In many of nowadays web-based environments for electronic marketing and commerce, that present large multimedia product and service catalogues, it becomes more and more difficult to provide naive end users, such as private consumers or commercial business partners, with intuitive user interfaces to access the large multimedia collections describing the presented products and services. The same holds for marketing managers and other employees responsible for managing and maintaining the large and constantly changing set of multimedia information chunks and fragments contained in these collections. As a consequence, many efforts are devoted to improve the quality of the interaction between users and databases. Virtual Reality (VR) techniques are a promising interaction paradigm particularly suited to novice and/or occasional users. The users are facilitated in the database navigation since the system proposes them an environment that reproduces a real situation and gives the possibility of interacting by manipulating objects that have a direct correspondence with known objects.

* Provides simple, conceptual descriptions of everyday technologies * Includes clear examples and diagrams that demonstrate the principles and techniques, not just a "how-to" punch list * Covers advanced topics for readers who want to dive into the deep end of the technology pool * Avoids jargon-where terminology does appear, the text will provide clear, concise definitions

A developer's knowledge of a computing system's requirements is necessarily imperfect because organizations change. Many requirements lie in the future and are unknowable at the time the system is designed and built. To avoid burdensome maintenance costs developers must therefore rely on a system's ability to change gracefully-its flexibility. Flexible Software Design: Systems Development for Changing Requirements demonstrates the design principles and techniques that enable the design of software that empowers business staff to make functional changes to their systems with little or no professional IT intervention. The book concentrates on the design aspects of system development, the area with the most flexibility leverage. Divided into four parts, the text begins by introducing the fundamental concepts of flexibility, explaining the reality of imperfect knowledge and how development participants must change their thinking to implement flexible software. The second part covers design guidelines, stable identifiers, stable information structures, the Generic Entity Cloud concept, and regulatory mechanisms that give business staff control over system modifications. Part three relates strategic information systems planning to flexible systems. It examines the elicitation of requirements and the relevance of agile methods in a flexible systems environment. It also discusses practical aspects of stable identifier design and compares the testing of traditional and flexible software. In part four, the book concludes with details of the flexible UniverSIS system and an explanation of the applications and extensions of the Generic Entity Cloud tools. The combination of smart design and smart work offered in Flexible Software Design can materially benefit your organization by radically reducing the systems maintenance burden.

This reference text provides the theoretical foundations, the emergence, and the application areas of Blockchain in an easy-to-understand manner that would be highly helpful for the researchers, academicians, and industry professionals to understand the disruptive potentials of Blockchain. It explains Blockchain concepts related to Industry 4.0, Smart Healthcare, and the Internet of Things (IoT) and explores Smart Contracts and Consensus algorithms. This book will serve as an ideal reference text for graduate students and academic researchers in electrical engineering, electronics and communication engineering, computer engineering, and information technology. This book * Discusses applications of blockchain technology in diverse sectors such as industry 4.0, education, finance, and supply chain. * Provides theoretical concepts, applications, and research advancements in the field of blockchain. * Covers industry 4.0 digitization platform and blockchain for data management in industry 4.0 in a comprehensive manner. * Emphasizes analysis and design of consensus algorithms, fault tolerance, and strategy to choose the correct consensus algorithm. * Introduces security issues in the industrial internet of things, internet of things, blockchain integration, and blockchain-based applications. The text presents in-depth coverage of theoretical concepts, applications and advances in the field of blockchain technology. This book will be an ideal reference for graduate students and academic researchers in diverse engineering fields such as electrical, electronics and communication, computer, and information technology.

Built specifically for statistical computing and graphics, the R language, along with its amazing collection of libraries and tools, is one of the most powerful tools you can use to tackle data analysis for business, research, and other data-intensive domains. This revised and expanded third edition of R in Action covers the new tidy verse approach to data analysis and R's state-of-the-art graphing capabilities with the ggplot2 package. R in Action, Third Edition teaches you to use the R language, including the popular tidy verse packages, through hands-on examples relevant to scientific, technical, and business developers. Focusing on practical solutions to real-world data challenges, R expert RobKabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualisations. The R language is the most powerful platform you can choose for modern data analysis. Free and open source, R's community has created thousands of modules to tackle challenges from data-crunching to presentation. R's graphical capabilities are also state-of-the-art, with a comprehensive and powerful feature set available for data visualization. R runs on all major operating systems and is used by businesses, researchers, and organizations worldwide.

