The advent of new architectures and computing platforms means that synchronization and concurrent computing are among the most important topics in computing science. Concurrent programs are made up of cooperating entities -- processors, processes, agents, peers, sensors -- and synchronization is the set of concepts, rules and mechanisms that allow them to coordinate their local computations in order to realize a common task. This book is devoted to the most difficult part of concurrent programming, namely synchronization concepts, techniques and principles when the cooperating entities are asynchronous, communicate through a shared memory, and may experience failures. Synchronization is no longer a set of tricks but, due to research results in recent decades, it relies today on sane scientific foundations as explained in this book.

In this book the author explains synchronization and the implementation of concurrent objects, presenting in a uniform and comprehensive way the major theoretical and practical results of the past 30 years. Among the key features of the book are a new look at lock-based synchronization (mutual exclusion, semaphores, monitors, path expressions); an introduction to the atomicity consistency criterion and its properties and a specific chapter on transactional memory; an introduction to mutex-freedom and associated progress conditions such as obstruction-freedom and wait-freedom; a presentation of Lamport's hierarchy of safe, regular and atomic registers and associated wait-free constructions; a description of numerous wait-free constructions of concurrent objects (queues, stacks, weak counters, snapshot objects, renaming objects, etc.); a presentation of the computability power of concurrent objects including the notions of universal construction, consensus number and the associated Herlihy's hierarchy; and a survey of failure detector-based constructions of consensus objects.

The book is suitable for advanced undergraduate students and graduate students in computer science or computer engineering, graduate students in mathematics interested in the foundations of process synchronization, and practitioners and engineers who need to produce correct concurrent software. The reader should have a basic knowledge of algorithms and operating systems.

Design thinking as a user-centric innovation method has become more and more widespread during the past years. An increasing number of people and institutions have experienced its innovative power. While at the same time the demand has grown for a deep, evidence-based understanding of the way design thinking functions. This challenge is addressed by the Design Thinking Research Program between Stanford University, Palo Alto, USA and Hasso Plattner Institute, Potsdam, Germany. Summarizing the outcomes of the 5th program year, this book imparts the scientific findings gained by the researchers through their investigations, experiments and studies.

The method of design thinking works when applied with diligence and insight. With this book and the underlying research projects, we aim to understand the innovation process of design thinking and the people behind it. The contributions ultimately center on the issue of building innovators. The focus of the investigation is on what people are doing and thinking when engaged in creative design innovation and how their innovation work can be supported.Therefore, within three topic areas, various frameworks, methodologies, mind sets, systems and tools are explored and further developed. The book begins with an assessment of crucial factors for innovators such as empathy and creativity, the second part addresses the improvement of team collaboration and finally we turn to specific tools and approaches which ensure information transfer during the design process. All in all, the contributions shed light and show deeper insights how to support the work of design teams in order to systematically and successfully develop innovations and design progressive solutions for tomorrow.

This book examines the requirements, risks, and solutions to improve the security and quality of complex cyber-physical systems (C-CPS), such as production systems, power plants, and airplanes, in order to ascertain whether it is possible to protect engineering organizations against cyber threats and to ensure engineering project quality. The book consists of three parts that logically build upon each other. Part I "Product Engineering of Complex Cyber-Physical Systems" discusses the structure and behavior of engineering organizations producing complex cyber-physical systems, providing insights into processes and engineering activities, and highlighting the requirements and border conditions for secure and high-quality engineering. Part II "Engineering Quality Improvement" addresses quality improvements with a focus on engineering data generation, exchange, aggregation, and use within an engineering organization, and the need for proper data modeling and engineering-result validation. Lastly, Part III "Engineering Security Improvement" considers security aspects concerning C-CPS engineering, including engineering organizations' security assessments and engineering data management, security concepts and technologies that may be leveraged to mitigate the manipulation of engineering data, as well as design and run-time aspects of secure complex cyber-physical systems. The book is intended for several target groups: it enables computer scientists to identify research issues related to the development of new methods, architectures, and technologies for improving quality and security in multi-disciplinary engineering, pushing forward the current state of the art. It also allows researchers involved in the engineering of C-CPS to gain a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in their future research and development activities. Lastly, it offers practicing engineers and managers with engineering backgrounds insights into the benefits and limitations of applicable methods, architectures, and technologies for selected use cases.

