Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Written by foremost experts in the field, Engineering Modeling Languages provides end-to-end coverage of the engineering of modeling languages to turn domain knowledge into tools.
The book provides a definition of different kinds of modeling languages, their instrumentation with tools such as editors, interpreters and generators, the integration of multiple modeling languages to achieve a system view, and the validation of both models and tools. Industrial case studies, across a range of application domains, are included to attest to the benefits offered by the different techniques. The book also includes a variety of simple worked examples that introduce the techniques to the novice user.
The book is structured in two main parts. The first part is organized around a flow that introduces readers to Model Driven Engineering (MDE) concepts and technologies in a pragmatic manner. It starts with definitions of modeling and MDE, and then moves into a deeper discussion of how to express the knowledge of particular domains using modeling languages to ease the development of systems in the domains.
The second part of the book presents examples of applications of the model-driven approach to different types of software systems. In addition to illustrating the unification power of models in different software domains, this part demonstrates applicability from different starting points (language, business knowledge, standard, etc.) and focuses on different software engineering activities such as Requirement Engineering, Analysis, Design, Implementation, and V&V.
Each chapter concludes with a small set of exercises to help the reader reflect on what was learned or to dig further into the examples. Many examples of models and code snippets are presented throughout the book, and a supplemental website features all of the models and programs (and their associated tooling) discussed in the book.
Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Memmo's summaries are gold before exams. I don't have to re-read 800 pages two weeks before — just the important parts.
The AI chat has saved me the night before an exam more than once. I just keep asking until I get it — no waiting on a study group to reply.
The quizzes hit exactly what I need to know. Memmo tracks what I get stuck on — so I only practice what's worth it.
Flashcards with spaced repetition are magic. Memmo knows when I'm about to forget something and brings it back.
The AI podcasts are my favorite. I listen on my way to school and get a recap without sitting at a computer.
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