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.

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.

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.

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.

"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.

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.

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

Domain analysis is the process of studying the actions, knowledge production, knowledge dissemination, and knowledge-base of a community of commonality, such as an academic discipline or a professional community. The products of domain analysis range from controlled vocabularies and other knowledge organization systems, to scientific evidence about the growth and sharing of knowledge and the evolution of communities of discourse and practice.In the field of knowledge organization- both the science and the practice domain analysis is the basic research method for identifying the concepts that will be critical building blocks for knowledge organization systems. This book will survey the theoretical rationale for domain analysis, present tutorials in the specific methods of domain analysis, especially with regard to tools for visualizing knowledge domains.

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.

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.

MVC and CRUD make software easier to write, but harder to change. Microservice-based architectures can help even the smallest of projects remain agile in the long term, but most tutorials meander in theory or completely miss the point of what it means to be microservice-based. Roll up your sleeves with real projects and learn the most important concepts of evented architectures. You'll have your own deployable, testable project and a direction for where to go next. Much ink has been spilled on the topic of microservices, but all of this writing fails to accurately identity what makes a system a monolith, define what microservices are, or give complete, practical examples, so you're probably left thinking they have nothing to offer you. You don't have to be at Google or Facebook scale to benefit from a microservice-based architecture. Microservices will keep even small and medium teams productive by keeping the pieces of your system focused and decoupled. Discover the basics of message-based architectures, render the same state in different shapes to fit the task at hand, and learn what it is that makes something a monolith (it has nothing to do with how many machines you deploy to). Conserve resources by performing background jobs with microservices. Deploy specialized microservices for registration, authentication, payment processing, e-mail, and more. Tune your services by defining appropriate service boundaries. Deploy your services effectively for continuous integration. Master debugging techniques that work across different services. You'll finish with a deployable system and skills you can apply to your current project. Add the responsiveness and flexibility of microservices to your project, no matter what the size or complexity. What You Need: While the principles of this book transcend programming language, the code examples are in Node.js because JavaScript, for better or worse, is widely read. You'll use PostgreSQL for data storage, so familiarity with it is a plus. The books does provide Docker images to make working with PostgreSQL a bit easier, but extensive Docker knowledge is not required.

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

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.

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.

Security for Software Engineers is designed to introduce security concepts to undergraduate software engineering students. The book is divided into four units, each targeting activities that a software engineer will likely be involved in within industry.

The book explores the key areas of attack vectors, code hardening, privacy, and social engineering. Each topic is explored from a theoretical and a practical-application standpoint.

Features:

Targets software engineering students - one of the only security texts to target this audience.

Focuses on the white-hat side of the security equation rather than the black-hat side.

Includes many practical and real-world examples that easily translate into the workplace.

Covers a one-semester undergraduate course.

Describes all aspects of computer security as it pertains to the job of a software engineer and presents problems similar to that which an engineer will encounter in the industry.

This text will equip students to make knowledgeable security decisions, be productive members of a security review team, and write code that protects a user’s information assets.

Table of Contents

Introduction to Security 0: Security for Software Engineers 1: Roles Unit 1: Attack Vectors 2: Classification of Attacks 3: Software Weapons 4: Social Engineering Unit 2: Code Hardening 5: Command Injection 6: Script Injection 7: Memory Injection 8: Threat Modeling 9: Mitigation Unit 3: Privacy 10: Authentication 11: Access Control 12: Encryption Appendices A: Arrays B: Function Pointers C: V-Tables D: Integers E: The Callstack F: The Heap G: Further Reading H: Works Cited I: Glossary J: Index

- the book provides a unique overview of the NCBI resources, including BLAST (which are foundational to bioinformatics), and how to use them, making it a great introduction to bioinformatics and a great resource for those just starting in an industry lab - whereas many bioinformatics books try to cover every aspect of the topic and easily confuse readers, this is highly practical and focuses on key resources and tools, and how to use them - the companion website contains tutorials, R and Python codes, instructor materials including slides, exercises, and problems for students

Despite its importance, the role of HdS is most often underestimated and the topic is not well represented in literature and education. To address this, Hardware-dependent Software brings together experts from different HdS areas. By providing a comprehensive overview of general HdS principles, tools, and applications, this book provides adequate insight into the current technology and upcoming developments in the domain of HdS. The reader will find an interesting text book with self-contained introductions to the principles of Real-Time Operating Systems (RTOS), the emerging BIOS successor UEFI, and the Hardware Abstraction Layer (HAL). Other chapters cover industrial applications, verification, and tool environments. Tool introductions cover the application of tools in the ASIP software tool chain (i.e. Tensilica) and the generation of drivers and OS components from C-based languages. Applications focus on telecommunication and automotive systems.

