Advances in Computers, the latest volume in the series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

This comprehensive book unveils the working relationship of blockchain and the fog/edge computing. The contents of the book have been designed in such a way that the reader will not only understand blockchain and fog/edge computing but will also understand their co-existence and their collaborative power to solve a range of versatile problems. The first part of the book covers fundamental concepts and the applications of blockchain-enabled fog and edge computing. These include: Internet of Things, Tactile Internet, Smart City; and E-challan in the Internet of Vehicles. The second part of the book covers security and privacy related issues of blockchain-enabled fog and edge computing. These include, hardware primitive based Physical Unclonable Functions; Secure Management Systems; security of Edge and Cloud in the presence of blockchain; secure storage in fog using blockchain; and using differential privacy for edge-based Smart Grid over blockchain. This book is written for students, computer scientists, researchers and developers, who wish to work in the domain of blockchain and fog/edge computing. One of the unique features of this book is highlighting the issues, challenges, and future research directions associated with Blockchain-enabled fog and edge computing paradigm. We hope the readers will consider this book a valuable addition in the domain of Blockchain and fog/edge computing.

Managing Trade-Offs in Adaptable Software Architectures explores the latest research on adapting large complex systems to changing requirements. To be able to adapt a system, engineers must evaluate different quality attributes, including trade-offs to balance functional and quality requirements to maintain a well-functioning system throughout the lifetime of the system. This comprehensive resource brings together research focusing on how to manage trade-offs and architect adaptive systems in different business contexts. It presents state-of-the-art techniques, methodologies, tools, best practices, and guidelines for developing adaptive systems, and offers guidance for future software engineering research and practice. Each contributed chapter considers the practical application of the topic through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to, how to architect a system for adaptability, software architecture for self-adaptive systems, understanding and balancing the trade-offs involved, architectural patterns for self-adaptive systems, how quality attributes are exhibited by the architecture of the system, how to connect the quality of a software architecture to system architecture or other system considerations, and more.

Certifiable Software Applications 1: Main Processes is dedicated to the establishment of quality assurance and safety assurance. It establishes the context for achieving a certifiable software application. In it, the author covers recent developments such as the module, component and product line approach. Applicable standards are presented and security principles are described and discussed. Finally, the requirements for mastering quality and configuration are explained. In this book the reader will find the fundamental practices from the field and an introduction to the concept of software application.

This textbook presents an introduction to the mathematical foundations of software engineering. It presents the rich applications of mathematics in areas such as error-correcting codes, cryptography, the safety and security critical fields, the banking and insurance fields, as well as traditional engineering applications. Topics and features: Addresses core mathematics for critical thinking and problem solving Discusses propositional and predicate logic and various proof techniques to demonstrate the correctness of a logical argument. Examines number theory and its applications to cryptography Considers the underlying mathematics of error-correcting codes Discusses graph theory and its applications to modelling networks Reviews tools to support software engineering mathematics, including automated and interactive theorem provers and model checking Discusses financial software engineering, including simple and compound interest, probability and statistics, and operations research Discusses software reliability and dependability and explains formal methods used to derive a program from its specification Discusses calculus, matrices, vectors, complex numbers, and quaternions, as well as applications to graphics and robotics Includes key learning topics, summaries, and review questions in each chapter, together with a useful glossary This practical and easy-to-follow textbook/reference is ideal for computer science students seeking to learn how mathematics can assist them in building high-quality and reliable software on time and on budget. The text also serves as an excellent self-study primer for software engineers, quality professionals, and software managers.

This textbook was written from the perspective of someone who began his software security career in 2005, long before the industry began focusing on it. This is an excellent perspective for students who want to learn about securing application development. After having made all the rookie mistakes, the author realized that software security is a human factors issue rather than a technical or process issue alone. Throwing technology into an environment that expects people to deal with it but failing to prepare them technically and psychologically with the knowledge and skills needed is a certain recipe for bad results. Practical Security for Agile and DevOps is a collection of best practices and effective implementation recommendations that are proven to work. The text leaves the boring details of software security theory out of the discussion as much as possible to concentrate on practical applied software security that is useful to professionals. It is as much a book for students' own benefit as it is for the benefit of their academic careers and organizations. Professionals who are skilled in secure and resilient software development and related tasks are in tremendous demand. This demand will increase exponentially for the foreseeable future. As students integrate the text's best practices into their daily duties, their value increases to their companies, management, community, and industry. The textbook was written for the following readers: Students in higher education programs in business or engineering disciplines AppSec architects and program managers in information security organizations Enterprise architecture teams with a focus on application development Scrum Teams including: Scrum Masters Engineers/developers Analysts Architects Testers DevOps teams Product owners and their management Project managers Application security auditors Agile coaches and trainers Instructors and trainers in academia and private organizations

Learning by Doing with National Instruments Development Boards starts with a brief introduction to LabVIEW programming, which is required to explore the National Instrument platform, an introduction that includes detailed installation and licensing setup. Further, it gives the features and configuration setup of NI SPEEDY-33, NI ELVIS and myRIO boards. The focus of the book is on worked-out case studies for students working in different areas of electronics such as basic digital design, biomedical instrumentation, sensors and measurement. Data acquisition using SPEEDY-33, NI -ELVIS and myRIO kits is also odiscussed. The book also examines the myRIO platform.

