This title includes a number of Open Access chapters. Data structure and software engineering is an integral part of computer science. This volume presents new approaches and methods to knowledge sharing, brain mapping, data integration, and data storage. The author describes how to manage an organization's business process and domain data and presents new software and hardware testing methods. The book introduces a game development framework used as a learning aid in a software engineering at the university level. It also features a review of social software engineering metrics and methods for processing business information. It explains how to use Pegasys to create and manage sequence analysis workflows.

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.

This book presents an exciting new theory of time for a world built on hyper-fast digital media networks. Computers have changed the human social experience enormously. We're becoming familiar with many of the macro changes, but we rarely consider the complex, underlying mechanics of how a technology interacts with our social, political and economic worlds. And we cannot explain how the mechanics of a technology are being translated into social influence unless we understand the role of time in that process. Offering an original reconsideration of temporality, Philip Pond explains how super-powerful computers and global webs of connection have remade time through speed. The book introduces key developments in network time theory and explains their importance, before presenting a new model of time which seeks to reconcile the traditionally separate subjective and objective approaches to time theory and measurement.

The aim of this book is to provide a platform to academicians, practitioners, and researchers to understand current and future trends in software reliability growth modeling. Emphasis will be on qualitative work relevant to the theme with particular importance given to mathematical modeling for software reliability and various methods and applications of multi attributed decision making in governing the software performance. Presents software quality and security models Offers reliability analysis, assurance techniques for software systems Covers methodologies, tools, and practical applications of software reliability modeling and testing resources Includes robust reliability design techniques, diagnostic, and decision support Discusses stochastic modelling for software systems

This book presents, in an integrated form, both the analysis and synthesis of three different types of hidden Markov models. Unlike other books on the subject, it is generic and does not focus on a specific theme, e.g. speech processing. Moreover, it presents the translation of hidden Markov models' concepts from the domain of formal mathematics into computer codes using MATLAB (R). The unique feature of this book is that the theoretical concepts are first presented using an intuition-based approach followed by the description of the fundamental algorithms behind hidden Markov models using MATLAB (R). This approach, by means of analysis followed by synthesis, is suitable for those who want to study the subject using a more empirical approach. Key Selling Points: Presents a broad range of concepts related to Hidden Markov Models (HMM), from simple problems to advanced theory Covers the analysis of both continuous and discrete Markov chains Discusses the translation of HMM concepts from the realm of formal mathematics into computer code Offers many examples to supplement mathematical notation when explaining new concepts

This book provides readers insights into cyber maneuvering or adaptive and intelligent cyber defense. It describes the required models and security supporting functions that enable the analysis of potential threats, detection of attacks, and implementation of countermeasures while expending attacker resources and preserving user experience. This book not only presents significant education-oriented content, but uses advanced content to reveal a blueprint for helping network security professionals design and implement a secure Software-Defined Infrastructure (SDI) for cloud networking environments. These solutions are a less intrusive alternative to security countermeasures taken at the host level and offer centralized control of the distributed network. The concepts, techniques, and strategies discussed in this book are ideal for students, educators, and security practitioners looking for a clear and concise text to avant-garde cyber security installations or simply to use as a reference. Hand-on labs and lecture slides are located at http://virtualnetworksecurity.thothlab.com/. Features Discusses virtual network security concepts Considers proactive security using moving target defense Reviews attack representation models based on attack graphs and attack trees Examines service function chaining in virtual networks with security considerations Recognizes machine learning and AI in network security

Essential Infrastructure as Code teaches patterns for scaling systems and supporting infrastructure for mission-critical applications. The book is fullof flexible automation techniques and universal principles that are easy toapply to almost any use case, from data centers, to public cloud, to software-as-a-Service. The book is full of techniques that work whether you're managing your personal projects or making live network changes across a large enterprise. Infrastructure as Code (IaC) replaces time-consuming manual provisioning and configuration with automation via configuration managers or provisioning tools like Hashicorp Terraform. Managing your infrastructure as code makes it easy to test changes and implement new features, scale systems without downtime or operational toil, and rapidly roll back mistakes.