Hands-on guidance to creating great test-driven development practice Test-driven development (TDD) practice helps developers recognize a well-designed application, and encourages writing a test before writing the functionality that needs to be implemented. This hands-on guide provides invaluable insight for creating successful test-driven development processes. With source code and examples featured in both C# and .NET, the book walks you through the TDD methodology and shows how it is applied to a real-world application. You'll witness the application built from scratch and details each step that is involved in the development, as well as any problems that were encountered and the solutions that were applied. * Clarifies the motivation behind test-driven development (TDD), what it is, and how it works * Reviews the various steps involved in developing an application and the testing that is involved prior to implementing the functionality * Discusses unit testing and refactoring Professional Test-Driven Development with C# shows you how to create great TDD processes right away.

Although industry has been leveraging the advancements of component-oriented development and assembly (CODA) technology for some time, there has long been a need for a book that provides a complete overview of the multiple technologies that support CODA. Filling this need, Component-Oriented Development and Assembly supplies comprehensive coverage of the principles, practice, and paradigm of component-oriented development and assembly. The first part of the book provides the conceptual foundation for component-oriented software. Part II focuses on the various standard Java component models and describes how to develop a component-oriented system using these component models. Part III covers the various aspects of the component-oriented development paradigm. Based on the authors' research and teaching experience, the text focuses on the principles of component-oriented software development from a technical concepts perspective, designer's perspective, programmer's perspective, and manager's perspective. Covering popular component development frameworks based on Java, it is suitable as a textbook for component-oriented software for undergraduate and postgraduate courses. It is also an ideal reference for anyone looking to adopt the component-oriented development paradigm. The book provides readers with access to all the source code used in the book on a companion site (http://www.codabook.com). The source code for the CODA implementation of the case study presented in Chapter 11 is also hosted on the website. The website will also serve as a technical forum for further discussions on the topic and for any updates to the book.

This updated and completely revised edition of a bestseller extends the concepts and considerations of modern project management into the realm of project management oversight, control, and support. Illustrating the implications of project management in today's organizations, The Complete Project Management Office Handbook, Third Edition explains how to use the project management office (PMO) as a business integrator to influence project outcomes in a manner that serves both project and business management interests. Helping you determine if a PMO is right for your organization, this edition presents a five-stage PMO competency continuum to help you understand how to develop PMOs at different competency levels and associated functionalities. It also identifies five progressive PMO development levels to help you identify which level is best for your organization. Updates to this edition include: A refinement of the 20 PMO functions that guide PMO setup and operations A new section that provides an effective evaluation of PMO maturity indicators based on the prescribed 20 PMO functions presented in the handbook A new section on Establishing a Project Management Office that details a comprehensive process for determining the needs, purpose, and functionality for a new PMO Best practices that have cross-industry value and applicability The book includes checklists, detailed process steps, and descriptive guidance for developing PMO functional capability. The up-to-date PMO model defined will not only help you better understand business practices in project management, but will also help you to adapt and integrate those practices into the project management environment in your organization. For anyone associated with start-up and smaller PMOs, the book explains what can be done to create less rigorous PMO functional capabilities. It also includes helpful insights for those who need to specify and demonstrate "quick-wins" and early PMO-based accomplishments in their organization.

You want increased customer satisfaction, faster development cycles, and less wasted work. Domain-driven design (DDD) combined with functional programming is the innovative combo that will get you there. In this pragmatic, down-to-earth guide, you'll see how applying the core principles of functional programming can result in software designs that model real-world requirements both elegantly and concisely - often more so than an object-oriented approach. Practical examples in the open-source F# functional language, and examples from familiar business domains, show you how to apply these techniques to build software that is business-focused, flexible, and high quality. Domain-driven design is a well-established approach to designing software that ensures that domain experts and developers work together effectively to create high-quality software. This book is the first to combine DDD with techniques from statically typed functional programming. This book is perfect for newcomers to DDD or functional programming - all the techniques you need will be introduced and explained. Model a complex domain accurately using the F# type system, creating compilable code that is also readable documentation---ensuring that the code and design never get out of sync. Encode business rules in the design so that you have "compile-time unit tests," and eliminate many potential bugs by making illegal states unrepresentable. Assemble a series of small, testable functions into a complete use case, and compose these individual scenarios into a large-scale design. Discover why the combination of functional programming and DDD leads naturally to service-oriented and hexagonal architectures. Finally, create a functional domain model that works with traditional databases, NoSQL, and event stores, and safely expose your domain via a website or API. Solve real problems by focusing on real-world requirements for your software. What You Need: The code in this book is designed to be run interactively on Windows, Mac and Linux. You will need a recent version of F# (4.0 or greater), and the appropriate .NET runtime for your platform. Full installation instructions for all platforms at fsharp.org.

