The work presented in this book is based on empirical study undertaken as a case study to understand the challenges faced in massively open online course (MOOC) based learning and experimentation to understand the challenges for presenting theoretical and practical courses. The book proposes a flexible online platform. This solution provides flexibility in distance learning processes including course enrollment, learning, evaluation, and outcome of degrees. The proposed system not only gives students freedom to choose their courses in accordance with their needs but also use earned credit towards online degrees of any university of their choice.

This book provides guidelines for practicing design science in the fields of information systems and software engineering research. A design process usually iterates over two activities: first designing an artifact that improves something for stakeholders and subsequently empirically investigating the performance of that artifact in its context. This "validation in context" is a key feature of the book - since an artifact is designed for a context, it should also be validated in this context. The book is divided into five parts. Part I discusses the fundamental nature of design science and its artifacts, as well as related design research questions and goals. Part II deals with the design cycle, i.e. the creation, design and validation of artifacts based on requirements and stakeholder goals. To elaborate this further, Part III presents the role of conceptual frameworks and theories in design science. Part IV continues with the empirical cycle to investigate artifacts in context, and presents the different elements of research problem analysis, research setup and data analysis. Finally, Part V deals with the practical application of the empirical cycle by presenting in detail various research methods, including observational case studies, case-based and sample-based experiments and technical action research. These main sections are complemented by two generic checklists, one for the design cycle and one for the empirical cycle. The book is written for students as well as academic and industrial researchers in software engineering or information systems. It provides guidelines on how to effectively structure research goals, how to analyze research problems concerning design goals and knowledge questions, how to validate artifact designs and how to empirically investigate artifacts in context - and finally how to present the results of the design cycle as a whole.

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to "experiment and learn" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.

This open access book provides an overview of the dissertations of the five nominees for the Ernst Denert Award for Software Engineering in 2019. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains five papers describing the works by Sebastian Baltes (U Trier) on Software Developers'Work Habits and Expertise, Timo Greifenberg's thesis on Artefaktbasierte Analyse modellgetriebener Softwareentwicklungsprojekte, Marco Konersmann's (U Duisburg-Essen) work on Explicitly Integrated Architecture, Marija Selakovic's (TU Darmstadt) research about Actionable Program Analyses for Improving Software Performance, and Johannes Spath's (Paderborn U) thesis on Synchronized Pushdown Systems for Pointer and Data-Flow Analysis - which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work.

Organizations enjoy two kinds of strategic advantages. One is transitory: being in the right place with the right products at the right time. The other comes from having first class management and instituting processes that mobilize an organization, keeping in ahead of the competition. Which would you like to count on for your organization's success?Integrating ERP, CRM, Supply Chain Management, and Smart Materials explores how to create business opportunities and reap savings by: Restructuring and updating of ERP and CRM software as it integrates supply chain management and delivers new killer applications Evolving opportunities that will develop from the implementation of smart materials, automatic identification, classification systems, and quality assurance projects Auditing the implementation, operation, and maintenance of ERP and CRM software as well as the corrective action taken on the basis of resultsInternet commerce, online supply chain, and advances in technology - all available at increasingly lower costs - make systems of the past obsolete. However, just as new technology creates new opportunities, it can also create unforeseen consequences. By binding a wealth of interdependent issues between the covers of one book, Integrating ERP, CRM, Supply Chain Management, and Smart Materials gives you the tools you need to create proprietary, high value-added solutions.

Even though Six Sigma programs have successfully been implemented in practice, many IT departments remain skeptical of the process or are unaware of how the tools can be used to improve system development. Removing the mystique surrounding this technique, Six Sigma Software Development, Second Edition demonstrates how Six Sigma tools and concepts can be used to enhance the system development process. Revised and updated, this second edition clearly explains Six Sigma concepts and their application, maps Six Sigma concepts and tools to all aspects of system development, and proposes the use of Six Sigma tools to evaluate and improve the overall performance of the IT department. In addition to classic Six Sigma, the book introduces Design for Six Sigma (DFSS) and illustrates when and how its tools and techniques can be used to increase the robustness and reliability of a new system. It also shows how the judicious application of lean tools can reduce the complexity of IT processes, thus shortening the time needed to translate customer requirements into completed systems and increasing customer satisfaction.

