The Re Exive CHAM and the Join-Calculus 1 Introduction
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Concepts of Concurrent Programming Summary of the Course in Spring 2011 by Bertrand Meyer and Sebastian Nanz
Concepts of Concurrent Programming Summary of the course in spring 2011 by Bertrand Meyer and Sebastian Nanz Stefan Heule 2011-05-28 Licence: Creative Commons Attribution-Share Alike 3.0 Unported (http://creativecommons.org/licenses/by-sa/3.0/) Contents 1 Introduction .......................................................................................................................................... 4 1.1 Ambdahl’s Law .............................................................................................................................. 4 1.2 Basic Notions ................................................................................................................................. 4 1.2.1 Multiprocessing ..................................................................................................................... 4 1.2.2 Multitasking .......................................................................................................................... 4 1.2.3 Definitions ............................................................................................................................. 4 1.2.4 The Interleaving Semantics ................................................................................................... 5 1.3 Transition Systems and LTL ........................................................................................................... 6 1.3.1 Syntax and Semantics of Linear-Time Temporal Logic.......................................................... 7 1.3.2 Safety and Liveness Properties -
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. -
Implementing a Transformation from BPMN to CSP+T with ATL: Lessons Learnt
Implementing a Transformation from BPMN to CSP+T with ATL: Lessons Learnt Aleksander González1, Luis E. Mendoza1, Manuel I. Capel2 and María A. Pérez1 1 Processes and Systems Department, Simón Bolivar University PO Box 89000, Caracas, 1080-A, Venezuela 2 Software Engineering Department, University of Granada Aynadamar Campus, 18071, Granada, Spain Abstract. Among the challenges to face in order to promote the use of tech- niques of formal verification in organizational environments, there is the possi- bility of offering the integration of features provided by a Model Transforma- tion Language (MTL) as part of a tool very used by business analysts, and from which formal specifications of a model can be generated. This article presents the use of MTL ATLAS Transformation Language (ATL) as a transformation artefact within the domains of Business Process Modelling Notation (BPMN) and Communicating Sequential Processes + Time (CSP+T). It discusses the main difficulties encountered and the lessons learnt when building BTRANSFORMER; a tool developed for the Eclipse platform, which allows us to generate a formal specification in the CSP+T notation from a business process model designed with BPMN. This learning is valid for those who are interested in formalizing a Business Process Modelling Language (BPML) by means of a process calculus or another formal notation. 1 Introduction Business Processes (BP) must be properly and formally specified in order to be able to verify properties, such as scope, structure, performance, capacity, structural consis- tency and concurrency, i.e., those properties of BP which can provide support to the critical success factors of any organization. Formal specification languages and proc- ess algebras, which allow for the exhaustive verification of BP behaviour [17], are used to carry out the formalization of models obtained from Business Process Model- ling (BPM). -
Bisimulations in the Join-Calculus
Bisimulations in the Join-Calculus C´edricFournet a Cosimo Laneve b,1 aMicrosoft Research, 1 Guildhall Street, Cambridge, U.K. b Dipartimento di Scienze dell’Informazione, Universit`adi Bologna, Mura Anteo Zamboni 7, 40127 Bologna, Italy. Abstract We develop a theory of bisimulations in the join-calculus. We introduce a refined operational model that makes interactions with the environment explicit, and dis- cuss the impact of the lexical scope discipline of the join-calculus on its extensional semantics. We propose several formulations of bisimulation and establish that all formulations yield the same equivalence. We prove that this equivalence is finer than barbed congruence, but that both relations coincide in the presence of name matching. Key words: asynchronous processes; barbed congruence; bisimulation; chemical semantics; concurrency; join-calculus; locality; name matching; pi-calculus. 1 Introduction The join-calculus is a recent formalism for modeling mobile systems [15,17]. Its main motivation is to relate two crucial issues in concurrency: distributed implementation and formal semantics. To this end, the join-calculus enforces a strict lexical scope discipline over the channel names that appear in processes: names can be sent and received, but their input capabilities cannot be affected by the receivers. This is the locality property. 2 Locality yields a realistic distributed model, because the communication prim- itives of the calculus can be directly implemented via standard primitives of 1 This work is partly supported by the ESPRIT CONFER-2 WG-21836 2 The term locality is a bit overloaded in the literature; here, names are locally defined inasmuch as no external definition may interfere; this is the original meaning of locality in the chemical semantics of Banˆatre et al. -
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. -
Deadlock Analysis of Wait-Notify Coordination Laneve Cosimo, Luca Padovani
Deadlock Analysis of Wait-Notify Coordination Laneve Cosimo, Luca Padovani To cite this version: Laneve Cosimo, Luca Padovani. Deadlock Analysis of Wait-Notify Coordination. The Art of Modelling Computational Systems: A Journey from Logic and Concurrency to Security and Privacy - Essays Dedicated to Catuscia Palamidessi on the Occasion of Her 60th Birthday, Nov 2019, Paris, France. hal-02430351 HAL Id: hal-02430351 https://hal.archives-ouvertes.fr/hal-02430351 Submitted on 7 Jan 2020 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. Deadlock Analysis of Wait-Notify Coordination Cosimo Laneve1[0000−0002−0052−4061] and Luca Padovani2[0000−0001−9097−1297] 1 Dept. of Computer Science and Engineering, University of Bologna { INRIA Focus 2 Dipartimento di Informatica, Universit`adi Torino Abstract. Deadlock analysis of concurrent programs that contain co- ordination primitives (wait, notify and notifyAll) is notoriously chal- lenging. Not only these primitives affect the scheduling of processes, but also notifications unmatched by a corresponding wait are silently lost. We design a behavioral type system for a core calculus featuring shared objects and Java-like coordination primitives. The type system is based on a simple language of object protocols { called usages { to determine whether objects are used reliably, so as to guarantee deadlock freedom. -
The Beacon Calculus: a Formal Method for the flexible and Concise Modelling of Biological Systems
bioRxiv preprint doi: https://doi.org/10.1101/579029; this version posted November 26, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. The Beacon Calculus: A formal method for the flexible and concise modelling of biological systems Michael A. Boemo1∗ Luca Cardelli2 Conrad A. Nieduszynski3 1Department of Pathology, University of Cambridge 2Department of Computer Science, University of Oxford 3Genome Damage and Stability Centre, University of Sussex Abstract Biological systems are made up of components that change their actions (and interactions) over time and coordinate with other components nearby. Together with a large state space, the complexity of this behaviour can make it difficult to create concise mathematical models that can be easily extended or modified. This paper introduces the Beacon Calculus, a process algebra designed to simplify the task of modelling interacting biological components. Its breadth is demonstrated by creating models of DNA replication dynamics, the gene expression dynamics in response to DNA methylation damage, and a multisite phosphorylation switch. The flexibility of these models is shown by adapting the DNA replication model to further include two topics of interest from the literature: cooperative origin firing and replication fork barriers. The Beacon Calculus is supported with the open-source simulator bcs (https://github.com/MBoemo/bcs.git) to allow users to develop and simulate their own models. Author summary Simulating a model of a biological system can suggest ideas for future experiments and help ensure that conclusions about a mechanism are consistent with data. -
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 -
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.