Is your application or Web site ready for prime time?
A major revision of a classic reference, GUI Bloopers 2.0 looks at user interface design bloopers from commercial software, Web sites, Web applications, and information appliances, explaining how intelligent, well-intentioned professionals make these mistakes--and how you can avoid them. While equipping you with the minimum of theory, GUI expert Jeff Johnson presents the reality of interface design in an entertaining, anecdotal, and instructive way.
* Updated to reflect the bloopers that are common today, incorporating many comments and suggestions from first edition readers.
* Takes a learn-by-example approach that teaches how to avoid common errors.
* Covers bloopers in a wide range of categories: GUI controls, graphic design and layout, text messages, interaction strategies, Web site design -- including search, link, and navigation, responsiveness issues, and management decision-making.
* Organized and formatted so information needed is quickly found, the new edition features call-outs for the examples and informative captions to enhance quick knowledge building.
* Hundreds of illustrations: both the DOs and the DON'Ts for each topic covered, with checklists and additional bloopers on www.gui-bloopers.com.

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architecture

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.

This book discusses Change Management Impact Analysis and how this method is used to analysis the risks and benefits of a change management initiative when it pertains to obtaining critical insight into how the change management program budget should be allotted. The process also offers useful indicators for what areas within the system should be monitored during the change management process. This book presents theoretical analysis of practical implications and surveys, along with analysis. It covers the functions aimed at identifying various stakeholders associated with the software such as requirement component, design component, and class component. The book talks about the interrelationship between the change and the effects on the rest of the system and dives deeper to include the critical role that the analysis places on the existing multiple functions such as estimating the development costs, the project overhead costs, cost for the modification of the system, and system strength or detecting errors in the system during the process. Case studies are also included to help researchers and practitioners to absorb the material presented. This book is useful to graduate students, researchers, academicians, institutions, and professionals that interested in exploring the areas of Impact Analysis.

Understanding BIM presents the story of Building Information Modelling, an ever evolving and disruptive technology that has transformed the methodologies of the global construction industry. Written by the 2016 Prince Philip Gold Medal winner, Jonathan Ingram, it provides an in-depth understanding of BIM technologies, the business and organizational issues associated with its implementation, and the profound advantages its effective use can provide to a project team. Ingram, who pioneered the system heralding the BIM revolution, provides unrivalled access to case material and relevance to the current generation of BIM masters. With hundreds of colour images and illustrations showing the breadth and power of BIM, the book covers: The history of BIM What BIM is in technical and practical terms How it changes the day to day working environment Why we need BIM and what problems it can solve Where BIM is headed, particularly with regards to AI, AR, VR and voice recognition International case studies from a range of disciplines including: architecture, construction management, and retail Professionals and students in any field where the inter-disciplinary aspects of BIM are in operation will benefit from Ingram's insights. This book is an authoritative account of and reference on BIM for anyone wanting to understand its history, theory, application and potential future developments.

The first edition of Exercises in Programming Style was honored as an ACM Notable Book and praised as "The best programming book of the decade." This new edition retains the same presentation but has been upgraded to Python 3, and there is a new section on neural network styles. Using a simple computational task (term frequency) to illustrate different programming styles, Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs. The book contains 40 different styles for writing the term frequency task. The styles are grouped into ten categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, interactivity, and neural networks. The author states the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.

Developing secure software requires the integration of numerous methods and tools into the development process, and software design is based on shared expert knowledge, claims, and opinions. Empirical methods, including data analytics, allow extracting knowledge and insights from the data that organizations collect from their processes and tools, and from the opinions of the experts who practice these processes and methods. This book introduces the reader to the fundamentals of empirical research methods, and demonstrates how these methods can be used to hone a secure software development lifecycle based on empirical data and published best practices.

Practical Guidance on the Efficient Development of High-Quality Software Introduction to Software Engineering, Second Edition equips students with the fundamentals to prepare them for satisfying careers as software engineers regardless of future changes in the field, even if the changes are unpredictable or disruptive in nature. Retaining the same organization as its predecessor, this second edition adds considerable material on open source and agile development models. The text helps students understand software development techniques and processes at a reasonably sophisticated level. Students acquire practical experience through team software projects. Throughout much of the book, a relatively large project is used to teach about the requirements, design, and coding of software. In addition, a continuing case study of an agile software development project offers a complete picture of how a successful agile project can work. The book covers each major phase of the software development life cycle, from developing software requirements to software maintenance. It also discusses project management and explains how to read software engineering literature. Three appendices describe software patents, command-line arguments, and flowcharts.

GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation. Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different, the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas, as well as the bad ideas, so readers can apply the good ideas and avoid the bad ideas in their own programs. Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming language, an overview of GPU programming using other programming languages and API libraries (such as Python, OpenCV, OpenGL, and Apple's Swift and Metal,) and the deep learning library cuDNN.