"Ontology-based Application Integration" introduces UI-level (User Interface Level) application integration and discusses current problems which can be remedied by using ontologies. It shows a novel approach for applying ontologies in system integration. While ontologies have been used for integration of IT systems on the database and on the business logic layer, integration on the user interface layer is a novel field of research. This book also discusses how end users, not only developers, can benefit from semantic technologies.

"Ontology-based Application Integration" presents the development of a software framework including a detailed ontology about user interfaces and interactions. This includes a running case study of a real world integrated emergency management system. The last section of this book discusses useful features that can be built on top of the framework for improving the user experience with future integrated information systems.

"Ontology-based Application Integration" is designed as a reference book for practitioners and researchers who understand and work with the principles of applying semantic web technologies to a software engineering problem. This book will also make an excellent reference or secondary text book for advanced-level students concentrating on computer science.

Mobile Applications Development with Android: Technologies and Algorithms presents advanced techniques for mobile app development, and addresses recent developments in mobile technologies and wireless networks. The book covers advanced algorithms, embedded systems, novel mobile app architecture, and mobile cloud computing paradigms.

Divided into three sections, the book explores three major dimensions in the current mobile app development domain. The first section describes mobile app design and development skills, including a quick start on using Java to run an Android application on a real phone. It also introduces 2D graphics and UI design, as well as multimedia in Android mobile apps.

The second part of the book delves into advanced mobile app optimization, including an overview of mobile embedded systems and architecture. Data storage in Android, mobile optimization by dynamic programming, and mobile optimization by loop scheduling are also covered. The last section of the book looks at emerging technologies, including mobile cloud computing, advanced techniques using Big Data, and mobile Big Data storage.

About the Authors

Meikang Qiu is an Associate Professor of Computer Science at Pace University, and an adjunct professor at Columbia University. He is an IEEE/ACM Senior Member, as well as Chair of the IEEE STC (Special Technical Community) on Smart Computing. He is an Associate Editor of a dozen of journals including IEEE Transactions on Computers and IEEE Transactions on Cloud Computing. He has published 320+ peer-reviewed journal/conference papers and won 10+ Best Paper Awards.

Wenyun Dai is pursuing his PhD at Pace University. His research interests include high performance computing, mobile data privacy, resource management optimization, cloud computing, and mobile networking. His paper about mobile app privacy has been published in IEEE Transactions on Computers.

Keke Gai is pursuing his PhD at Pace University. He has published over 60 peer-reviewed journal or conference papers, and has received three IEEE Best Paper Awards. His research interests include cloud computing, cyber security, combinatorial optimization, business process modeling, enterprise architecture, and Internet computing.

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Table of Contents

Overview of Mobile Apps and Mobile Interface. Mobile Embedded System and Architecture. Introduction of Android Framework, Key Concepts, User Interface, and Multimedia Deployment. Network Management in Mobile Cloud Computing and Adaptive Resource Allocations. 2-D Graphics and Mobile Image Processing Techniques. Mobile Optimization by Dynamic Programming. Big Data and Hybrid Memory Implementations. Exploring Mobile Hardware and Software Coding Techniques. Secure Bluetooth Connection and Near Field Communication. Data Storage, data security, and advanced data protection techniques. Efficient Data Synchronization on Mobile Devices. Mobile Apps on Wearable Devices.

PhoneGap is a standards-based, open-source development framework that can be deployed to any mobile device without losing the features of the native app-allowing for access to device contacts, the local file system, camera, and media on multiple platforms without requiring users to write a single line of code. Ideal for intermediate to advanced users, PhoneGap Build: Developing Cross Platform Mobile Applications in the Cloud offers the comprehensive coverage you need to harness the power of this dynamic tool. It provides complete coverage of the cloud computing platform and the theories behind cloud computing, using a series of engaging examples. The book explains the differences between existing mobile platforms, the different types of browsers they support, and the programming languages and integrated development environment required to develop apps for each of them. It then describes how PhoneGap makes the task of developing cross-platform mobile apps easier. This book will teach you how to use: HTML5, CSS3, and JavaScript to develop apps for devices across various mobile operating systems PhoneGap Build to develop mobile apps in the cloud PhoneGap with Sencha Touch and jQuery Mobile Back end databases to store and retrieve information The text starts with simpler applications and gradually moves toward describing advanced concepts and how to exploit different application programming interfaces and methods. By the time you finish the book, you will learn how to develop feature-rich mobile applications that can run on the cloud to support different platforms. Supplying authoritative guidance and proven best practices for designing cloud-based applications, the book is an ideal reference for cloud system developers, architects, and IT professionals. It is also suitable for use in instructional settings.