This book provides techniques for offshore center managers and head office managers to motivate and manage globally distributed teams, which are spread across the offshore center and the head office, and thereby achieve higher productivity. Readers learn how to integrate the offshore center with the head office to make the offshore team an extension of the head office. While integrating teams with the head office, offshore center managers can still retain independence and authority to meet team aspirations. The book provides insight into devising new organizational structures to balance the authority and responsibilities of offshore center and head office managers. Head office managers responsible for managing globally distributed projects learn how to achieve a higher success rate on their projects and be better rewarded for their efforts in offshoring. Head office managers also learn techniques to make more significant contributions in their expatriate assignments to the offshore center. This book guides both the offshore center managers and the head office managers to fully realize the potential of the offshore center, which can result in higher revenues and profitability.

This book gathers chapters from some of the top international empirical software engineering researchers focusing on the practical knowledge necessary for conducting, reporting and using empirical methods in software engineering. Topics and features include guidance on how to design, conduct and report empirical studies. The volume also provides information across a range of techniques, methods and qualitative and quantitative issues to help build a toolkit applicable to the diverse software development contexts

In the decade since the idea of adapting the evidence-based paradigm for software engineering was first proposed, it has become a major tool of empirical software engineering. Evidence-Based Software Engineering and Systematic Reviews provides a clear introduction to the use of an evidence-based model for software engineering research and practice. The book explains the roles of primary studies (experiments, surveys, case studies) as elements of an over-arching evidence model, rather than as disjointed elements in the empirical spectrum. Supplying readers with a clear understanding of empirical software engineering best practices, it provides up-to-date guidance on how to conduct secondary studies in software engineering-replacing the existing 2004 and 2007 technical reports. The book is divided into three parts. The first part discusses the nature of evidence and the evidence-based practices centered on a systematic review, both in general and as applying to software engineering. The second part examines the different elements that provide inputs to a systematic review (usually considered as forming a secondary study), especially the main forms of primary empirical study currently used in software engineering. The final part provides practical guidance on how to conduct systematic reviews (the guidelines), drawing together accumulated experiences to guide researchers and students in planning and conducting their own studies. The book includes an extensive glossary and an appendix that provides a catalogue of reviews that may be useful for practice and teaching.

The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions.

Information Systems Development: Reflections, Challenges and New Directions, is the collected proceedings of the 20th International Conference on Information Systems Development held in Edinburgh, Scotland, August 24 - 26, 2011. It follows in the tradition of previous conferences in the series in exploring the connections between industry, research and education. These proceedings represent ongoing reflections within the academic community on established information systems topics and emerging concepts, approaches and ideas. It is hoped that the papers herein contribute towards disseminating research and improving practice

The "servicemesh" pattern, implemented by platforms like Istio, helps you push operational issues into the infrastructure so the application code is easier to understand, maintain, and adapt. Istio in Action teaches you how to implement a full-featured Istio-based service mesh to manage a microservices application. Istio in Action is a comprehensive guide to handling authentication, routing, retrying, load balancing, collecting data, security, and other common network-related tasks using the Istio service mesh platform. With helpful diagrams and hands-on examples, you'll learn how to use this open-source service mesh to control routing, secure container applications, and monitor network traffic. You will also bring Istio to legacy systems without changes to your applications and discover how to use Istio in amulti-cloud world with the data layer deployed on a cluster like Kubernetes. Cloud-native applications can include thousands of clustered containers, distributed components, and complex interactions. To build them effectively, developers need a new approach to infrastructural concerns like monitoring, storage, scaling, orchestration, and security. The Istio platform offers a configurable infrastructure layer called a service mesh that reliably and efficiently manages day-to-day concerns like service discovery, load balancing, encryption, authentication and authorization, circuit breakers, and more. Open source andcloud-ready, Istio is a welcome upgrade from manually managed microservices infrastructure.