Developing projects outside of a classroom setting can be intimidating for students and is not always a seamless process. Real-World Software Projects for Computer Science and Engineering Students is a quick, easy source for tackling such issues. Filling a critical gap in the research literature, the book: Is ideal for academic project supervisors. Helps researchers conduct interdisciplinary research. Guides computer science students on undertaking and implementing research-based projects This book explains how to develop highly complex, industry-specific projects touching on real-world complexities of software developments. It shows how to develop projects for students who have not yet had the chance to gain real-world experience, providing opportunity to become familiar with the skills needed to implement projects using standard development methodologies. The book is also a great source for teachers of undergraduate students in software engineering and computer science as it can help students prepare for the risk and uncertainty that is typical of software development in industrial settings.

Originally published in 1966. Professor Rescher's aim is to develop a "logic of commands" in exactly the same general way which standard logic has already developed a "logic of truth-functional statement compounds" or a "logic of quantifiers". The object is to present a tolerably accurate and precise account of the logically relevant facets of a command, to study the nature of "inference" in reasonings involving commands, and above all to establish a viable concept of validity in command inference, so that the logical relationships among commands can be studied with something of the rigour to which one is accustomed in other branches of logic.

Do modern programming languages, IDEs, and libraries make coding easy? Maybe, but coding is not design. Large-scale or expensive apps clearly require evaluation of design choices. Still, software design directly impacts code reuse and longevity even for small-scale apps with limited overhead. This text evaluates and contrasts common object-oriented designs. A given problem may have many solutions. A developer may employ different design techniques - composition, inheritance, dependency injection, delegation, etc. - to solve a particular problem. A skilled developer can determine the costs and benefits of different design responses, even amid competing concerns. A responsible developer documents design choices as a contract with the client, delineating external and internal responsibilities. To promote effective software design, this book examines contractual, object-oriented designs for immediate and sustained use as well as code reuse. The intent of identifying design variants is to recognize and manage conflicting goals such as short versus long-term utility, stability versus flexibility, and storage versus computation. Many examples are given to evaluate and contrast different solutions and to compare C# and C++ effects. No one has a crystal ball; however, deliberate design promotes software longevity. With the prominence of legacy OO code, a clear understanding of different object-oriented designs is essential. Design questions abound. Is code reuse better with inheritance or composition? Should composition rely on complete encapsulation? Design choices impact flexibility, efficiency, stability, longevity, and reuse, yet compilers do not enforce design and syntax does not necessarily illustrate design. Through deliberate design, or redesign when refactoring, developers construct sustainable, efficient code.

Do modern programming languages, IDEs, and libraries make coding easy? Maybe, but coding is not design. Large-scale or expensive apps clearly require evaluation of design choices. Still, software design directly impacts code reuse and longevity even for small-scale apps with limited overhead. This text evaluates and contrasts common object-oriented designs. A given problem may have many solutions. A developer may employ different design techniques - composition, inheritance, dependency injection, delegation, etc. - to solve a particular problem. A skilled developer can determine the costs and benefits of different design responses, even amid competing concerns. A responsible developer documents design choices as a contract with the client, delineating external and internal responsibilities. To promote effective software design, this book examines contractual, object-oriented designs for immediate and sustained use as well as code reuse. The intent of identifying design variants is to recognize and manage conflicting goals such as short versus long-term utility, stability versus flexibility, and storage versus computation. Many examples are given to evaluate and contrast different solutions and to compare C# and C++ effects. No one has a crystal ball; however, deliberate design promotes software longevity. With the prominence of legacy OO code, a clear understanding of different object-oriented designs is essential. Design questions abound. Is code reuse better with inheritance or composition? Should composition rely on complete encapsulation? Design choices impact flexibility, efficiency, stability, longevity, and reuse, yet compilers do not enforce design and syntax does not necessarily illustrate design. Through deliberate design, or redesign when refactoring, developers construct sustainable, efficient code.

Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support 21st-century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on 40 years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past 20 years, the book explains that end users now expect designs and behaviors that are much closer to the way they think, work, and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design, and search system architecture and engineering.

Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support 21st-century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on 40 years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past 20 years, the book explains that end users now expect designs and behaviors that are much closer to the way they think, work, and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design, and search system architecture and engineering.

Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB (R) codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/

Software Design: Creating Solutions for Ill-Structured Problems, Third Edition provides a balanced view of the many and varied software design practices used by practitioners. The book provides a general overview of software design within the context of software development and as a means of addressing ill-structured problems. The third edition has been expanded and reorganised to focus on the structure and process aspects of software design, including architectural issues, as well as design notations and models. It also describes a variety of different ways of creating design solutions such as plan-driven development, agile approaches, patterns, product lines, and other forms. Features *Includes an overview and review of representation forms used for modelling design solutions *Provides a concise review of design practices and how these relate to ideas about software architecture *Uses an evidence-informed basis for discussing design concepts and when their use is appropriate This book is suitable for undergraduate and graduate students taking courses on software engineering and software design, as well as for software engineers. Author David Budgen is a professor emeritus of software engineering at Durham University. His research interests include evidence-based software engineering (EBSE), software design, and healthcare informatics.

The book addresses the need to investigate new approaches to lower energy requirement in multiple application areas and serves as a guide into emerging circuit technologies. It explores revolutionary device concepts, sensors, and associated circuits and architectures that will greatly extend the practical engineering limits of energy-efficient computation. The book responds to the need to develop disruptive new system architectures and semiconductor processes aimed at achieving the highest level of computational energy efficiency for general purpose computing systems. Discusses unique technologies and material only available in specialized journal and conferences. Covers emerging materials and device structures, such as ultra-low power technologies, nanoelectronics, and microsystem manufacturing. Explores semiconductor processing and manufacturing, device design, and performance. Contains practical applications in the engineering field, as well as graduate studies. Written by international experts from both academia and industry.

This book presents a comprehensive coverage of the five fundamental yet intertwined pillars paving the road towards the future of connected autonomous electric vehicles and smart cities. The connectivity pillar covers all the latest advancements and various technologies on vehicle-to-everything (V2X) communications/networking and vehicular cloud computing, with special emphasis on their role towards vehicle autonomy and smart cities applications. On the other hand, the autonomy track focuses on the different efforts to improve vehicle spatiotemporal perception of its surroundings using multiple sensors and different perception technologies. Since most of CAVs are expected to run on electric power, studies on their electrification technologies, satisfaction of their charging demands, interactions with the grid, and the reliance of these components on their connectivity and autonomy, is the third pillar that this book covers. On the smart services side, the book highlights the game-changing roles CAV will play in future mobility services and intelligent transportation systems. The book also details the ground-breaking directions exploiting CAVs in broad spectrum of smart cities applications. Example of such revolutionary applications are autonomous mobility on-demand services with integration to public transit, smart homes, and buildings. The fifth and final pillar involves the illustration of security mechanisms, innovative business models, market opportunities, and societal/economic impacts resulting from the soon-to-be-deployed CAVs. This book contains an archival collection of top quality, cutting-edge and multidisciplinary research on connected autonomous electric vehicles and smart cities. The book is an authoritative reference for smart city decision makers, automotive manufacturers, utility operators, smart-mobility service providers, telecom operators, communications engineers, power engineers, vehicle charging providers, university professors, researchers, and students who would like to learn more about the advances in CAEVs connectivity, autonomy, electrification, security, and integration into smart cities and intelligent transportation systems.

This book focuses on a specialized branch of the vast domain of software engineering: component-based software engineering (CBSE). Component-Based Software Engineering: Methods and Metrics enhances the basic understanding of components by defining categories, characteristics, repository, interaction, complexity, and composition. It divides the research domain of CBSE into three major sub-domains: (1) reusability issues, (2) interaction and integration issues, and (3) testing and reliability issues. This book covers the state-of-the-art literature survey of at least 20 years in the domain of reusability, interaction and integration complexities, and testing and reliability issues of component-based software engineering. The aim of this book is not only to review and analyze the previous works conducted by eminent researchers, academicians, and organizations in the context of CBSE, but also suggests innovative, efficient, and better solutions. A rigorous and critical survey of traditional and advanced paradigms of software engineering is provided in the book. Features: In-interactions and Out-Interactions both are covered to assess the complexity. In the context of CBSE both white-box and black-box testing methods and their metrics are described. This work covers reliability estimation using reusability which is an innovative method. Case studies and real-life software examples are used to explore the problems and their solutions. Students, research scholars, software developers, and software designers or individuals interested in software engineering, especially in component-based software engineering, can refer to this book to understand the concepts from scratch. These measures and metrics can be used to estimate the software before the actual coding commences.