The International Conference on Communications, Management, and Information Technology (ICCMIT'16) provides a discussion forum for scientists, engineers, educators and students about the latest discoveries and realizations in the foundations, theory, models and applications of systems inspired on nature, using computational intelligence methodologies, as well as in emerging areas related to the three tracks of the conference: Communication Engineering, Knowledge, and Information Technology. The best 25 papers to be included in the book will be carefully reviewed and selected from numerous submissions, then revised and expanded to provide deeper insight into trends shaping future ICT.

"A stereotype of computer science textbooks is that they are dry, boring, and sometimes even intimidating. As a result, they turn students' interests off from the subject matter instead of enticing them into it. This textbook is the opposite of such a stereotype. The author presents the subject matter in a refreshing story-telling style and aims to bring the Internet-generation of students closer to her stories." --Yingcai Xiao, The University of Akron Introduction to Middleware: Web Services, Object Components, and Cloud Computing provides a comparison of different middleware technologies and the overarching middleware concepts they are based on. The various major paradigms of middleware are introduced and their pros and cons are discussed. This includes modern cloud interfaces, including the utility of Service Oriented Architectures. The text discusses pros and cons of RESTful vs. non-RESTful web services, and also compares these to older but still heavily used distributed object/component middleware. The text guides readers to select an appropriate middleware technology to use for any given task, and to learn new middleware technologies as they appear over time without being greatly overwhelmed by any new concept. The book begins with an introduction to different distributed computing paradigms, and a review of the different kinds of architectures, architectural styles/patterns, and properties that various researchers have used in the past to examine distributed applications and determine the quality of distributed applications. Then it includes appropriate background material in networking and the web, security, and encoding necessary to understand detailed discussion in this area. The major middleware paradigms are compared, and a comparison methodology is developed. Readers will learn how to select a paradigm and technology for a particular task, after reading this text. Detailed middleware technology review sections allow students or industry practitioners working to expand their knowledge to achieve practical skills based on real projects so as to become well-functional in that technology in industry. Major technologies examined include: RESTful web services (RESTful cloud interfaces such as OpenStack, AWS EC2 interface, CloudStack; AJAX, JAX-RS, ASP.NET MVC and ASP.NET Core), non-RESTful (SOAP and WSDL-based) web services (JAX-WS, Windows Communication Foundation), distributed objects/ components (Enterprise Java Beans, .NET Remoting, CORBA). The book presents two projects that can be used to illustrate the practical use of middleware, and provides implementations of these projects over different technologies. This versatile and class-tested textbook is suitable (depending on chapters selected) for undergraduate or first-year graduate courses on client server architectures, middleware, and cloud computing, web services, and web programming.

Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced, and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle, and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development, as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development, including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software, including not only computational modeling, but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the Editors Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www.SE4Science.org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software.

Automatic biometrics recognition techniques are increasingly important in corporate and public security systems and have increased in methods due to rapid field development. This book discusses classic behavioral biometrics as well as collects the latest advances in techniques, theoretical approaches, and dynamic applications. This future-looking book is an important reference tool for researchers, practitioners, academicians, and technologists. While there are existing books that focus on physiological biometrics or algorithmic approaches deployed in biometrics, this book addresses a gap in the existing literature for a text that is solely dedicated to the topic of behavioral biometrics.

From the Foreword "Getting CPS dependability right is essential to forming a solid foundation for a world that increasingly depends on such systems. This book represents the cutting edge of what we know about rigorous ways to ensure that our CPS designs are trustworthy. I recommend it to anyone who wants to get a deep look at these concepts that will form a cornerstone for future CPS designs." --Phil Koopman, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA Trustworthy Cyber-Physical Systems Engineering provides practitioners and researchers with a comprehensive introduction to the area of trustworthy Cyber Physical Systems (CPS) engineering. Topics in this book cover questions such as What does having a trustworthy CPS actually mean for something as pervasive as a global-scale CPS? How does CPS trustworthiness map onto existing knowledge, and where do we need to know more? How can we mathematically prove timeliness, correctness, and other essential properties for systems that may be adaptive and even self-healing? How can we better represent the physical reality underlying real-world numeric quantities in the computing system? How can we establish, reason about, and ensure trust between CPS components that are designed, installed, maintained, and operated by different organizations, and which may never have really been intended to work together? Featuring contributions from leading international experts, the book contains sixteen self-contained chapters that analyze the challenges in developing trustworthy CPS, and identify important issues in developing engineering methods for CPS. The book addresses various issues contributing to trustworthiness complemented by contributions on TCSP roadmapping, taxonomy, and standardization, as well as experience in deploying advanced system engineering methods in industry. Specific approaches to ensuring trustworthiness, namely, proof and refinement, are covered, as well as engineering methods for dealing with hybrid aspects.