Your customers want rock-solid, bug-free software that does exactly what they expect it to do. Yet they can't always articulate their ideas clearly enough for you to turn them into code. You need Cucumber: a testing, communication, and requirements tool-all rolled into one. All the code in this book is updated for Cucumber 2.4, Rails 5, and RSpec 3.5. Express your customers' wild ideas as a set of clear, executable specifications that everyone on the team can read. Feed those examples into Cucumber and let it guide your development. Build just the right code to keep your customers happy. You can use Cucumber to test almost any system or any platform. Get started by using the core features of Cucumber and working with Cucumber's Gherkin DSL to describe-in plain language-the behavior your customers want from the system. Then write Ruby code that interprets those plain-language specifications and checks them against your application. Next, consolidate the knowledge you've gained with a worked example, where you'll learn more advanced Cucumber techniques, test asynchronous systems, and test systems that use a database. Recipes highlight some of the most difficult and commonly seen situations the authors have helped teams solve. With these patterns and techniques, test Ajax-heavy web applications with Capybara and Selenium, REST web services, Ruby on Rails applications, command-line applications, legacy applications, and more. Written by the creator of Cucumber and the co-founders of Cucumber Ltd., this authoritative guide will give you and your team all the knowledge you need to start using Cucumber with confidence. What You Need: Windows, Mac OS X (with XCode) or Linux, Ruby 1.9.2 and upwards, Cucumber 2.4, Rails 5, and RSpec 3.5

"The situation is good, but not hopeless" (Polish folk wisdom) The text is devoted to the Software Analysis and Testing (SAT) methods and s- porting tools for assessing and, if possible, improving software quality, specifically its correctness. The term quality assurance is avoided for it is this author's firm belief that in the current state of the art that goal is unattainable, a plethora of "gu- anteed" solutions to the problem notwithstanding. Therefore, the rather awkward phrase "improving correctness" is to be understood as an effort to minimize the number of residual programming faults ("bugs") and their impact on the software's behavior, that is, to make the faults tolerable. It is clear that such a minimalist approach is a result of frustration. Indeed, having spent years developing software and teaching (preaching?) "How to do it right," I still do not know how to go about it with any degree of certainty! It appears then I probably should stop right now, for who with a modicum of common sense would reach for a text that does not offer salvation but (as will be seen) hard work and misery? If I intend to continue, it is only that I suspect there are many professionals out there who have similar doubts. And they are the intended audience of this project. The philosophical underpinning of the text is the importance of sound engine- ing practices in software development.

With the emergence of cloud computing, traditional approaches to software engineering must be adapted in order to take full advantage of the benefits promised by cloud technologies.

This timely and authoritative text/reference presents the latest research on "Software Engineering Frameworks for the Cloud Computing Paradigm," drawn from an international selection of researchers and practitioners. The book offers both a discussion of relevant software engineering approaches and practical guidance on enterprise-wide software deployment in the cloud environment, together with real-world case studies.

Topics and features: presents the state of the art in software engineering approaches for developing cloud-suitable applications; discusses the impact of the cloud computing paradigm on software engineering, including the semantic web; offers guidance and best practices for students and practitioners of cloud-based applications architecture; examines the stages of the software development lifecycle, with a focus on the requirements engineering and testing of cloud-based applications; reviews the efficiency and performance of cloud-based applications; explores feature-driven and cloud-aided software design, presenting strategies for cloud adoption and migration; provides relevant theoretical frameworks, practical approaches and current and future research directions.

This practical and clearly-structured volume is an ideal self-study primer for students of cloud computing and software engineering. Software engineers, application developers and IT infrastructure managers will also find the work to be an invaluable reference.