Rapid Application Generation of Business and Finance Software describes a method for developing wide ranging computing applications with emerging software technologies. The pressure of the market place calls for reducing the time to market of new software applications. This book shows how to build such software faster and more reliably. Using an elegant concept of extended tools, the book presents a method for the constructive building of hybrid' applications. The book includes such application areas as direct marketing, banking insurance and executive information systems. The methods used adopt the latest object-oriented and client-server techniques. Rapid Application Generation of Business and Finance Software is an important book for computer scientists working on rapid application development. It is also of interest to information systems specialists.

This book focuses on mathematical modeling, describes the process of constructing and evaluating models, discusses the challenges and delicacies of the modeling process, and explicitly outlines the required rules and regulations so that the reader will be able to generalize and reuse concepts in other problems by relying on mathematical logic.Undergraduate and postgraduate students of different academic disciplines would find this book a suitable option preparing them for jobs and research fields requiring modeling techniques. Furthermore, this book can be used as a reference book for experts and practitioners requiring advanced skills of model building in their jobs.

Do you have creative ideas that you wish you could transform into code? Do you want to boost your problem solving and logic skills? Do you want to enhance your career by adopting an algorithmic mindset? In our increasingly digital world, coding is an essential skill. Communicating an algorithm to a machine to perform a set of tasks is vital. Beginner's Guide to Code Algorithms: Experiments to Enhance Productivity and Solve Problems written by Deepankar Maitra teaches you how to think like a programmer. The author unravels the secret behind writing code - building a good algorithm. Algorithmic thinking leads to asking the right question and enables a shift from issue resolution to value creation. Having this mindset will make you more marketable to employers. This book takes you on a problem-solving journey to expand your mind and increase your willingness to experiment with code. You will: Learn the art of building an algorithm through hands-on exercises Understand how to develop code for inspiring productivity concepts Build a mentality of developing algorithms to solve problems Develop, test, review, and improve code through guided experimentation This book is designed to develop a culture of logical thinking through intellectual stimulation. It will benefit students and teachers of programming, business professionals, as well as experienced users of Microsoft Excel who wish to become proficient with macros.

Mashups are mostly lightweight Web applications that offer new functionalities by combining, aggregating and transforming resources and services available on the Web. Popular examples include a map in their main offer, for instance for real estate, hotel recommendations, or navigation tools. Mashups may contain and mix client-side and server-side activity. Obviously, understanding the incoming resources (services, statistical figures, text, videos, etc.) is a precondition for optimally combining them, so that there is always some undercover semantics being used. By using semantic annotations, neutral mashups permute into the branded type of semantic mashups. Further and deeper semantic processing such as reasoning is the next step. The chapters of this book reflect the diversity of real-life semantic mashups. Two overview chapters take the reader to the environments where mashups are at home and review the regulations (standards, guidelines etc.) mashups are based on and confronted with. Chapters focusing on DBpedia, search engines and the Web of Things inspect the main Web surroundings of mashups. While mashups upgrading search queries may be nearer to the everyday experience of readers, mashups using DBpedia input and sensor data from the real world lead to important new and therefore less known developments. Finally, the diversity of mashups is tracked through a few application areas: mathematical knowledge, speech, crisis and disaster management, recommendations (for games), inner-city information, and tourism. Participants of the AI Mashup Challenge wrote all the chapters of this book. The authors were writing for their current and future colleagues - researchers and developers all over the Web who integrate mashup functionalities into their thinking and possibly into their applications.

• UML (the Unified Modeling Language), design patterns, and software component technologies are three new advances that help software engineers create more efficient and effective software designs
• A helpful project threaded throughout the book enables readers to apply what they are learning
• Presents a modern and applied approach to software design
• Numerous design patterns with detailed explanations provide essential tools for technical and professional growth
• Includes extensive discussion of UML with many UML examples

"The Testing Network" presents an integrated approach to testing based on cutting-edge methodologies, processes and tools in today's IT context. It means complex network-centric applications to be tested in heterogeneous IT infrastructures and in multiple test environments (also geographically distributed). The added-value of this book is the in-depth explanation of all processes and relevant methodologies and tools to address this complexity. Main aspects of testing are explained using TD/QC - the world-leader test platform.

