{PDF} Architecture Oriented Otherwise Ebook, Epub
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
(Perry & Wolf 92) Software Architecture (Garlan & Shaw
ICS 221, Winter 2001 Software Architecture Software Architecture (Perry & Wolf 92) “Architecture is concerned with the selection of architectural elements, their interactions, and the Software Architecture constraints on those elements and their interactions necessary to provide a framework in which to satisfy the requirements and serve as a basis for the design.” David S. Rosenblum ICS 221 “Design is concerned with the modularization and detailed interfaces of the design elements, their Winter 2001 algorithms and procedures, and the data types needed to support the architecture and to satisfy the requirements.” Software Architecture Software Architecture (Garlan & Shaw 93) (Shaw & Garlan 96) “Software architecture is a level of design that goes “The architecture of a software system defines beyond the algorithms and data structures of the that system in terms of computational computation; designing and specifying the overall components and interactions among those system structure emerges as a new kind of problem. Structural issues include gross organization and components. … In addition to specifying the global control structure; protocols for communication, structure and topology of the system, the synchronization, and data access; assignment of architecture shows the correspondence functionality to design elements; physical between the requirements and elements of distribution; composition of design elements; scaling the constructed system, thereby providing and performance; and selection among design some rationale for the design decisions.” alternatives.” Analogies with Differences Between Civil and Civil Architecture Software Architecture Civil Engineering and Civil Architecture “Software systems are like cathedrals—first we are concerned with the engineering and design of build them and then we pray.” civic structures (roads, buildings, bridges, etc.) — Sam Redwine ! Multiple views ! Civil: Artist renderings, elevations, floor plans, blueprints ! Physical vs. -
Synchronization Spinlocks - Semaphores
CS 4410 Operating Systems Synchronization Spinlocks - Semaphores Summer 2013 Cornell University 1 Today ● How can I synchronize the execution of multiple threads of the same process? ● Example ● Race condition ● Critical-Section Problem ● Spinlocks ● Semaphors ● Usage 2 Problem Context ● Multiple threads of the same process have: ● Private registers and stack memory ● Shared access to the remainder of the process “state” ● Preemptive CPU Scheduling: ● The execution of a thread is interrupted unexpectedly. ● Multiple cores executing multiple threads of the same process. 3 Share Counting ● Mr Skroutz wants to count his $1-bills. ● Initially, he uses one thread that increases a variable bills_counter for every $1-bill. ● Then he thought to accelerate the counting by using two threads and keeping the variable bills_counter shared. 4 Share Counting bills_counter = 0 ● Thread A ● Thread B while (machine_A_has_bills) while (machine_B_has_bills) bills_counter++ bills_counter++ print bills_counter ● What it might go wrong? 5 Share Counting ● Thread A ● Thread B r1 = bills_counter r2 = bills_counter r1 = r1 +1 r2 = r2 +1 bills_counter = r1 bills_counter = r2 ● If bills_counter = 42, what are its possible values after the execution of one A/B loop ? 6 Shared counters ● One possible result: everything works! ● Another possible result: lost update! ● Called a “race condition”. 7 Race conditions ● Def: a timing dependent error involving shared state ● It depends on how threads are scheduled. ● Hard to detect 8 Critical-Section Problem bills_counter = 0 ● Thread A ● Thread B while (my_machine_has_bills) while (my_machine_has_bills) – enter critical section – enter critical section bills_counter++ bills_counter++ – exit critical section – exit critical section print bills_counter 9 Critical-Section Problem ● The solution should ● enter section satisfy: ● critical section ● Mutual exclusion ● exit section ● Progress ● remainder section ● Bounded waiting 10 General Solution ● LOCK ● A process must acquire a lock to enter a critical section. -
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. -
The Deadlock Problem
