Model-Based Engineering of Collaborative Embedded Systems: Extensions of the SPES Methodology

Preface
Table of Contents
1 CrESt Use Cases
	1.1 Introduction
	1.2 Vehicle Platooning
	1.3 Adaptable and Flexible Factory
	1.4 Autonomous Transport Robots
2 Engineering of Collaborative Embedded Systems
	2.1 Introduction
	2.2 Background
	2.3 Collaborating Embedded Systems
		2.3.1 Collaborative and Collaborating Systems
		2.3.2 Goals of System Networks
		2.3.3 Coordination in System Networks
		2.3.4 Dynamics in System Networks
		2.3.5 Functions
	2.4 Problem Dimensions of Collaborative Embedded Systems
		2.4.1 Challenges Related to Collaboration
		2.4.2 Challenges Related to Dynamics
	2.5 Application in the Domains “Cooperative Vehicle Automation” and “Industry 4.0”
		2.5.1 Challenges in the Application Domain “Cooperative Vehicle Automation”
			Collaboration
			Dynamics
		2.5.2 Challenges in the Application Domain “Industry 4.0”
			Collaboration
			Dynamics
	2.6 Concepts and Methods for the Development of Collaborative Embedded Systems
		2.6.1 Enhancements Regarding SPES2020 and SPES_XT
		2.6.2 Collaboration
			Goals
			Functions and Behavior
			Architecture and Structure
			Communication
		2.6.3 Dynamics
			Goals
			Functions and Behavior
			Architecture and Structure
			Context
			Uncertainty
	2.7 Conclusion
	2.8 Literature
	2.9 Appendix
3 Architectures for Flexible Collaborative Systems
	3.1 Introduction
	3.2 Designing Reference Architectures
		3.2.1 Method for Designing Reference Architectures
		3.2.2 Application Example: Reference Architecture for Adaptable and Flexible Factories
	3.3 Reference Architecture for Operator Assistance Systems
		3.3.1 Simulation-Based Operator Assistance
		3.3.2 Design Decisions
		3.3.3 Technical Reference Architecture
		3.3.4 Workflow of Services and Data Flow
		3.3.5 Application Example for an Adaptable and Flexible Factory
	3.4 Checkable Safety Cases for Architecture Design
		3.4.1 Checkable Safety Case Models – A Definition
		3.4.2 Checkable Safety Case Patterns
		3.4.3 An Example of Checkable Safety Case Patterns
	3.5 Conclusion
	3.6 Literature
4 Function Modeling for Collaborative Embedded Systems
	4.1 Introduction
	4.2 Methodological Approach
	4.3 Background
	4.4 Metamodel for Functions of CESs and CSGs
		4.4.1 Systems, CESs, and CSGs
		4.4.2 Functions
		4.4.3 Goal Contribution and Fulfillment
		4.4.4 Roles
		4.4.5 Context and Adaptivity
	4.5 Evaluation of the Metamodel
		4.5.1 Abstraction
		4.5.2 Relationships between Functions
		4.5.3 Openness and Dynamicity
		4.5.4 Goal Contributions
		4.5.5 Relationships Between Functions and Systems
		4.5.6 Input/Output Compatibility
		4.5.7 Runtime Restructuring
	4.6 Application of the Metamodel
		4.6.1 Example from the Adaptable and Flexible Factory
		4.6.2 Modeling of Goals for Transport Robots
	4.7 Related Work
	4.8 Conclusion
	4.9 Literature
5 Architectures for Dynamically Coupled Systems
	5.1 Introduction
	5.2 Specification Modeling of the Behavior of Collaborative System Groups
	5.3 Modeling CES Functional Architectures
		5.3.1 Scenario
		5.3.2 Modelling
		5.3.3 Analysis
	5.4 Extraction of Dynamic Architectures
		5.4.1 Methods
		5.4.2 Software Product Line Engineering
		5.4.3 Product-Driven Software Product Line Engineering
		5.4.4 Family Mining — A Method for Extracting Reference Architectures from Model Variants
		5.4.5 Summary
	5.5 Functional Safety Analysis (Online)
		5.5.1 Functional Testing
		5.5.2 Communication Errors
	5.6 Conclusion
	5.7 Literature
6 Modeling and Analyzing Context-Sensitive Changes during Runtime
	6.1 Introduction and Motivation
	6.2 Solution Concept
	6.3 Ontology and Modeling