This up-to-date know-how is based on real-life IT experiences gained in large-scale projects of companies operating worldwide. The book is abundantly illustrated to better show all technical aspects of modern testing in a national and international context. The author has a deep expertise by designing and giving testing training in large companies using the above-mentioned tools and processes. "The Testing Network" is a unique synthesis of core test topics applied in real-life.

The Web of Things (WoT) is a concept that describes approaches, programming tools and software architectural systems, which interface networks of real-world objects with the World Wide Web. The book is organized into 11 chapters, each focusing on a unique wireless technological aspect of the Web of Things, and it aims to comprehensively cover each of its various applications, including: A strong emphasis on WoT problems and solutions, identifying the main open issues, innovations and latest technologies behind WoT A blend of theoretical and simulation-based problems for better understanding of the concepts behind WoT Various exemplifying applications in which the use of WoT is very attractive and an inspiration for future applications The book will be useful to researchers, software developers and undergraduate and postgraduate students, as well as practitioners.

The agile transformation is an act of transforming an organization's form or nature gradually to one that can embrace and thrive in a flexible, collaborative, self-organizing, and fast-changing environment. It seems like most of the companies starting an agile transformation never reach the goal of agility, but there are those few that truly become agile and reap incredible benefits by utilizing DevOps as well. This book introduces the theory and practice of the "double-flywheels model" of Continuous Delivery 2.0: Discovery Loop, which allows information technology (IT) organizations to help businesses figure out the most efficacious ways to develop. Additionally, it explores applications of the Verification Loop that allows IT organizations to deliver value quickly and safely with high quality. Along the way, the book provides an array of insights and case studies that dive into all the aspects of software delivery, and how to implement Continuous Delivery in the most economical way for long-run business development. Features Organization culture and software architecture Business requirement management Pipeline and tooling Branching and releasing strategy Automation strategy Configuration and artefacts management Deployment and production healthy The case studies at the end of the book-scenarios in which the author was personally involved-are explored in depth and meticulously detailed in order to represent typical agile transition scenarios that will benefit all readers.

Includes step-by-step screenshots for all the examples Shows the graphical user interface of COMSOL, which does not require any programming effort Provides chapter-end problems for extensive practice along with solutions Includes actual examples of chemical reactors, transport processes, fluid flow, and heat and mass transfer

1) The book provides a basic understanding to readers who want to start their career in web application development. The book develops an understanding of the basics concepts and then takes a broader turn to enlighten the readers about the horizons which can be accessed using JavaScript. 2) JavaScript is exhaustively used in almost all kinds of application development, be it the web applications, cross platform mobile applications, server backend applications. JavaScript is now being used for full stack development and is thus used to write independent applications. Since the need for JavaScript web developers is high, the numbers of students should be high as well. 3) As compared to other books in the market, the proposed book would cover more topics (or, better, levels) in a single volume.

provides a thorough understanding of the integration of computational intelligence with information retrieval includes discussion on protecting and analysing big data on cloud platforms provides a plethora of theoretical as well as experimental research, along with surveys and impact studies

Distributed across servers, difficult to test, and resistant to modification-modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems so that they're easier to test and debug. Available in PDF (ePub, kindle, and liveBook formats coming soon). about the technologyEven experienced developers struggle with software systems that sprawl across distributed servers and APIs, are filled with redundant code, and are difficult to reliably test and modify. Adopting ways of thinking derived from functional programming can help you design and refactor your codebase in ways that reduce complexity, rather than encouraging it. Grokking Simplicity lays out how to use functional programming in a professional environment to write a codebase that's easier to test and reuse, has fewer bugs, and is better at handling the asynchronous nature of distributed systems. about the bookIn Grokking Simplicity, you'll learn techniques and, more importantly, a mindset that will help you tackle common problems that arise when software gets complex. Veteran functional programmer Eric Normand guides you to a crystal-clear understanding of why certain features of modern software are so prone to complexity and introduces you to the functional techniques you can use to simplify these systems so that they're easier to read, test, and debug. Through hands-on examples, exercises, and numerous self-assessments, you'll learn to organize your code for maximum reusability and internalize methods to keep unwanted complexity out of your codebase. Regardless of the language you're using, the ways of thinking in this book will help recognize problematic code and tame even the most complex software. what's inside Apply functional programming principles to reduce codebase complexity Work with data transformation pipelines for code that's easier to test and reuse Tools for modeling time to simplify asynchrony 60 exercises and 100 questions to test your knowledge about the readerFor experienced programmers. Examples are in JavaScript. about the author Eric Normand has been a functional programmer since 2001 and has been teaching functional programming online and in person since 2007. Visit LispCast.com to see more of his credentials.