The deadlock problem More deadlocks mutex_t m1, m2; Same problem with condition variables void p1 (void *ignored) { • lock (m1); - Suppose resource 1 managed by c1, resource 2 by c2 lock (m2); - A has 1, waits on 2, B has 2, waits on 1 /* critical section */ c c unlock (m2); Or have combined mutex/condition variable unlock (m1); • } deadlock: - lock (a); lock (b); while (!ready) wait (b, c); void p2 (void *ignored) { unlock (b); unlock (a); lock (m2); - lock (a); lock (b); ready = true; signal (c); lock (m1); unlock (b); unlock (a); /* critical section */ unlock (m1); One lesson: Dangerous to hold locks when crossing unlock (m2); • } abstraction barriers! This program can cease to make progress – how? - I.e., lock (a) then call function that uses condition variable • Can you have deadlock w/o mutexes? • 1/15 2/15 Deadlocks w/o computers Deadlock conditions 1. Limited access (mutual exclusion): - Resource can only be shared with finite users. 2. No preemption: - once resource granted, cannot be taken away. Real issue is resources & how required • 3. Multiple independent requests (hold and wait): E.g., bridge only allows traffic in one direction - don’t ask all at once (wait for next resource while holding • - Each section of a bridge can be viewed as a resource. current one) - If a deadlock occurs, it can be resolved if one car backs up 4. Circularity in graph of requests (preempt resources and rollback). All of 1–4 necessary for deadlock to occur - Several cars may have to be backed up if a deadlock occurs. • Two approaches to dealing with deadlock: - Starvation is possible. -
Designing Software Architecture to Support Continuous Delivery and Devops: a Systematic Literature Review
Designing Software Architecture to Support Continuous Delivery and DevOps: A Systematic Literature Review Robin Bolscher and Maya Daneva University of Twente, Drienerlolaan 5, Enschede, The Netherlands [email protected], [email protected] Keywords: Software Architecture, Continuous Delivery, Continuous Integration, DevOps, Deployability, Systematic Literature Review, Micro-services. Abstract: This paper presents a systematic literature review of software architecture approaches that support the implementation of Continuous Delivery (CD) and DevOps. Its goal is to provide an understanding of the state- of-the-art on the topic, which is informative for both researchers and practitioners. We found 17 characteristics of a software architecture that are beneficial for CD and DevOps adoption and identified ten potential software architecture obstacles in adopting CD and DevOps in the case of an existing software system. Moreover, our review indicated that micro-services are a dominant architectural style in this context. Our literature review has some implications: for researchers, it provides a map of the recent research efforts on software architecture in the CD and DevOps domain. For practitioners, it describes a set of software architecture principles that possibly can guide the process of creating or adapting software systems to fit in the CD and DevOps context. 1 INTRODUCTION designing new software architectures tailored for CD and DevOps practices. The practice of releasing software early and often has For clarity, before elaborating on the subject of been increasingly more adopted by software this SLR, we present the definitions of the concepts organizations (Fox et al., 2014) in order to stay that we will address: Software architecture of a competitive in the software market. -
Fair K Mutual Exclusion Algorithm for Peer to Peer Systems ∗
Fair K Mutual Exclusion Algorithm for Peer To Peer Systems ∗ Vijay Anand Reddy, Prateek Mittal, and Indranil Gupta University of Illinois, Urbana Champaign, USA {vkortho2, mittal2, indy}@uiuc.edu Abstract is when multiple clients are simultaneously downloading a large multimedia file, e.g., [3, 12]. Finally applications k-mutual exclusion is an important problem for resource- where a service has limited computational resources will intensive peer-to-peer applications ranging from aggrega- also benefit from a k mutual exclusion primitive, preventing tion to file downloads. In order to be practically useful, scenarios where all the nodes of the p2p system simultane- k-mutual exclusion algorithms not only need to be safe and ously overwhelm the server. live, but they also need to be fair across hosts. We pro- The k mutual exclusion problem involves a group of pro- pose a new solution to the k-mutual exclusion problem that cesses, each of which intermittently requires access to an provides a notion of time-based fairness. Specifically, our identical resource called the critical section (CS). A k mu- algorithm attempts to minimize the spread of access time tual exclusion algorithm must satisfy both safety and live- for the critical resource. While a client’s access time is ness. Safety means that at most k processes, 1 ≤ k ≤ n, the time between it requesting and accessing the resource, may be in the CS at any given time. Liveness means that the spread is defined as a system-wide metric that measures every request for critical section access is satisfied in finite some notion of the variance of access times across a homo- time. -
