Engineering Modeling Languages Turning Domain Knowledge into Tools 1st editon by Benoit Combemale , Robert France , Jean Marc Jézéquel , Bernhard Rumpe , James Steel , Didier Vojtisek ISBN 1466583738 978-1466583733

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ISBN 10:1466583738  
ISBN 13:978-1466583733
Author: Benoit Combemale , Robert France , Jean-Marc Jézéquel , Bernhard Rumpe , James Steel , Didier Vojtisek

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.

Engineering Modeling Languages Turning Domain Knowledge into Tools 1st Table of contents:

CHAPTER 1 ■ What’s a Model?

1.1 Introduction

1.2 Modeling in Science

1.3 Modeling in Engineering

1.4 Illustrative Example: Cellular Automata

1.4.1 Cellular Automaton Topology

1.4.2 Cellular Automaton Evolution Rules

1.4.3 Modeling Cellular Automata

1.5 Semantic Foundations of MDE: the Meaning of Models

1.5.1 Basics of Denotational Semantics

1.5.2 Underspecification and Interpretation in the Real World

1.5.3 Operations on Models

1.6 Exercises

CHAPTER 2 ■ What’s a Modeling Language?

2.1 Why We Need Modeling Languages

2.2 Concrete Syntax

2.2.1 Textual Concrete Syntax

2.2.2 Graphical Concrete Syntax: Box-and-Line Diagrams

2.2.3 Graphical Concrete Syntax: Tabular Notations

2.2.4 Graphical Concrete Syntax: Trees

2.3 Abstract Syntax

2.3.1 Abstract Syntax of Textual Languages

2.3.2 Abstract Syntax of Graphical Languages

2.3.3 Concrete and Abstract Syntax Relationship

2.4 Semantics of a Modeling Language

2.4.1 Denotational Semantics

2.4.2 Operational Semantics

2.5 Exercises

CHAPTER 3 ■ Metamodeling with MOF and Ecore

3.1 Metamodel and Meta-Language

3.2 Metamodel, Meta-Language, Language Workbench, and Meta-Metamodel

3.3 Meta-Object Facility (MOF)

3.4 Ecore and EMF

3.5 Representations for Machine Consumption

3.5.1 Textual Representations for Machine Consumption

3.5.2 Database Representation

3.6 Illustrative Example: Metamodels for the Cellular Automaton

3.7 Exercises

CHAPTER 4 ■ Metamodeling with OCL

4.1 The Object Constraint Language

4.1.1 Invariant and Its Context

4.1.2 Basic Operations

4.1.3 Collections

4.1.4 Quantification, Collection, Selection

4.1.5 Navigation along Associations

4.1.6 Derived Attributes

4.2 Advanced Features of OCL

4.2.1 Nature of OCL: First Order and Expression Language?

4.2.2 Specifying Operations in OCL

4.2.3 Further Concepts of OCL

4.2.4 OCL Used at Different Modeling Levels

4.3 Usage of OCL for MOF

4.3.1 OCL for Context Conditions

4.3.1.1 Illustrative Example: Geometry Constraints

4.3.1.2 Illustrative Example: Enhanced Versions of OCL

4.3.1.3 Illustrative Example: Filter Constraints

4.3.1.4 Illustrative Example: Language Constraints from Metamodel Composition

4.3.2 OCL for the Execution Domains (Semantics)

4.3.2.1 Illustrative Example: Evaluating Expressions

4.3.2.2 Illustrative Example: Describing the Effect of a Regular Geometry

4.3.3 Conjunct Use of MOF and OCL

4.4 Exercises

CHAPTER 5 ■ Building Editors and Viewers

5.1 Introduction

5.2 Generic versus Specific Concrete Syntax

5.3 Visual Representations for Human Reading

5.4 Tree View

5.4.1 Generic Tree View

5.4.2 Customization of the Tree View

5.4.3 Illustrative Example: Tree Editor for CAIR

5.5 Diagram View (Box and Line)

5.5.1 Generic Diagram View

5.5.2 Customization of the Diagram View

5.5.3 Illustrative Example: Graphical Editor for Universe Models

5.6 Textual View

5.6.1 Generic Textual View

5.6.2 Customization of the Textual View