Software Quality Assurance in Large Scale and Complex Software-intensive Systems presents novel and high-quality research related approaches that relate the quality of software architecture to system requirements, system architecture and enterprise-architecture, or software testing. Modern software has become complex and adaptable due to the emergence of globalization and new software technologies, devices and networks. These changes challenge both traditional software quality assurance techniques and software engineers to ensure software quality when building today (and tomorrow's) adaptive, context-sensitive, and highly diverse applications. This edited volume presents state of the art techniques, methodologies, tools, best practices and guidelines for software quality assurance and offers guidance for future software engineering research and practice. Each contributed chapter considers the practical application of the topic through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited, to: quality attributes of system/software architectures; aligning enterprise, system, and software architecture from the point of view of total quality; design decisions and their influence on the quality of system/software architecture; methods and processes for evaluating architecture quality; quality assessment of legacy systems and third party applications; lessons learned and empirical validation of theories and frameworks on architectural quality; empirical validation and testing for assessing architecture quality.

Discusses core concepts and principles of deep learning in gaming and animation with applications. Covers application of neural networks for intelligent video game character. Discusses automated video generation and real time animation. Covers technological advancements in virtual reality (VR), and augmented reality (AR).

Software quality stems from two distinctive, but associated, topics in software engineering: software functional quality and software structural quality. Software Quality Engineering studies the tenets of both of these notions, which focus on the efficiency and value of a design, respectively. The text addresses engineering quality on both the application and system levels with attention to Information Systems and Embedded Systems as well as recent developments. Targeted at graduate engineering students and software quality specialists, the book analyzes the relationship between functionality and quality with practical applications to related ISO/IEC JTCI SC7 standards.

This volume provides an overview and an understanding of REST (Representational State Transfer). Discussing the constraints of REST the book focuses on REST as a type of web architectural style. The focus is on applying REST beyond Web applications (i.e., in enterprise environments), and in reusing established and well-understood design patterns when doing so. The reader will be able to understand how RESTful systems can be designed and deployed, and what the results are in terms of benefits and challenges encountered in the process.

Since REST is relatively new as an approach for designing Web Services, the more advanced part of the book collects a number of challenges to some of the assumptions and constraints of REST, and looks at current research work on how REST can be extended and applied to scenarios that often are considered not to be a good match for REST.

This work will help readers to reach a deeper understanding of REST on a practical as well as on an advanced level.

The field of information technology continues to advance at a brisk pace, including the use of Remote Laboratory (RL) systems in education and research. To address the needs of remote laboratory development for such purposes, the authors present a new state-of-the-art unified framework for RL system development. Included are solutions to commonly encountered RL implementation issues such as third-party plugin, traversing firewalls, cross platform running, and scalability, etc. Additionally, the book introduces a new application architecture of remote lab for mobile-optimized RL application development for Mobile Learning (M-Learning). It also shows how to design and organize the remote experiments at different universities and make available a framework source code. The book is intended to serve as a complete guide for remote lab system design and implementation for an audience comprised of researchers, practitioners and students to enable them to rapidly and flexibly implement RL systems for a range of fields.

Learn data science with Python by building five real-world projects! In Data Science Bookcamp you'll test and build your knowledge of Python and learn to handle the kind of open-ended problems that professional data scientists work on daily. Downloadable data sets and thoroughly-explained solutions help you lock in what you've learned, building your confidence and making you ready for an exciting new data science career. about the technologyIn real-world practice, data scientists create innovative solutions to novel open ended problems. Easy to learn and use, the Python language has become the de facto language for data science amongst researchers, developers, and business users. But knowing a few basic algorithms is not enough to tackle a vague and thorny problem. It takes relentless practice at cracking difficult data tasks to achieve mastery in the field. That's just what this book delivers. about the book Data Science Bookcamp is a comprehensive set of challenging projects carefully designed to grow your data science skills from novice to master. Veteran data scientist Leonard Apeltsin sets five increasingly difficult exercises that test your abilities against the kind of problems you'd encounter in the real world. As you solve each challenge, you'll acquire and expand the data science and Python skills you'll use as a professional data scientist. Ranging from text processing to machine learning, each project comes complete with a unique downloadable data set and a fully-explained step-by-step solution. Because these projects come from Dr. Apeltsin's vast experience, each solution highlights the most likely failure points along with practical advice for getting past unexpected pitfalls. When you wrap up these five awesome exercises, you'll have a diverse relevant skill set that's transferable to working in industry. what's inside Five in-depth Python exercises with full downloadable data sets Web scraping for text and images Organise datasets with clustering algorithms Visualize complex multi-variable datasets Train a decision tree machine learning algorithm about the readerFor readers who know the basics of Python. No prior data science or machine learning skills required. about the author Leonard Apeltsin is a senior data scientist and engineering lead at Primer AI, a startup that specializes in using advanced Natural Language Processing techniques to extract insight from terabytes of unstructured text data. His PhD research focused on bioinformatics that required analyzing millions of sequenced DNA patterns to uncover genetic links in deadly diseases.