Anyone Can Code: The Art and Science of Logical Creativity introduces computer programming as a way of problem-solving through logical thinking. It uses the notion of modularization as a central lens through which we can make sense of many software concepts. This book takes the reader through fundamental concepts in programming by illustrating them in three different and distinct languages: C/C++, Python, and Javascript. Key features: Focuses on problem-solving and algorithmic thinking instead of programming functions, syntax, and libraries; Includes engaging examples, including video games and visual effects; Provides exercises and reflective questions. This book gives beginner and intermediate learners a strong understanding of what they are doing so that they can do it better and with any other tool or language that they may end up using later.

This book supports readers in the development of a remotely operated vehicle (ROV) pilot training simulator by exploiting open-source or free gaming software and emphasizing the importance of using established and widely-available game design techniques to provide engaging scenarios for ROV training developers and trainees. There is no such book to guide the users to create an open-source virtual simulator for pilot training in the marine and offshore industry. This book can be used as a reference for undergraduate and postgraduate students, engineers, researchers, and lecturers in VR simulation using UnityTM as the leading software. Some of the key features of the book include: * Step-by-step procedures in development ROV pilot training simulator * Use of open-source software UnityTM that is freely available to all readers * The codes used in the book are self-sufficient as there are no codes hidden from readers

The book addresses the need to investigate new approaches to lower energy requirement in multiple application areas and serves as a guide into emerging circuit technologies. It explores revolutionary device concepts, sensors, and associated circuits and architectures that will greatly extend the practical engineering limits of energy-efficient computation. The book responds to the need to develop disruptive new system architecutres, circuit microarchitectures, and attendant device and interconnect technology aimed at achieving the highest level of computational energy efficiency for general purpose computing systems. Features Discusses unique technologies and material only available in specialized journal and conferences Covers emerging applications areas, such as ultra low power communications, emerging bio-electronics, and operation in extreme environments Explores broad circuit operation, ex. analog, RF, memory, and digital circuits Contains practical applications in the engineering field, as well as graduate studies Written by international experts from both academia and industry

This book focuses on elementary concepts of both radio frequency energy harvesting (RFEH) and wireless power transfer (WPT), and highlights their fundamental requirements followed by recent advancements. It provides a systematic overview of the key components required for RFEH and WPT applications and also comprehensively introduces the pioneering research advancements achieved to date. The state-of-the-art circuit design topologies for the two different applications are presented mainly in terms of antenna operating frequencies, polarization characteristics, efficient matching network circuits, rectifier topologies, and overall rectenna systems. The book serves as a single point of reference for practicing engineers and researchers searching for potential sources and elements involved in the RFEH system as well as in the WPT system, and need rapid training and design guidelines in the following areas: * Different sensing elements used in RFEH and WPT * Inclusions of mathematical expressions and design problems * Illustration of some design examples and performance enhancement techniques

A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source. Key features: Allows you to learn R and Python in parallel Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools - data.table and pandas Provides a concise and accessible presentation Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc. Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.

Published in 1993. Software reuse has been shown to achieve improvements in productivity, quality and timeliness of software. The collection of papers in this book were given at a seminar organized by UNICOM and the British Computer Society Software Reuse Specialist Group. They address the reasons why software reuse can maximize an organization's return from past expenditure and ensure a good future expenditure. Increasing the automation of software development requires access to explicit knowledge about processes and products involved. The chapters examine the relationship between reuse and other aspects of software engineering, including management techniques and structures, CASE, methodologies and object orientation. In addition, the papers aim to provide a structures insight into new techniques which will become available through the 1990s. This text is suitable for software managers and directors, software engineers, software professionals, academics, and other involved in software engineering research.

Businesses today are faced with a highly competitive market and fast-changing technologies. In order to meet demanding customers' needs, they rely on high quality software. A new field of study, soft computing techniques, is needed to estimate the efforts invested in component-based software. Component-Based Systems: Estimating Efforts Using Soft Computing Techniques is an important resource that uses computer-based models for estimating efforts of software. It provides an overview of component-based software engineering, while addressing uncertainty involved in effort estimation and expert opinions. This book will also instruct the reader how to develop mathematical models. This book is an excellent source of information for students and researchers to learn soft computing models, their applications in software management, and will help software developers, managers, and those in the industry to apply soft computing techniques to estimate efforts.