5.6.3 Illustrative Example: A Textual Editor for Cellular Automation Evolution Rules

5.7 Tabular View

5.8 Other Views

CHAPTER 6 ■ Model Transformation: from Contemplative to Productive Models

6.1 Motivation

6.2 Overview of Model Transformations

6.2.1 Model-to-Text vs. Model-to-Model

6.2.2 Homogeneous vs. Heterogeneous

6.2.3 Declarative vs. Imperative

6.2.4 Unidirectional vs. Bidirectional

6.2.5 Traceability

6.3 Kermeta: An Executable Metamodeling Approach

6.3.1 Kermeta as an Ecore Extension

6.3.2 Kermeta as an Xtend Extension

6.3.3 Kermeta as an OCL Extension

6.3.4 Kermeta as a Metamodel Integration Platform

6.3.5 Examples with Kermeta

6.3.6 Scaling Up Transformations in Kermeta

6.4 Exercises

CHAPTER 7 ■ Interpreter

7.1 Ingredients for Interpretation

7.1.1 Runtime Data

7.1.2 Computational Steps

7.2 Design Pattern Interpreter

7.3 Combining the Interpreter and Visitor Design Patterns

7.3.1 Approach Overview

7.3.2 Illustrative Example: Interpreter for Cellular Automaton Using a Visitor

7.4 Aspect Weaving with Static Introduction

7.4.1 Approach Overview

7.4.2 Illustrative Example: Operational Semantics for Cellular Automaton Using Static Introduction

7.4.3 Adding Runtime Data Using Static Introduction

7.4.4 Modeling the Interpreter Runtime Data

7.5 Exercises

CHAPTER 8 ■ Refactoring and Refinement

8.1 Foundations

8.1.1 Refactorings

8.1.2 Refinement

8.1.3 Refinements, Refactorings, and Compositions

8.1.4 Testing Refactorings and Refinements

8.2 Applying Model Refactoring

8.2.1 Illustrative Example: CAIR-Lite Refactoring

8.2.2 Illustrative Example: CAER Refactoring

8.3 Applying Model Refinement

8.3.1 Example and Caveats: Data Structure Refinement

8.3.2 Example: Data Structure Refinement with OCL

8.3.3 Example: Behavioral Refinement with OCL

8.3.4 Example: Behavioral Refinement with State Machines

8.4 Exercises

CHAPTER 9 ■ Generators

9.1 Usefulness of Text and Code Generation

9.2 Model-to-Text Transformations

9.2.1 General Purpose Transformation Languages for Text Generation

9.2.2 Illustrative Example: Straightforward Approach

9.2.3 Template-Based Languages

9.2.4 Illustrative Example: Template Approach

9.2.5 Pretty Printing

9.2.6 Mixing All Approaches

9.3 Code Generation

9.3.1 Illustrative Example: Code Generation

9.4 Documentation Generation

9.4.1 Illustrative Example: Documentation Generation for a Universe Model

9.5 Model Generation

9.5.1 Illustrative Example: Generation of VM Model from Initialization Rules

9.6 Test Generation: Model-Based Validation and Verification

9.6.1 Introduction

9.6.2 Model-Based Testing

9.6.2.1 Formal Verification of Properties

9.6.2.2 Intensive Simulation

9.6.2.3 Testing

9.6.3 Automatic Test Generation: A Use Case–Driven Approach

9.6.3.1 Principle of the Approach

9.6.3.2 Simulating the Use Cases

9.6.3.3 Exhaustive Simulation and Transition System

9.6.3.4 Generating Test Cases from Test Objectives and Sequence Diagrams

9.7 Exercises

CHAPTER 10 ■ Variability Management

10.1 Context of Software Product Lines

10.2 Modeling Variability with Feature Diagrams

10.3 Advanced Variability Modeling Methods

10.4 Amalgamated Approach

10.4.1 Annotate a Base Model by Means of Ad hoc Extensions

10.4.2 Combine a Reusable Variability Metamodel with Different Domain Metamodels

10.5 Separating the Assets and the Variability Concern

10.6 Exploitation of Variability Models

10.6.1 Automated Analysis of Feature Models

