a chronological order. 3. Vividly distinguish between modular programming paradigm and object oriented programming paradigm. Answer 1i). UNSTRUCTURED LANGUAGE DEVELOPER DATE Assembly Language 1949 FORTRAN John Backus 1957 COBOL CODASYL, ANSI, ISO 1959 JOSS Cliff Shaw, RAND 1963 BASIC John G. Kemeny, Thomas E. Kurtz 1964 TELCOMP BBN 1965 MUMPS Neil Pappalardo 1966 FOCAL Richard Merrill, DEC 1968 STRUCTURED LANGUAGE DEVELOPER DATE ALGOL 58 Friedrich L. Bauer, and co. 1958 ALGOL 60 Backus, Bauer and co. 1960 ABC CWI 1980 Ada United States Department of Defence 1980 Accent R NIS 1980 Action! Optimized Systems Software 1983 Alef Phil Winterbottom 1992 DASL Sun Micro-systems Laboratories 1999-2003 MODULAR LANGUAGE DEVELOPER DATE ALGOL W Niklaus Wirth, Tony Hoare 1966 APL Larry Breed, Dick Lathwell and co. 1966 ALGOL 68 A. Van Wijngaarden and co. 1968 AMOS BASIC FranÇois Lionet anConstantin Stiropoulos 1990 Alice ML Saarland University 2000 Agda Ulf Norell;Catarina coquand(1.0) 2007 Arc Paul Graham, Robert Morris and co. 2008 Bosque Mark Marron 2019 OBJECT-ORIENTED LANGUAGE DEVELOPER DATE C* Thinking Machine 1987 Actor Charles Duff 1988 Aldor Thomas J. Watson Research Center 1990 Amiga E Wouter van Oortmerssen 1993 Action Script Macromedia 1998 BeanShell JCP 1999 AngelScript Andreas Jönsson 2003 Boo Rodrigo B. -
Download Distributed Systems Free Ebook
DISTRIBUTED SYSTEMS DOWNLOAD FREE BOOK Maarten van Steen, Andrew S Tanenbaum | 596 pages | 01 Feb 2017 | Createspace Independent Publishing Platform | 9781543057386 | English | United States Distributed Systems - The Complete Guide The hope is that together, the system can maximize resources and information while preventing failures, as if one system fails, it won't affect the availability of the service. Banker's algorithm Dijkstra's algorithm DJP algorithm Prim's algorithm Dijkstra-Scholten algorithm Dekker's algorithm generalization Smoothsort Shunting-yard algorithm Distributed Systems marking algorithm Concurrent algorithms Distributed Systems algorithms Deadlock prevention algorithms Mutual exclusion algorithms Self-stabilizing Distributed Systems. Learn to code for free. For the first time computers would be able to send messages to other systems with a local IP address. The messages passed between machines contain forms of data that the systems want to share like databases, objects, and Distributed Systems. Also known as distributed computing and distributed databases, a distributed system is a collection of independent components located on different machines that share messages with each other in order to achieve common goals. To prevent infinite loops, running the code requires some amount of Ether. As mentioned in many places, one of which this great articleyou cannot have consistency and availability without partition tolerance. Because it works in batches jobs a problem arises where if your job fails — Distributed Systems need to restart the whole thing. While in a voting system an attacker need only add nodes to the network which is Distributed Systems, as free access to the network is a design targetin a CPU power based scheme an attacker faces a physical limitation: getting access to more and more powerful hardware.