The general theme of this conference is notations, methods, and tool support for the calculation of programs from specifications. The purpose of this working conference is to present the results of ongoing research, descriptions of existing and proposed systems, and applications to the production of practical software.

Users increasingly demand more from their software than ever before more features, fewer errors, faster runtimes. To deliver the best quality products possible, software engineers are constantly in the process of employing novel tools in developing the latest software applications. Progressions and Innovations in Model-Driven Software Engineering investigates the most recent and relevant research on model-driven engineering. Within its pages, researchers and professionals in the field of software development, as well as academics and students of computer science, will find an up-to-date discussion of scientific literature on the topic, identifying opportunities and advantages, and complexities and challenges, inherent in the future of software engineering.

"Iterating Infusion: Clearer Views of Objects, Classes, and Systems" is a one-of-a-kind book, not dependent on any single technology. Rather, it provides a way to integrate the most efficient techniques from a variety of programming methods, in a manner that makes designing and programming software look easy.

"Iterating Infusion" presents comprehensive tools for you to best manage and work with object orientation. These include simplified fundamental concepts, popular language comparisons, advanced designing strategies, a broad usage progression, thorough design notations (interaction algebra), and data-oriented (fundamentally-OO) languages.

The title, "Iterating Infusion," alludes to the fact that any system has multiple, coexisting functional levels and that new levelsboth lower and higherare continually added to the same functional area. The practical effect is to bring processes into more focus, always clarifying the vague. The extreme form of this is when separate but compatible technologies are brought together to create advancements; these can be baby-steps or great leaps, with varying amounts of effort. In more general terms, the same thing in a different context can take on much more power. And actually, this phenomenon is at the heart of object-oriented software.

Readers have been confirming that, compared to books on just low-level details, "Iterating Infusion" presents cohesive insights that allow you to solve more problems with the same effort in more key places.

The idea for this workshop originated when I came across and read Martin Zelkowitz's book on Requirements for Software Engineering Environments (the proceedings of a small workshop held at the University of Maryland in 1986). Although stimulated by the book I was also disappointed in that it didn't adequately address two important questions - "Whose requirements are these?" and "Will the environment which meets all these requirements be usable by software engineers?." And thus was the decision made to organise this workshop which would explicitly address these two questions. As time went by setting things up, it became clear that our workshop would happen more than five years after the Maryland workshop and thus, at the same time as addressing the two questions above, this workshop would attempt to update the Zelkowitz approach. Hence the workshop acquired two halves, one dominated by discussion of what we already know about usability problems in software engineering and the other by discussion of existing solutions (technical and otherwise) to these problems. This scheme also provided a good format for bringing together those in the HeI community concerned with the human factors of software engineering and those building tools to solve acknowledged, but rarely understood problems.

Welcome to the 5th International Conference on Open Source Systems! It is quite an achievement to reach the five-year mark - that's the sign of a successful enterprise. This annual conference is now being recognized as the primary event for the open source research community, attracting not only high-quality papers, but also building a community around a technical program, a collection of workshops, and (starting this year) a Doctoral Consortium. Reaching this milestone reflects the efforts of many people, including the conference founders, as well as the organizers and participants in the previous conferences. My task has been easy, and has been greatly aided by the hard work of Kevin Crowston and Cornelia Boldyreff, the Program Committee, as well as the Organizing Team led by Bjoern Lundell. All of us are also grateful to our attendees, especially in the difficult economic climate of 2009. We hope the participants found the conference valuable both for its technical content and for its personal networking opportunities. To me, it is interesting to look back over the past five years, not just at this conference, but at the development and acceptance of open source software. Since 2004, the business and commercial side of open source has grown enormously. At that time, there were only a handful of open source businesses, led by RedHat and its Linux distribution. Companies such as MySQL and JBoss were still quite small.