10.6.2 Multi-Views and Compositional Approaches

10.6.3 Product Derivation

10.6.3.1 Derivation in Amalgamated Approaches

10.6.3.2 Product Derivation in Separated Approaches: The CVL Example

10.6.4 Test Generation

10.7 MDE for SPL: Wrapup

CHAPTER 11 ■ Scaling Up Modeling

11.1 Heterogeneous Modeling

11.2 Model Merging and Weaving

11.2.1 Models and Aspects

11.2.2 Design and Aspect Weaving

11.2.3 Weaving Aspects at Model Level

11.2.4 Weaving Aspects in Sequence Diagrams

11.2.5 Weaving More than One Aspect: The Detection Problem

11.2.6 Weaving More than One Aspect: The Composition Problem

11.2.7 Discussion

11.2.8 Building Project-Specific Aspect Weavers with Kermeta

11.2.9 Merging and Weaving: Wrapup

11.3 Language Reuse with Model Typing

11.3.1 Limits of the Conformance Relations

11.3.2 Model Typing

11.4 Model Slicing

11.5 Software Language Engineering

11.6 Exercises

CHAPTER 12 ■ Wrapup: Metamodeling Process

12.1 Actors

12.2 Tools to Build

12.3 Metamodeling Process

12.4 Metamodeling Process Variants

12.5 Metamodeling Guidelines

12.5.1 Decompose Large Transformations into Smaller Ones

12.5.2 Illustrative Example: Reusing Existing Smaller Transformations

12.5.3 Illustrative Example: Using a Transformation Generator

12.5.4 Illustrative Example: Reducing Transformation Complexity

12.6 Illustrative Example: Process Followed to Build Cellular Automaton Tooling

CHAPTER 13 ■ Language Engineering: The Logo Example

13.1 Introduction

13.2 Metamodeling Logo

13.3 Weaving Static Semantics

13.3.1 The Object Constraint Language

13.3.2 Expressing the Logo Static Semantics in OCL

13.3.3 Adding the Logo Static Semantics to Its Metamodel

13.4 Weaving Dynamic Semantics to Get an Interpreter

13.4.1 Logo Runtime Model

13.4.2 Operational Semantics

13.4.3 Getting an Interpreter

13.5 Compilation as a Kind of Model Transformation

13.6 Model-to-Model Transformation

13.7 Concrete Syntax

13.8 Exercises

CHAPTER 14 ■ Model-Driven Engineering of a Role-Playing Game

14.1 Introduction

14.2 Metamodeling the SRD 3.5

14.2.1 Main Concepts of the SRD 3.5

14.2.2 Metamodeling the SRD Rules

14.2.3 Implementing the SRD Metamodel

14.2.3.1 The Core Package

14.2.3.2 The Expression Package

14.2.3.3 The Action Package

14.2.3.4 The Bonus Package

14.2.4 Example: Creating a Tiny Rule Set

14.3 Weaving Dynamic Semantics to Get an Interpreter

14.3.1 SRD Runtime Model

14.3.2 Mapping the Abstract Syntax to the Runtime Model

14.4 Compilation of a Web-Based Editor

14.4.1 Requirements

14.4.2 Overview of JHipster

14.4.3 Targeting JHipster

14.5 Testing a Rule Set

14.5.1 Random Intensive Testing

14.5.2 Exhaustive Testing

14.5.3 Pairwise Testing

14.6 Exercises

CHAPTER 15 ■ Civil/Construction Engineering: The BIM Example

15.1 Introduction

15.2 Abstract Syntax of Buildings

15.2.1 Industry Foundation Classes

15.3 Model Storage: Large Models

15.4 Concrete Syntax

15.5 Case Study: Clash Detection

15.6 Case Study: Quantity Take-Off

15.6.1 Background: Description of the Domain

15.6.2 Automated Estimator: Buildings and Bills

15.6.2.1 The Intelligent Building Model Language

15.6.2.2 The Bill of Quantities Language

15.6.3 The Take-Off Rules Language and Tool Support

15.6.3.1 Take-Off Rules

15.6.3.2 Tool Support for Quantity Take-Off

15.6.3.3 Traceability and Debugging

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Benoit Combemale,Robert France,Jean Marc Jézéquel,Bernhard Rumpe,James Steel,Didier Vojtisek,Engineering Modeling