The Science of Biometrics: Security Technology for Identity Verification covers the technical aspects of iris and facial recognition, focusing primarily on the mathematical and statistical algorithms that run the verification and identification processes in these two modalities. Each chapter begins with a review of the technologies, examining how they work, their advantages and disadvantages, as well as some of their established market applications. Numerous approaches are examined. Facial recognition is much more of an emerging biometric technology than iris recognition; therefore, there are more algorithms that are currently being developed in that area. After this review, numerous applications of these two modalities are covered as well, some of which have just been commercially deployed while others are under research and development. Chapters 3 and 4 conclude with case studies to provide further application review. This book is directed to security managers, electronic security system designers, consultants, and system integrators, as well as electronic security system manufacturers working in access control and biometrics.

When it comes to data analytics, it pays tothink big. PySpark blends the powerful Spark big data processing engine withthe Python programming language to provide a data analysis platform that can scaleup for nearly any task. Data Analysis with Python and PySpark is yourguide to delivering successful Python-driven data projects. Data Analysis with Python and PySpark is a carefully engineered tutorial that helps you use PySpark to deliver your data-driven applications at any scale. This clear and hands-on guide shows you how to enlarge your processing capabilities across multiple machines with data from any source, ranging from Had oop-based clusters to Excel worksheets. You'll learn how to break down big analysis tasks into manageable chunks and how to choose and use the best PySpark data abstraction for your unique needs. The Spark data processing engine is an amazing analytics factory: raw data comes in,and insight comes out. Thanks to its ability to handle massive amounts of data distributed across a cluster, Spark has been adopted as standard by organizations both big and small. PySpark, which wraps the core Spark engine with a Python-based API, puts Spark-based data pipelines in the hands of programmers and data scientists working with the Python programming language. PySpark simplifies Spark's steep learning curve, and provides a seamless bridge between Spark and an ecosystem of Python-based data science tools.

This is the last in a four book series comprising a critical review of the Unified Process that includes a survey of the alternate software processes and the synthesis of a more robust process. The transition and production phases are the final phases of the Unified Process that provide for the deployment, operation and support of the system among the user groups. This volume includes a masters' collection of best practices that include practical advice for successfully launching the software, applying personal processes, developing and enhancing organizational software processes, achieving reuse, conducting project assessments, saving a troubled project, testing the system, avoiding a maintenance nightmare, and operating and supporting the software.

This book constitutes the refereed proceedings of the artificial intelligence in intelligent systems section of the 10th Computer Science Online Conference 2021 (CSOC 2021), held online in April 2021. Artificial intelligence in intelligent systems topics are presented in this book. Modern hybrid and bio-inspired algorithms and their application are discussed in selected papers.

This book constitutes the refereed proceedings of the informatics and cybernetics in intelligent systems section of the 10th Computer Science Online Conference 2021 (CSOC 2021), held online in April 2021. Modern cybernetics and computer engineering papers in the scope of intelligent systems are an essential part of actual research topics. In this book, a discussion of modern algorithms approaches techniques is held.

This book is perhaps the first attempt to give full treatment to the topic of Software Design. It will facilitate the academia as well as the industry. This book covers all the topics of software design including the ancillary ones.

Like other sciences and engineering disciplines, software engineering requires a cycle of model building, experimentation, and learning. Experiments are valuable tools for all software engineers who are involved in evaluating and choosing between different methods, techniques, languages and tools.

The purpose of Experimentation in Software Engineering is to introduce students, teachers, researchers, and practitioners to empirical studies in software engineering, using controlled experiments. The introduction to experimentation is provided through a process perspective, and the focus is on the steps that we have to go through to perform an experiment. The book is divided into three parts. The first part provides a background of theories and methods used in experimentation. Part II then devotes one chapter to each of the five experiment steps: scoping, planning, execution, analysis, and result presentation. Part III completes the presentation with two examples. Assignments and statistical material are provided in appendixes. Overall the book provides indispensable information regarding empirical studies in particular for experiments, but also for case studies, systematic literature reviews, and surveys. It is a revision of the authors' book, which was published in 2000. In addition, substantial new material, e.g. concerning systematic literature reviews and case study research, is introduced. The book is self-contained and it is suitable as a course book in undergraduate or graduate studies where the need for empirical studies in software engineering is stressed. Exercises and assignments are included to combine the more theoretical material with practical aspects. Researchers will also benefit from the book, learning more about how to conduct empirical studies, and likewise practitioners may use it as a "cookbook" when evaluating new methods or techniques before implementing them in their organization."

