Meta-Programming and Model-Driven Meta-Program Development: Principles, Processes and Techniques presents an overall analysis of meta-programming, focusing on insights of meta-programming techniques, heterogeneous meta-program development processes in the context of model-driven, feature-based and transformative approaches. The fundamental concepts of meta-programming are still not thoroughly understood, in this well organized book divided into three parts the authors help to address this. Chapters include: Taxonomy of fundamental concepts of meta-programming; Concept of structural heterogeneous meta-programming based on the original meta-language; Model-driven concept and feature-based modeling to the development process of meta-programs; Equivalent meta-program transformations and metrics to evaluate complexity of feature-based models and meta-programs; Variety of academic research case studies within different application domains to experimentally verify the soundness of the investigated approaches. Both authors are professors at Kaunas University of Technology with 15 years research and teaching experience in the field. Meta-Programming and Model-Driven Meta-Program Development: Principles, Processes and Techniques is aimed at post-graduates in computer science and software engineering and researchers and program system developers wishing to extend their knowledge in this rapidly evolving sector of science and technology.

Model-Driven Software Development (MDSD) is currently a highly regarded development paradigm among developers and researchers. With the advent of OMG's MDA and Microsoft's Software Factories, the MDSD approach has moved to the centre of the programmer's attention, becoming the focus of conferences such as OOPSLA, JAOO and OOP. MDSD is about using domain-specific languages to create models that express application structure or behaviour in an efficient and domain-specific way. These models are subsequently transformed into executable code by a sequence of model transformations. This practical guide for software architects and developers is peppered with practical examples and extensive case studies. International experts deliver: * A comprehensive overview of MDSD and how it relates to industry standards such as MDA and Software Factories. * Technical details on meta modeling, DSL construction, model-to-model and model-to-code transformations, and software architecture. * Invaluable insight into the software development process, plus engineering issues such as versioning, testing and product line engineering. * Essential management knowledge covering economic and organizational topics, from a global perspective. Get started and benefit from some practical support along the way!

This monograph presents the challenges, vision and context to design smart learning objects (SLOs) through Computer Science (CS) education modelling and feature model transformations. It presents the latest research on the meta-programming-based generative learning objects (the latter with advanced features are treated as SLOs) and the use of educational robots in teaching CS topics. The introduced methodology includes the overall processes to develop SLO and smart educational environment (SEE) and integrates both into the real education setting to provide teaching in CS using constructivist and project-based approaches along with evaluation of pedagogic outcomes. Smart Learning Objects for Smart Education in Computer Science will appeal to researchers in CS education particularly those interested in using robots in teaching, course designers and educational software and tools developers. With research and exercise questions at the end of each chapter students studying CS related courses will find this work informative and valuable too.

At the centre of the methodology used in this book is STEM learning variability space that includes STEM pedagogical variability, learners’ social variability, technological variability, CS content variability and interaction variability. To design smart components, firstly, the STEM learning variability space is defined for each component separately, and then model-driven approaches are applied. The theoretical basis includes feature-based modelling and model transformations at the top specification level and heterogeneous meta-programming techniques at the implementation level. Practice includes multiple case studies oriented for solving the task prototypes, taken from the real world, by educational robots. These case studies illustrate the process of gaining interdisciplinary knowledge pieces identified as S-knowledge, T-knowledge, E-knowledge, M-knowledge or integrated STEM knowledge and evaluate smart components from the pedagogical and technological perspectives based on data gathered from one real teaching setting. Smart STEM-Driven Computer Science Education: Theory, Methodology and Robot-based Practices outlines the overall capabilities of the proposed approach and also points out the drawbacks from the viewpoint of different actors, i.e. researchers, designers, teachers and learners.