This book is about a significant step forward in software development. It brings state-of-the-art ontology reasoning into mainstream software development and its languages. Ontology Driven Software Development is the essential, comprehensive resource on enabling technologies, consistency checking and process guidance for ontology-driven software development (ODSD). It demonstrates how to apply ontology reasoning in the lifecycle of software development, using current and emerging standards and technologies. You will learn new methodologies and infrastructures, additionally illustrated using detailed industrial case studies. The book will help you: Learn how ontology reasoning allows validations of structure models and key tasks in behavior models. Understand how to develop ODSD guidance engines for important software development activities, such as requirement engineering, domain modeling and process refinement. Become familiar with semantic standards, such as the Web Ontology Language (OWL) and the SPARQL query language. Make use of ontology reasoning, querying and justification techniques to integrate software models and to offer guidance and traceability supports. This book is helpful for undergraduate students and professionals who are interested in studying how ontologies and related semantic reasoning can be applied to the software development process. In addition, itwill also be useful for postgraduate students, professionals and researchers who are going to embark on their research in areas related to ontology or software engineering.

This textbook introduces the concept of embedded systems with exercises using Arduino Uno. It is intended for advanced undergraduate and graduate students in computer science, computer engineering, and electrical engineering programs. It contains a balanced discussion on both hardware and software related to embedded systems, with a focus on co-design aspects. Embedded systems have applications in Internet-of-Things (IoT), wearables, self-driving cars, smart devices, cyberphysical systems, drones, and robotics. The hardware chapter discusses various microcontrollers (including popular microcontroller hardware examples), sensors, amplifiers, filters, actuators, wired and wireless communication topologies, schematic and PCB designs, and much more. The software chapter describes OS-less programming, bitmath, polling, interrupt, timer, sleep modes, direct memory access, shared memory, mutex, and smart algorithms, with lots of C-code examples for Arduino Uno. Other topics discussed are prototyping, testing, verification, reliability, optimization, and regulations. Appropriate for courses on embedded systems, microcontrollers, and instrumentation, this textbook teaches budding embedded system programmers practical skills with fun projects to prepare them for industry products. Introduces embedded systems for wearables, Internet-of-Things (IoT), robotics, and other smart devices; Offers a balanced focus on both hardware and software co-design of embedded systems; Includes exercises, tutorials, and assignments.

"Meta-Programming and Model-Driven Meta-Program Development: Principles, Processes and Techniques" presents an overall analysis of meta-programming, focusing on insights of meta-programming techniques, heterogeneous meta-program development processes in the context of model-driven, feature-based and transformative approaches.

The fundamental concepts of meta-programming are still not thoroughly understood, in this well organized book divided into three parts the authors help to address this. Chapters include: Taxonomy of fundamental concepts of meta-programming; Concept of structural heterogeneous meta-programming based on the original meta-language; Model-driven concept and feature-based modeling to the development process of meta-programs; Equivalent meta-program transformations and metrics to evaluate complexity of feature-based models and meta-programs; Variety of academic research case studies within different application domains to experimentally verify the soundness of the investigated approaches.

Both authors are professors at Kaunas University of Technology with 15 years research and teaching experience in the field. "Meta-Programming and Model-Driven Meta-Program Development: Principles, Processes and Techniques" is aimed at post-graduates in computer science and software engineering and researchers and program system developers wishing to extend their knowledge in this rapidly evolving sector of science and technology.