Software Engineering (SE) 1
Software Engineering (SE) 1 SE 352 | OBJECT-ORIENTED ENTERPRISE APPLICATION DEVELOPMENT SOFTWARE ENGINEERING | 4 quarter hours (Undergraduate) (SE) This course focuses on applying object-oriented techniques in the design and development of software systems for enterprise applications. Topics SE 325 | INTRODUCTION TO SOFTWARE ENGINEERING | 4 quarter hours include component architecture, such as Java Beans and Enterprise (Undergraduate) Java Beans, GUI components, such as Swing, database connectivity and This course introduces students to the activities performed at each object repositories, server application integration using technologies stage of the development process so that they can understand the full such as servlets, Java Server Pages, JDBC and RMI, security and lifecycle context of specific tasks such as coding and testing. Topics will internationalization. PREREQUISITE(S): CSC 301. include software development processes, domain modeling, requirements CSC 301 is a prerequisite for this class. elicitation and specification, architectural design and analysis, product SE 356 | SOFTWARE DEVELOPMENT FOR MOBILE AND WIRELESS and process level metrics, configuration management, quality assurance SYSTEMS | 4 quarter hours activities including user acceptance testing and unit testing, project (Undergraduate) management skills such as risk analysis, effort estimation, project This course will focus on the unique aspects of developing software release planning, and software engineering ethics. applications for mobile and wireless systems, such as personal digital CSC 301 or CSC 393 is a prerequisite for this class. assistant (PDA) devices and mobile phones. Topics will include user SE 330 | OBJECT ORIENTED MODELING | 4 quarter hours interface design for small screens with restricted input modalities, data (Undergraduate) synchronization for mobile databases as well as wireless programming Object-oriented modeling techniques for analysis and design. -
Sorting Algorithm 1 Sorting Algorithm
Sorting algorithm 1 Sorting algorithm In computer science, a sorting algorithm is an algorithm that puts elements of a list in a certain order. The most-used orders are numerical order and lexicographical order. Efficient sorting is important for optimizing the use of other algorithms (such as search and merge algorithms) that require sorted lists to work correctly; it is also often useful for canonicalizing data and for producing human-readable output. More formally, the output must satisfy two conditions: 1. The output is in nondecreasing order (each element is no smaller than the previous element according to the desired total order); 2. The output is a permutation, or reordering, of the input. Since the dawn of computing, the sorting problem has attracted a great deal of research, perhaps due to the complexity of solving it efficiently despite its simple, familiar statement. For example, bubble sort was analyzed as early as 1956.[1] Although many consider it a solved problem, useful new sorting algorithms are still being invented (for example, library sort was first published in 2004). Sorting algorithms are prevalent in introductory computer science classes, where the abundance of algorithms for the problem provides a gentle introduction to a variety of core algorithm concepts, such as big O notation, divide and conquer algorithms, data structures, randomized algorithms, best, worst and average case analysis, time-space tradeoffs, and lower bounds. Classification Sorting algorithms used in computer science are often classified by: • Computational complexity (worst, average and best behaviour) of element comparisons in terms of the size of the list . For typical sorting algorithms good behavior is and bad behavior is . -
Composition of Software Architectures Christos Kloukinas