The importance of architecture for software systems is widely accepted, but the role of architecture in the overall development process is not so clear. Presenting an architecture-centric process, Model-Driven Software Systems Development Using the Meta-Artifact Process makes the role of architecture clear. At its core, this book is about developing software systems and, more specifically, software code. It describes three major innovations for making software, which are combined with five widely used enabling technologies, to provide a complete, hypothesis-driven software development process known as Meta-Artifact Process (MAP). Having complete requirements is essential for making good software and supports the hypothesis-driven MAP. MAP offers properties, qualities, and capabilities that help stakeholders and developers understand and reason about a domain and target systems of interest. MAP, through the central role of the Meta-Artifact and incorporating the view that a computer program is a hypothesis about the requirements, offers new ways to look at systems and their development, even changing the roles of developers and stakeholders. Recommending agile methods wherever appropriate while supporting the OMG Essence standard and working within an overarching architecture, MAP presents ways to ensure that the requirements are complete and correct. It helps to identify likely points during development to form alternative hypotheses about them. Because MAP requires an underlying software development process, it can provide that clarity to existing processes in which the organization’s developers are already proficient. This book provides concrete examples from two broad but diverse areas—Accounting Information Systems in the commercial area and a military command and control system—to show the wide applicability of MAP in both commercial and defense domains.

The book discusses the evolution of STEM-driven Computer Science (CS) Education based on three categories of Big Concepts, Smart Education (Pedagogy), Technology (tools and adequate processes) and Content that relates to IoT, Data Science and AI. For developing, designing, testing, delivering and assessing learning outcomes for K-12 students (9-12 classes), the multi-dimensional modelling methodology is at the centre. The methodology covers conceptual and feature-based modelling, prototyping, and virtual and physical modelling at the implementation and usage level. Chapters contain case studies to assist understanding and learning. The book contains multiple methodological and scientific innovations including models, frameworks and approaches to drive STEM-driven CS education evolution. Educational strategists, educators, and researchers will find valuable material in this book to help them improve STEM-driven CS education strategies, curriculum development, and new ideas for research.

This book constitutes the refereed proceedings of the 10th European Conference on Technology Enhanced Learning, EC-TEL 2015, held in Toledo, Spain, in September 2015. The 27 full papers, 19 short papers, 9 demo papers and 23 posters were carefully reviewed and selected from 176 submissions. They address topics such as blended learning; self-regulated and self directed learning; reflective learning; intelligent learning systems; learning communities; learning design; learning analytics; learning assessment; personalization and adaptation; serious games; social media; massive open online courses (MOOCs); schools of the future.

Conceptual modeling has always been one of the main issues in information systems engineering as it aims to describe the general knowledge of the system at an abstract level that facilitates user understanding and software development. This collection of selected papers provides a comprehensive and extremely readable overview of what conceptual modeling is and perspectives on making it more and more relevant in our society. It covers topics like modeling the human genome, blockchain technology, model-driven software development, data integration, and wiki-like repositories and demonstrates the general applicability of conceptual modeling to various problems in diverse domains. Overall, this book is a source of inspiration for everybody in academia working on the vision of creating a strong, fruitful and creative community of conceptual modelers. With this book the editors and authors want to honor Prof. Antoni Olivé for his enormous and ongoing contributions to the conceptual modeling discipline. It was presented to him on the occasion of his keynote at ER 2017 in Valencia, a conference that he has contributed to and supported for over 20 years. Thank you very much to Antoni for so many years of cooperation and friendship.

Today, reliable software systems are the basis of any business or company. The continuous further development of those systems is the central component in software evolution. It requires a huge amount of time- man power- as well as financial resources. The challenges are size, seniority and heterogeneity of those software systems. Christian Wagner addresses software evolution: the inherent problems and uncertainties in the process. He presents a model-driven method which leads to a synchronization between source code and design. As a result the model layer will be the central part in further evolution and source code becomes a by-product. For the first time a model-driven procedure for maintenance and migration of software systems is described. The procedure is composed of a model-driven reengineering and a model-driven migration phase. The application and effectiveness of the procedure are confirmed with a reference implementation applied to four exemplary systems.

This book constitutes the refereed proceedings of the 14th International Conference on Model Driven Engineering Languages and Systems, MODELS 2011, held in Wellington, New Zealand, in October 2011. The papers address a wide range of topics in research (foundations track) and practice (applications track). For the first time a new category of research papers, vision papers, are included presenting "outside the box" thinking. The foundations track received 167 full paper submissions, of which 34 were selected for presentation. Out of these, 3 papers were vision papers. The application track received 27 submissions, of which 13 papers were selected for presentation. The papers are organized in topical sections on model transformation, model complexity, aspect oriented modeling, analysis and comprehension of models, domain specific modeling, models for embedded systems, model synchronization, model based resource management, analysis of class diagrams, verification and validation, refactoring models, modeling visions, logics and modeling, development methods, and model integration and collaboration.