Formal methods traditionally address the question of transforming software engineering into a mature engineering discipline. This essentially refers to trusting that the software-intensive systems that form our society's infrastructures are behaving according to their specifications. More recently, formal methods are also used to understand properties and evolution laws of existing complex and adaptive systems-man-made such as smart electrical grids or natural ones such as biological networks. A tribute to Professor Kaisa Sere's contributions to the field of computer science, From Action Systems to Distributed Systems: The Refinement Approach is the first book to address the impact of refinement through a multitude of formal methods ranging from Action Systems to numerous related approaches in computer science research. It presents a state-of-the-art review on the themes of distributed systems and refinement. A fundamental part of Kaisa Sere's research consisted of developing Action Systems, a formalism for modeling, analysing, and constructing distributed systems. Within the design of distributed systems, Kaisa Sere's main research focus was on refinement-based approaches to the construction of systems ranging from pure software to hardware and digital circuits. Presenting scientific contributions from renowned researchers around the world, this edited book consists of five sections: Modeling, Analysis, Proof, Refinement, and Applications. Each chapter has been thoroughly reviewed by experts in the field. The book covers both traditional aspects in formal methods research, as well as current and innovative research directions. It describes the transition from the strong theory of refinement to a methodology that can be applied in practice, with tool support. Examining industrial applications of the methods discussed, this book is a suitable resource for graduate students, researchers, and practitioners interested in using formal methods to develop distributed systems of quality.

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.

Computer games represent a significant software application domain for innovative research in software engineering techniques and technologies. Game developers, whether focusing on entertainment-market opportunities or game-based applications in non-entertainment domains, thus share a common interest with software engineers and developers on how to best engineer game software. Featuring contributions from leading experts in software engineering, the book provides a comprehensive introduction to computer game software development that includes its history as well as emerging research on the interaction between these two traditionally distinct fields. An ideal reference for software engineers, developers, and researchers, this book explores game programming and development from a software engineering perspective. It introduces the latest research in computer game software engineering (CGSE) and covers topics such as HALO (Highly Addictive, sociaLly Optimized) software engineering, multi-player outdoor smartphone games, gamifying sports software, and artificial intelligence in games. The book explores the use of games in software engineering education extensively. It also covers game software requirements engineering, game software architecture and design approaches, game software testing and usability assessment, game development frameworks and reusability techniques, and game scalability infrastructure, including support for mobile devices and web-based services.

This book provides a high-level description, together with a mathematical and an experimental analysis, of Java and of the Java Virtual Machine (JVM), including a standard compiler of Java programs to JVM code and the security critical bytecode verifier component of the JVM. The description is structured into language layers and machine components. It comes with a natural executable refinement (written in AsmGofer and provided on CD ROM) which can be used for testing code. The method developed for this purpose is based on Abstract State Machines (ASMs) and can be applied to other virtual machines and to other programming languages as well. The book is written for advanced students and for professionals and practitioners in research and development who need a complete and transparent definition and an executable model of the language and of the virtual machine underlying its intended implementation.The CD ROM contains the entire text of the book and numerous examples and exercises.

As the number of Internet of Things (IoT) elements grows exponentially, their interactions can generate a massive amount of raw and multi-structured data. The challenge with this data explosion is to transform any raw data into information and knowledge, which can be used by people and systems to make intelligent decisions. Industrial IoT Application Architectures and Use Cases explores how artificial intelligence (AI), data analytics, and IoT technology combine to promote intelligent decision-making and automation in a range of industries. With faster, more stable AI algorithms and approaches, knowledge discovery and dissemination from IoT-device data can be simplified and streamlined. An era of powerful cognitive technology is beginning due to cloud-based cognitive systems that are forming the foundation of game-changing intelligent applications. This book presents next-generation use cases of IoT and IoT data analytics for a variety of industrial verticals as given below: An Intelligent IoT framework for smart water management An IoT-enabled smart traffic control system for congestion control and smart traffic management An intelligent airport system for airport management and security surveillance An IoT framework for healthcare to integrate and report patient information Fuzzy scheduling with IoT for tracking and monitoring hotel assets An IoT system for designing drainage systems and monitoring drainage pipes Predictive maintenance of plant equipment to decide the actual mean time to malfunction Integrated neural networks and IoT systems for predictive equipment maintenance IoT integration in blockchain for smart waste management This book also includes a chapter on the IoT paradigm and an overview of uses cases for personal, social, and industrial applications.