Composition of Software Architectures Christos Kloukinas To cite this version: Christos Kloukinas. Composition of Software Architectures. Computer Science [cs]. Université Rennes 1, 2002. English. tel-00469412 HAL Id: tel-00469412 https://tel.archives-ouvertes.fr/tel-00469412 Submitted on 1 Apr 2010 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. Composition of Software Architectures - Ph.D. Thesis - - Presented in front of the University of Rennes I, France - - English Version - Christos Kloukinas Jury Members : Jean-Pierre Banâtre Jacky Estublier Cliff Jones Valérie Issarny Nicole Lévy Joseph Sifakis February 12, 2002 Résumé Les systèmes informatiques deviennent de plus en plus complexes et doivent offrir un nombre croissant de propriétés non fonctionnelles, comme la fiabi- lité, la disponibilité, la sécurité, etc.. De telles propriétés sont habituellement fournies au moyen d’un intergiciel qui se situe entre le matériel (et le sys- tème d’exploitation) et le niveau applicatif, masquant ainsi les spécificités du système sous-jacent et permettant à des applications d’être utilisées avec dif- férentes infrastructures. Cependant, à mesure que les exigences de propriétés non fonctionnelles augmentent, les architectes système se trouvent confron- tés au cas où aucun intergiciel disponible ne fournit toutes les propriétés non fonctionnelles visées. -
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. -
Introduction to Software Architecture
Introduction to Software Architecture Imed Hammouda Chalmers | University of Gothenburg Who am I? • Associate Professor of Software Engineering, previously in Tampere, Finland • Research interests – Software Architecture, Open Source, Software Ecosystems, Software Development Methods and Tools, Variability Management • Developing and supporting open software architectures • Studying socio-technical dependencies in software development • Software ecosystems • Coordinates: [email protected], [email protected] • Room 416, floor 4, Jupiter building, Campus Lindholmen • Phone +46 31 772 60 40 Introduction to Software Architecture 2 • What is software architecture? • Architectural drivers • Addressing architectural drivers • Architectural views • Example system Introduction to Software Architecture 3 What is Software Architecture? • Software Architecture is the global organization of a software system, including – the division of software into subsystems/components, – policies according to which these subsystems interact, – the definition of their interfaces. T. C. Lethbridge & R. Laganière Introduction to Software Architecture 4 What is Software Architecture? • "The software architecture of a program or computing system is the structure or structures of the system, which comprise software components, the externally visible properties of those components, and the relationships among them." Len Bass Introduction to Software Architecture 5 What is Software Architecture? • “fundamental concepts or properties of a system in its environment -
In the Beginning... Example Critical Sections / Mutual Exclusion Critical
Temporal relations • Instructions executed by a single thread are totally CSE 451: Operating Systems ordered Spring 2013 – A < B < C < … • Absent synchronization, instructions executed by distinct threads must be considered unordered / Module 7 simultaneous Synchronization – Not X < X’, and not X’ < X Ed Lazowska [email protected] Allen Center 570 © 2013 Gribble, Lazowska, Levy, Zahorjan © 2013 Gribble, Lazowska, Levy, Zahorjan 2 Critical Sections / Mutual Exclusion Example: ExampleIn the beginning... • Sequences of instructions that may get incorrect main() Y-axis is “time.” results if executed simultaneously are called critical A sections Could be one CPU, could pthread_create() • (We also use the term race condition to refer to a be multiple CPUs (cores). situation in which the results depend on timing) B foo() A' • Mutual exclusion means “not simultaneous” – A < B or B < A • A < B < C – We don’t care which B' • A' < B' • Forcing mutual exclusion between two critical section C • A < A' executions is sufficient to ensure correct execution – • C == A' guarantees ordering • C == B' • One way to guarantee mutually exclusive execution is using locks © 2013 Gribble, Lazowska, Levy, Zahorjan 3 © 2013 Gribble, Lazowska, Levy, Zahorjan 4 CriticalCritical sections When do critical sections arise? is the “happens-before” relation • One common pattern: T1 T2 T1 T2 T1 T2 – read-modify-write of – a shared value (variable) – in code that can be executed concurrently (Note: There may be only one copy of the code (e.g., a procedure), but it