The Lean Approach to Digital Transformation: From Customer to Code and From Code to Customer is organized into three parts that expose and develop the three capabilities that are essential for a successful digital transformation: 1. Understanding how to co-create digital services with users, whether they are customers or future customers. This ability combines observation, dialogue, and iterative experimentation. The approach proposed in this book is based on the Lean Startup approach, according to an extended vision that combines Design Thinking and Growth Hacking. Companies must become truly "customer-centric", from observation and listening to co-development. The revolution of the digital age of the 21st century is that customer orientation is more imperative -- the era of abundance, usages rate of change, complexity of experiences, and shift of power towards communities -- are easier, using digital tools and digital communities. 2. Developing an information system (IS) that is the backbone of the digital transformation - called "exponential information system" to designate an open IS (in particular on its borders), capable of interfacing and combining with external services, positioned as a player in software ecosystems and built for processing scalable and dynamic data flows. The exponential information system is constantly changing and it continuously absorbs the best of information processing technology, such as Artificial Intelligence and Machine Learning. 3. Building software "micro-factories" that produce service platforms, which are called "Lean software factories." This "software factory" concept covers the integration of agile methods, tooling and continuous integration and deployment practices, a customer-oriented product approach, and a platform approach based on modularity, as well as API-based architecture and openness to external stakeholders. This software micro-factory is the foundation that continuously produces and provides constantly evolving services. These three capabilities are not unique or specific to this book, they are linked to other concepts such as agile methods, product development according to lean principles, software production approaches such as CICD (continuous integration and deployment) or DevOps. This book weaves a common frame of reference for all these approaches to derive more value from the digital transformation and to facilitate its implementation. The title of the book refers to the "lean approach to digital transformation" because the two underlying frameworks, Lean Startup and Lean Software Factory, are directly inspired by Lean, in the sense of the Toyota Way. The Lean approach is present from the beginning to the end of this book -- it provides the framework for customer orientation and the love of a job well done, which are the conditions for the success of a digital transformation.

"Specification and transformation of programs" is short for a methodology of software development where, from a formal specification of a problem to be solved, programs correctly solving that problem are constructed by stepwise application of formal, semantics-preserving transformation rules. The approach considers programming as a formal activity. Consequently, it requires some mathematical maturity and, above all, the will to try something new. A somewhat experienced programmer or a third- or fourth-year student in computer science should be able to master most of this material - at least, this is the level I have aimed at. This book is primarily intended as a general introductory textbook on transformational methodology. As with any methodology, reading and understanding is necessary but not sufficient. Therefore, most of the chapters contain a set of exercises for practising as homework. Solutions to these exercises exist and can, in principle, be obtained at nominal cost from the author upon request on appropriate letterhead. In addition, the book also can be seen as a comprehensive account of the particular transformational methodology developed within the Munich CIP project.

This edited book presents scientific results of the 21st ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD2021-Winter) which was held on January 28-30, at Ho Chi Minh City, Vietnam. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way and research results about all aspects (theory, applications, and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 18 of most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

For real-time systems, the worst-case execution time (WCET) is the key objective to be considered. Traditionally, code for real-time systems is generated without taking this objective into account and the WCET is computed only after code generation. Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems presents the first comprehensive approach integrating WCET considerations into the code generation process. Based on the proposed reconciliation between a compiler and a timing analyzer, a wide range of novel optimization techniques is provided. Among others, the techniques cover source code and assembly level optimizations, exploit machine learning techniques and address the design of modern systems that have to meet multiple objectives.

Using these optimizations, the WCET of real-time applications can be reduced by about 30% to 45% on the average. This opens opportunities for decreasing clock speeds, costs and energy consumption of embedded processors. The proposed techniques can be used for all types real-time systems, including automotive and avionics IT systems.

At the dawn of the 21st century and the information age, communication and c- puting power are becoming ever increasingly available, virtually pervading almost every aspect of modern socio-economical interactions. Consequently, the potential for realizing a signi?cantly greater number of technology-mediated activities has emerged. Indeed, many of our modern activity ?elds are heavily dependant upon various underlying systems and software-intensive platforms. Such technologies are commonly used in everyday activities such as commuting, traf?c control and m- agement, mobile computing, navigation, mobile communication. Thus, the correct function of the forenamed computing systems becomes a major concern. This is all the more important since, in spite of the numerous updates, patches and ?rmware revisions being constantly issued, newly discovered logical bugs in a wide range of modern software platforms (e. g. , operating systems) and software-intensive systems (e. g. , embedded systems) are just as frequently being reported. In addition, many of today's products and services are presently being deployed in a highly competitive environment wherein a product or service is succeeding in most of the cases thanks to its quality to price ratio for a given set of features. Accordingly, a number of critical aspects have to be considered, such as the ab- ity to pack as many features as needed in a given product or service while c- currently maintaining high quality, reasonable price, and short time -to- market.