Empirical research has now become an essential component of software engineering yet software practitioners and researchers often lack an understanding of how the empirical procedures and practices are applied in the field. Empirical Research in Software Engineering: Concepts, Analysis, and Applications shows how to implement empirical research processes, procedures, and practices in software engineering. Written by a leading researcher in empirical software engineering, the book describes the necessary steps to perform replicated and empirical research. It explains how to plan and design experiments, conduct systematic reviews and case studies, and analyze the results produced by the empirical studies. The book balances empirical research concepts with exercises, examples, and real-life case studies, making it suitable for a course on empirical software engineering. The author discusses the process of developing predictive models, such as defect prediction and change prediction, on data collected from source code repositories. She also covers the application of machine learning techniques in empirical software engineering, includes guidelines for publishing and reporting results, and presents popular software tools for carrying out empirical studies.

First Published in 2005. Routledge is an imprint of Taylor & Francis, an informa company.

Compiled by an experienced practitioner in the field, this book contains definitions of the major terms used in Reliability Engineering and Software Assessment. Approximately 2000 definitions have been carefully selected from standards and literature published by leading institutions such as the IEEE and IEC. Alternative definitions of the same term are given where relevant, enabling the reader to compare and contrast, thereby giving useful insights into different aspects of the same term. There is also extensive cross-referencing to make the book easy to use and practical.
This book will provide an invaluable reference book for anyone working in the fields of reliability engineering or software assessment but should be of particular interest to industrial researchers and practitioners, members of standards committees, reliability consultants, students on Software Quality courses, technical authors and sub-editors.

The book describes a fundamentally new approach to software dependability, considering a software system as an ever-changing system due to changes in service objectives, users' requirements, standards and regulations, and to advances in technology. Such a system is viewed as an Open System since its functions, structures, and boundaries are constantly changing. Thus, the approach to dependability is called Open Systems Dependability. The DEOS technology realizes Open Systems Dependability. It puts more emphasis on stakeholders' agreement and accountability achievement for business/service continuity than in elemental technologies.

Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects.

Experience has shown us that investment in the requirements process saves time, money, and effort. Yet, development efforts consistently charge ahead without investing sufficiently in the requirements process. We are so intent to develop the technical solutions that we are unwilling to take the time and effort to understand and meet the real customer needs.
--From the Foreword by Ralph R. Young, author of "Effective Requirements Practices"Who is it for?

If you are involved in the systems engineering process, in any company -- from transport and telecommunications, to aerospace and software -- you will learn how to write down requirements to guarantee you get the systems YOU need.What skills will I learn?

How to write simple, clear requirements -- so you get what you wantHow to organize requirements as scenarios -- so everyone understands what you wantHow to review requirements -- so you ask for the right things
0321131630B05282002

In his latest work, author Paul C Jorgensen takes his well-honed craftsman's approach to mastering model-based testing (MBT). To be expert at MBT, a software tester has to understand it as a craft rather than an art. This means a tester should have deep knowledge of the underlying subject and be well practiced in carrying out modeling and testing techniques. Judgment is needed, as well as an understanding of MBT the tools. The first part of the book helps testers in developing that judgment. It starts with an overview of MBT and follows with an in-depth treatment of nine different testing models with a chapter dedicated to each model. These chapters are tied together by a pair of examples: a simple insurance premium calculation and an event-driven system that describes a garage door controller. The book shows how simpler models-flowcharts, decision tables, and UML Activity charts-express the important aspects of the insurance premium problem. It also shows how transition-based models-finite state machines, Petri nets, and statecharts-are necessary for the garage door controller but are overkill for the insurance premium problem. Each chapter describes the extent to which a model can support MBT. The second part of the book gives testers a greater understanding of MBT tools. It examines six commercial MBT products, presents the salient features of each product, and demonstrates using the product on the insurance premium and the garage door controller problems. These chapters each conclude with advice on implementing MBT in an organization. The last chapter describes six Open Source tools to round out a tester's knowledge of MBT. In addition, the book supports the International Software Testing Qualifications Board's (ISTQB (R)) MBT syllabus for certification.