Improving existing code-refactoring-is one of the most common tasks you'll face as a programmer. Five Lines of Code teaches you clear and actionable refactoring rules that you can apply without relying on intuitive judgements such as "code smells." It's written for working developers, guiding you step by step through applying refactoring patterns to the codebase of a 2D puzzle game. Following the author's expert perspective-that refactoring and code smells can be learned by following a concrete set of principles-you'll learn when to refactor your code, what patterns to apply to what problem, and the code characteristics that indicate it's time for a rework. Thanks to this hands-on guide, you'll find yourself programming faster while still delivering high-quality code that your teammates will love to work with. about the technologyRefactoring is a fact of life. All code is imperfect, and refactoring is a systematic process you can use to improve the quality of your codebase. Whatever your architecture, choice of OO language, or skill as a programmer, the continuous design improvements of refactoring make your code simpler, more readable, and less prone to bugs. You'll be amazed at the productivity boost of adding refactoring to your code hygiene routine-it's quicker to hammer out bad code and then improve it than spending hours writing good code in the first place! about the book Five Lines of Code teaches working developers the shortcuts to quality code. You'll follow author Christian Clausen's unique approach to teaching refactoring that's focused on concrete rules, and getting any method down to five lines or less to implement! There's no jargon or tricky automated-testing skills required, just easy guidelines and patterns illustrated by detailed code samples. Chapter by chapter you'll put techniques into action by refactoring a complete 2D puzzle game. Before you know it, you'll be making serious and tangible improvements to your codebase. what's inside The symptoms of bad code The extracting method, introducing strategy pattern, and many other refactoring patterns Modifying code safely, even when you don't understand it Writing stable code that enables change-by-addition Proper compiler practices Writing code that needs no comments Real-world practices for great refactoring about the readerFor developers who know an object-oriented programming language. about the author Christian Clausen works as a Technical Agile Coach teaching teams how to properly refactor their code. Previously he worked as a software engineer on the Coccinelle semantic patching project, an automated refactoring tool. He has an MSc in computer science, and five years' experience teaching software quality at a university level.

Updates content and introduces topics such as business changes and outsourcing. Addresses new cyber security risks such as IoT and Distributed Networks (i.e., blockchain). Covers strategy based on the OODA loop in the cycle. Demonstrates application of the concepts through short case studies of real-world incidents chronologically delineating related events. Discusses certifications and reference manuals in cyber security and digital forensics. Includes an entire chapter on tools used by professionals in the field.

Part of a new four-volume series presenting best practices using UP to develop object-oriented, component-based software, this book examines the second UP phase--elaboration--focusing on defining, validating, and baselining the architecture for a system. Illustrations throughout.

This book describes the state-of-the-art of software ecosystems. It constitutes a fundamental step towards an empirically based, nuanced understanding of the implications for management, governance, and control of software ecosystems. This is the first book of its kind dedicated to this emerging field and offers guidelines on how to analyze software ecosystems; methods for managing and growing; methods on transitioning from a closed software organization to an open one; and instruments for dealing with open source, licensing issues, product management and app stores. It is unique in bringing together industry experiences, academic views and tackling challenges such as the definition of fundamental concepts of software ecosystems, describing those forces that influence its development and lifecycles, and the provision of methods for the governance of software ecosystems. This book is an essential starting point for software industry researchers, product managers, and entrepreneurs. Contributors: T. Aaltonen, T.A. Alspaugh, C. Alves, M. Anvaari, H.U. Asuncion, O. Barbosa, S. Biffl, S. Brinkkemper, M.A. Cusumano, E. den Hartigh, D. Dhungana, R.P. dos Santos, A. Finkelstein, M. Goeminne, I. Groher, I. Hammouda, S. Jansen, A. Jimenez Salas, J. Kabbedijk, M. Kauppinen, T. Kilamo, Y.-R. Li, L. Luinenburg, T. Mens, T. Mikkonen, K.M. Popp, W. Scacchi, E. Schludermann, J. Souer, M. Tol, J. van Angeren, G. van Capelleveen, M. Viljainen, W. Visscher, C. Werner

Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming language Machine learning--a branch of Artificial Intelligence (AI) which enables computers to improve their results and learn new approaches without explicit instructions--allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. Practical Machine Learning in R provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. Bestselling author and data analytics experts Fred Nwanganga and Mike Chapple explain what machine learning is, demonstrate its organizational benefits, and provide hands-on examples created in the R programming language. A perfect guide for professional self-taught learners or students in an introductory machine learning course, this reader-friendly book illustrates the numerous real-world business uses of machine learning approaches. Clear and detailed chapters cover data wrangling, R programming with the popular RStudio tool, classification and regression techniques, performance evaluation, and more. Explores data management techniques, including data collection, exploration and dimensionality reduction Covers unsupervised learning, where readers identify and summarize patterns using approaches such as apriori, eclat and clustering Describes the principles behind the Nearest Neighbor, Decision Tree and Naive Bayes classification techniques Explains how to evaluate and choose the right model, as well as how to improve model performance using ensemble methods such as Random Forest and XGBoost Practical Machine Learning in R is a must-have guide for business analysts, data scientists, and other professionals interested in leveraging the power of AI to solve business problems, as well as students and independent learners seeking to enter the field.

Environment Modeling-Based Requirements Engineering for Software Intensive Systems provides a new and promising approach for engineering the requirements of software-intensive systems, presenting a systematic, promising approach to identifying, clarifying, modeling, deriving, and validating the requirements of software-intensive systems from well-modeled environment simulations. In addition, the book presents a new view of software capability, i.e. the effect-based software capability in terms of environment modeling.

A commitment to usability in user interface design and development offers enormous benefits, including greater user productivity, more competitive products, lower support costs, and a more efficient development process. But what does it mean to be committed to usability? Inside, a twenty-year expert answers this question in full, presenting the techniques of Usability Engineering as a series of product lifecycle tasks that result directly in easier-to-learn, easier-to-use software.
You'll learn to perform a complete requirements analysis and then incorporate the resulting goals and constraints in a highly structured, iterative design and development process. This process doesn't end with installation but instead begins anew with the collection of user feedback that will guide further development. Also covered are organizational issues related to the implementation of Usability Engineering, including cost justification, project planning, and organizational structures.
* Unites all current UE techniques in a single, authoritative resource, presenting a coherent lifecycle process in which each clearly defined task leads directly the next.
* Teaches concrete, immediately usable skills to practitioners in all kinds of product development organizations-from internal departments to commercial developers to consultants.
* Contains examples of actual software development projects and the ways in which they have benefited from Usability Engineering.
* Deals in specifics, not generalities-provides detailed templates and instructions for every phase of the Usability Engineering lifecycle.
* Pays special attention to Web site development and explains how Usability Engineering principles can be applied to the development of any interactive product.

This book aims to promote an understanding of the origins and dynamics of the software industry in a number of key emerging markets - Brazil, China, India and Israel, and to establish what experiences, if any, are potentially replicable in other prevailing markets. In-depth interviews with leading players in the industry are combined with other new data to provide a comparative study of the dynamics of the sector in emerging markets, to emphasise the public policy implications of these developments, and place them in a wider international context. The last 25 years have seen an explosive growth in the software industry, which is still overwhelmingly dominated by firms from North America and Europe. The authors argue that a number of companies from emerging markets have made significant headway and have even consolidated their positions on account of major cost advantages. They go on to explain the factors behind these developments, and conclude that the software industry, through its ability to project good corporate governance, its lack of hierarchy and widespread use of motivating working practices and compensation schemes, has proved a powerful example to other sectors in these emerging market economies. This book will be of immense interest to both academics and practitioners with an interest in development economics or technology.

How do you detangle a monolithic system and migrate it to a microservice architecture? How do you do it while maintaining business-as-usual? As a companion to Sam Newman's extremely popular Building Microservices, this new book details a proven method for transitioning an existing monolithic system to a microservice architecture. With many illustrative examples, insightful migration patterns, and a bevy of practical advice to transition your monolith enterprise into a microservice operation, this practical guide covers multiple scenarios and strategies for a successful migration, from initial planning all the way through application and database decomposition. You'll learn several tried and tested patterns and techniques that you can use as you migrate your existing architecture. Ideal for organizations looking to transition to microservices, rather than rebuild Helps companies determine whether to migrate, when to migrate, and where to begin Addresses communication, integration, and the migration of legacy systems Discusses multiple migration patterns and where they apply Provides database migration examples, along with synchronization strategies Explores application decomposition, including several architectural refactoring patterns Delves into details of database decomposition, including the impact of breaking referential and transactional integrity, new failure modes, and more