This book analyses quantitative open source software (OSS) reliability assessment and its applications, focusing on three major topic areas: the Fundamentals of OSS Quality/Reliability Measurement and Assessment; the Practical Applications of OSS Reliability Modelling; and Recent Developments in OSS Reliability Modelling. Offering an ideal reference guide for graduate students and researchers in reliability for open source software (OSS) and modelling, the book introduces several methods of reliability assessment for OSS including component-oriented reliability analysis based on analytic hierarchy process (AHP), analytic network process (ANP), and non-homogeneous Poisson process (NHPP) models, the stochastic differential equation models and hazard rate models. These measurement and management technologies are essential to producing and maintaining quality/reliable systems using OSS.

This book draws new attention to domain-specific conceptual modeling by presenting the work of thought leaders who have designed and deployed specific modeling methods. It provides hands-on guidance on how to build models in a particular domain, such as requirements engineering, business process modeling or enterprise architecture. In addition to these results, it also puts forward ideas for future developments. All this is enriched with exercises, case studies, detailed references and further related information. All domain-specific methods described in this volume also have a tool implementation within the OMiLAB Collaborative Environment - a dedicated research and experimentation space for modeling method engineering at the University of Vienna, Austria - making these advances accessible to a wider community of further developers and users. The collection of works presented here will benefit experts and practitioners from academia and industry alike, including members of the conceptual modeling community as well as lecturers and students.

This book addresses action research (AR), one of the main research methodologies used for academia-industry research collaborations. It elaborates on how to find the right research activities and how to distinguish them from non-significant ones. Further, it details how to glean lessons from the research results, no matter whether they are positive or negative. Lastly, it shows how companies can evolve and build talents while expanding their product portfolio. The book's structure is based on that of AR projects; it sequentially covers and discusses each phase of the project. Each chapter shares new insights into AR and provides the reader with a better understanding of how to apply it. In addition, each chapter includes a number of practical use cases or examples. Taken together, the chapters cover the entire software lifecycle: from problem diagnosis to project (or action) planning and execution, to documenting and disseminating results, including validity assessments for AR studies. The goal of this book is to help everyone interested in industry-academia collaborations to conduct joint research. It is for students of software engineering who need to learn about how to set up an evaluation, how to run a project, and how to document the results. It is for all academics who aren't afraid to step out of their comfort zone and enter industry. It is for industrial researchers who know that they want to do more than just develop software blindly. And finally, it is for stakeholders who want to learn how to manage industrial research projects and how to set up guidelines for their own role and expectations.

The subject of this book is the control of software engineering. The rapidly increasing demand for software is accompanied by a growth in the number of products on the market, as well as their size and complexity. Our ability to control software engineering is hardly keeping pace with this growth. As a result, software projects are often late, software products sometimes lack the required quality and the productivity improvements achieved by software engineering are insufficient to keep up with the demand This book describes ways to improve software engineering control. It argues that this should be expanded to include control of the development, maintenance and reuse of software, thus making it possible to apply many of the ideas and concepts that originate in production control and quality control. The book is based on research and experience accumulated over a number of years. During this period I had two employers: Eindhoven University of Technology and Philips Electronics. Research is not a one-man activity and I would like to thank the following persons for their contributions to the successful completion of this project. First and foremost my Ph. D. advisers Theo Bemelmans, Hans van Vliet and Fred Heemstra whose insights and experience proved invaluable at every stage. Many thanks are also due to Rob Kusters and Fred Heemstra for their patience in listening to my sometimes wild ideas and for being such excellent colleagues.