"Proceedings of the 2012 International Conference on Information Technology and Software Engineering" presents selected articles from this major event, which was held in Beijing, December 8-10, 2012. This book presents the latest research trends, methods and experimental results in the fields of information technology and software engineering, covering various state-of-the-art research theories and approaches. The subjects range from intelligent computing to information processing, software engineering, Web, unified modeling language (UML), multimedia, communication technologies, system identification, graphics and visualizing, etc.
The proceedings provide a major interdisciplinary forum for researchers and engineers to present the most innovative studies and advances, which can serve as an excellent reference work for researchers and graduate students working on information technology and software engineering.
Prof. Wei Lu, Dr. Guoqiang Cai, Prof. Weibin Liu and Dr. Weiwei Xing all work at Beijing Jiaotong University.

Its scale, flexibility, cost effectiveness, and fast turnaround are just a few reasons why crowdsourced testing has received so much attention lately. While there are a few online resources that explain what crowdsourced testing is all about, there's been a need for a book that covers best practices, case studies, and the future of this technique. Filling this need, Leveraging the Wisdom of the Crowd in Software Testing shows you how to leverage the wisdom of the crowd in your software testing process. Its comprehensive coverage includes the history of crowdsourcing and crowdsourced testing, implementation practices, and future trends. The book discusses best practices in implementation-explaining what, when, and how to crowdsource in a testing effort. It also includes case studies that illustrate how both product and service companies have successfully applied crowdsourcing in their testing programs. Explaining how to use the combined advantages of crowdsourcing and cloud computing for software testing, the book examines various engagement models in which you could implement crowdsourced testing. It addresses effective defect management in crowdsourced testing and considers both the business and engineering aspects of crowdsourced testing. The book explores the challenges, limitations, and situations when crowdsourced testing will not work and provides powerful best practices for mitigating the constraints and challenges, including how to build a crowdsourcing platform to test software products. Covering career opportunities for crowd testers, the book concludes by taking a look at the need to build a crowdsourced testing ecosystem, who the players of such an ecosystem would be, and who would need to champion such an effort.

This title includes a number of Open Access chapters. Model-driven engineering (MDE) is the automatic production of software from simplified models of structure and functionality. It mainly involves the automation of the routine and technologically complex programming tasks, thus allowing developers to focus on the true value-adding functionality that the system needs to deliver. This book serves an overview of some of the core topics in MDE. The volume is broken into two sections offering a selection of papers that helps the reader not only understand the MDE principles and techniques, but also learn from practical examples. Also covered are the following topics: * MDE for software product lines * Formal methods for model transformation correctness * Metamodeling with Eclipse eCore * Metamodeling with UML profiles * Test cases generation This easily accessible reference volume offers a comprehensive guide to this rapidly expanding field. Edited by experienced writers with experience in both research and the practice of software engineering, Model-Driven Engineering of Information Systems: Principles, Techniques and Practice is an authoritative and easy-to-use reference, ideal for both researchers in the field and students who wish to gain an overview to this important field of study.

Practical models and fundamental aspects of reuse-based software engineering

This volume provides an overview of the current state and the future of reuse-based software engineering and discusses the vital technical, managerial, and organizational aspects of reuse in one treatment. It also shows how these fundamental aspects can be used in the development life cycle of component-based software and product line engineering.

The authors present the basic foundations upon which reuse processes and approaches can be established and integrate theoretical concepts with applied practice. They also discuss the development of an effective large-scale discipline utilizing:

• The state of the art in multi-paradigm programming, design, and architectural techniques for codifying and packaging high-quality software artifacts that are widely applicable and cost-effective
• Effective organizations with the mandate and the resources to produce and manage a shared repository of software assets
• A set of control and management tools for planning, controlling, and evaluating the degree to which such an organization meets its objectives

Reuse-Based Software Engineering offers in-depth discussion of these fundamental issues and total coverage of the state of the art. The inclusion of review questions and exercises makes it an excellent tutorial for both academics and professionals.