The increasing penetration of IT in organizations calls for an integrative perspective on enterprises and their supporting information systems. MERODE offers an intuitive and practical approach to enterprise modelling and using these models as core for building enterprise information systems. From a business analyst perspective, benefits of the approach are its simplicity and the possibility to evaluate the consequences of modeling choices through fast prototyping, without requiring any technical experience. The focus on domain modelling ensures the development of a common language for talking about essential business concepts and of a shared understanding of business rules. On the construction side, experienced benefits of the approach are a clear separation between specification and implementation, more generic and future-proof systems, and an improved insight in the cost of changes. A first distinguishing feature is the method's grounding in process algebra provides clear criteria and practical support for model quality. Second, the use of the concept of business events provides a deep integration between structural and behavioral aspects. The clear and intuitive semantics easily extend to application integration (COTS software and Web Services). Students and practitioners are the book's main target audience, as both groups will benefit from its practical advice on how to create complete models which combine structural and behavioral views of a system-to-be and which can readily be transformed into code, and on how to evaluate the quality of those models. In addition, researchers in the area of conceptual or enterprise modelling will find a concise overview of the main findings related to the MERODE project. The work is complemented by a wealth of extra material on the author's web page at KU Leuven, including a free CASE tool with code generator, a collection of cases with solutions, and a set of domain modelling patterns that have been developed on the basis of the method's use in industry and government.

The book begins with an introduction to software reliability, models and techniques. The book is an informative book covering the strategies needed to assess software failure behaviour and its quality, as well as the application of optimization tools for major managerial decisions related to the software development process. It features a broad range of topics including software reliability assessment and apportionment, optimal allocation and selection decisions and upgradations problems. It moves through a variety of problems related to the evolving field of optimization of software reliability engineering, including software release time, resource allocating, budget planning and warranty models, which are each explored in depth in dedicated chapters. This book provides a comprehensive insight into present-day practices in software reliability engineering, making it relevant to students, researchers, academics and practising consultants and engineers.

This text provides a very simple, initial introduction to the complete scientific computing pipeline: models, discretization, algorithms, programming, verification, and visualization. The pedagogical strategy is to use one case study - an ordinary differential equation describing exponential decay processes - to illustrate fundamental concepts in mathematics and computer science. The book is easy to read and only requires a command of one-variable calculus and some very basic knowledge about computer programming. Contrary to similar texts on numerical methods and programming, this text has a much stronger focus on implementation and teaches testing and software engineering in particular.

Aligning an organization's goals and strategies requires specifying their rationales and connections so that the links are explicit and allow for analytic reasoning about what is successful and where improvement is necessary. This book provides guidance on how to achieve this alignment, how to monitor the success of goals and strategies and use measurement to recognize potential failures, and how to close alignment gaps. It uses the GQM+Strategies approach, which provides concepts and actionable steps for creating the link between goals and strategies across an organization and allows for measurement-based decision-making. After outlining the general motivation for organizational alignment through measurement, the GQM+Strategies approach is described concisely, with a focus on the basic model that is created and the process for creating and using this model. The recommended steps of all six phases of the process are then described in detail with the help of a comprehensive application example. Finally, the industrial challenges addressed by the method and cases of its application in industry are presented, and the relations to other approaches, such as Balanced Scorecard, are described. The book concludes with supplementary material, such as checklists and guidelines, to support the application of the method. This book is aimed at organization leaders, managers, decision makers, and other professionals interested in aligning their organization's goals and strategies and establishing an efficient strategic measurement program. It is also interesting for academic researchers looking for mechanisms to integrate their research results into organizational environments.

This book introduces all the relevant information required to understand and put Model Driven Architecture (MDA) into industrial practice. It clearly explains which conceptual primitives should be present in a system specification, how to use UML to properly represent this subset of basic conceptual constructs, how to identify just those diagrams and modeling constructs that are actually required to create a meaningful conceptual schema, and how to accomplish the transformation process between the problem space and the solution space. The approach is fully supported by commercially available tools.

From start to finish, you'll see what it takes to develop a successful agile project. Find out how the Swedish police combined XP, Scrum, and Kanban to modernize their department--and learn how you can apply those same principles to your own workplace. We start with an organization in desperate need of a new way of doing things and finish with a group of sixty, all working in sync to develop a scalable, complex system. You'll walk through the project step by step, from customer engagement, to the daily "cocktail party," version control, bug tracking, and release. In this honest look at what works--and what doesn't--you'll find out how to: * Make quality everyone's business, not just the testers. * Keep everyone moving in the same direction without micromanagement. * Use simple and powerful metrics to aid in planning and process improvement. * Balance between low-level feature focus and high-level system focus. You'll be ready to jump into the trenches yourself as you apply those same techniques to your own software development projects.