The book emphasizes the predictive models of Big Data, Genetic Algorithm, and IoT with a case study. The book illustrates the predictive models with integrated fuel consumption models for smart and safe traveling. The text is a coordinated amalgamation of research contributions and industrial applications in the field of Intelligent Transportation Systems. The advanced predictive models and research results were achieved with the case studies, deployed in real transportation environments. Features: Provides a smart traffic congestion avoidance system with an integrated fuel consumption model. Predicts traffic in short-term and regular. This is illustrated with a case study. Efficient Traffic light controller and deviation system in accordance with the traffic scenario. IoT based Intelligent Transport Systems in a Global perspective. Intelligent Traffic Light Control System and Ambulance Control System. Provides a predictive framework that can handle the traffic on abnormal days, such as weekends, festival holidays. Bunch of solutions and ideas for smart traffic development in smart cities. This book focuses on advanced predictive models along with offering an efficient solution for smart traffic management system. This book will give a brief idea of the available algorithms/techniques of big data, IoT, and genetic algorithm and guides in developing a solution for smart city applications. This book will be a complete framework for ITS domain with the advanced concepts of Big Data Analytics, Genetic Algorithm and IoT. This book is primarily aimed at IT professionals. Undergraduates, graduates and researchers in the area of computer science and information technology will also find this book useful.

Software product lines are emerging as a critical new paradigm for software development. Product lines are enabling organizations to achieve impressive time-to-market gains and cost reductions. With the increasing number of product lines and product-line researchers and practitioners, the time is right for a comprehensive examination of the issues surrounding the software product line approach. The Software Engineering Institute at Carnegie Mellon University is proud to sponsor the first conference on this important subject. This book comprises the proceedings of the First Software Product Line Conference (SPLC1), held August 28-31, 2000, in Denver, Colorado, USA. The twenty-seven papers of the conference technical program present research results and experience reports that cover all aspects of software product lines. Topics include business issues, enabling technologies, organizational issues, and life-cycle issues. Emphasis is placed on experiences in the development and fielding of product lines of complex systems, especially those that expose problems in the design, development, or evolution of software product lines. The book will be essential reading for researchers and practitioners alike.

Scientific applications involve very large computations that strain the resources of whatever computers are available. Such computations implement sophisticated mathematics, require deep scientific knowledge, depend on subtle interplay of different approximations, and may be subject to instabilities and sensitivity to external input. Software able to succeed in this domain invariably embeds significant domain knowledge that should be tapped for future use. Unfortunately, most existing scientific software is designed in an ad hoc way, resulting in monolithic codes understood by only a few developers. Software architecture refers to the way software is structured to promote objectives such as reusability, maintainability, extensibility, and feasibility of independent implementation. Such issues have become increasingly important in the scientific domain, as software gets larger and more complex, constructed by teams of people, and evolved over decades. In the context of scientific computation, the challenge facing mathematical software practitioners is to design, develop, and supply computational components which deliver these objectives when embedded in end-user application codes. The Architecture of Scientific Software addresses emerging methodologies and tools for the rational design of scientific software, including component integration frameworks, network-based computing, formal methods of abstraction, application programmer interface design, and the role of object-oriented languages. This book comprises the proceedings of the International Federation for Information Processing (IFIP) Conference on the Architecture of Scientific Software, which was held in Ottawa, Canada, in October 2000. It will prove invaluable reading for developers of scientific software, as well as for researchers in computational sciences and engineering.

This book presents real-world decision support systems, i.e., systems that have been running for some time and as such have been tested in real environments and complex situations; the cases are from various application domains and highlight the best practices in each stage of the system's life cycle, from the initial requirements analysis and design phases to the final stages of the project. Each chapter provides decision-makers with recommendations and insights into lessons learned so that failures can be avoided and successes repeated. For this reason unsuccessful cases, which at some point of their life cycle were deemed as failures for one reason or another, are also included. All decision support systems are presented in a constructive, coherent and deductive manner to enhance the learning effect. It complements the many works that focus on theoretical aspects or individual module design and development by offering 'good' and 'bad' practices when developing and using decision support systems. Combining high-quality research with real-world implementations, it is of interest to researchers and professionals in industry alike.