		6.3.1 Ontology Building
		6.3.2 Capability Modeling
		6.3.3 Variability Modeling for Context-Sensitive Reconfiguration
		6.3.4 Scenario-Based Modeling
	6.4 Model Integration and Execution
		6.4.1 Model Generation for Simulation Models
			Model Generation via Knowledge Graph
			Application to a Real Production System
		6.4.2 Capability Matching
	6.5 Conclusion
	6.6 Literature
7 Handling Uncertainty in
Collaborative Embedded
Systems Engineering
	7.1 Uncertainty in Collaborative Embedded Systems
		7.1.1 Conceptual Ontology for Handling Uncertainty
		7.1.2 Different Kinds of Uncertainty
	7.2 Modeling Uncertainty
		7.2.1 Orthogonal Uncertainty Modeling
			Modeling Concepts and Notation
			Example
		7.2.2 Modeling Uncertainty in Traffic Scenarios
			Modeling Traffic Scenarios for CSGs
			Behavioral Uncertainty Modeling
			Risk Assessment
	7.3 Analyzing Uncertainty
		7.3.1 Identifying Epistemic Uncertainties
			Uncertainty Sources at the Type Level
			Uncertainty Sources at the Instance Level
			EURECA
		7.3.2 Assessing Data-Driven Uncertainties
			Three Types of Uncertainty Sources
			Managing Uncertainty during Operation
			Uncertainty Wrapper – Architecture and Application
			Uncertainty Wrappers – Limitations and Advantages
	7.4 Conclusion
	7.5 Literature
8 Dynamic Safety Certification for Collaborative Embedded Systems at Runtime
	8.1 Introduction and Motivation
	8.2 Overview of the Proposed Safety Certification Concept
	8.3 Assuring Runtime Safety Based on Modular Safety Cases
		8.3.1 Modeling CESs and their Context
			Modeling the Context
			Content Ontology
			Modeling Context in the Adaptable Factory
		8.3.2 Runtime Uncertainty Handling
			Concept Overview
			Development of a U-Map for the Adaptable Factory
		8.3.3 Runtime Monitoring of CESs and their Context
			Meta-model SQUADfps
			Case Study Example
		8.3.4 Integrated Model-Based Risk Assessment
		8.3.5 Dynamic Safety Certification
	8.4 Design and Runtime Contracts
		8.4.1 Design-Time Approach for Collaborative Systems
			Creating the CSG Specification
			Safety-Relevant Activities
		8.4.2 Contracts Concept
		8.4.3 Runtime Evaluation of Safety Contracts
			Simulative Approach for Validation of Safety Contracts
			Case Study: Vehicle Platoon Example
	8.5 Conclusion
	8.6 Literature
9 Goal-Based Strategy Exploration
	9.1 Introduction
	9.2 Goal Modeling for Collaborative System Groups
	9.3 Goal-Based Strategy Development
	9.4 Goal Operationalization (KPI Development)
	9.5 Modeling Methodology for Adaptive Systems with MATLAB/Simulink
	9.6 Collaboration Framework for Goal-Based Strategies
		9.6.1 Fleet Management in Collaborative Resource Networks
		9.6.2 Collaboration Framework
		9.6.3 Collaboration Design in Decentralized Fleet Management
	9.7 Conclusion
	9.8 Literature
10 Creating Trust in Collaborative Embedded Systems
	10.1 Introduction
	10.2 Building Trust during Design Time
		Testing framework for CSGs
		Model
		View
		Controller
	10.3 Building Trust during Runtime
	10.4 Monitoring Collaborative Embedded Systems
		Runtime Monitoring
		Runtime Monitoring of Collaborative System Groups
		Distributedness:
		Embeddedness:
		Runtime Monitoring of Interaction Protocols
		Monitoring Functional Correctness
		Agreement:
		Existence:
		Maximum:
		Monitoring Correct Timing Behavior
		U
		Ut
	10.5 Conclusion
	10.6 Literature
11 Language Engineering for Heterogeneous Collaborative Embedded Systems
	11.1 Introduction
	11.2 MontiCore
	11.3 Language Components
	11.4 Language Component Composition
	11.5 Language Product Lines
	11.6 Conclusion
	11.7 Literature
12 Development and Evaluation of Collaborative Embedded Systems using Simulation
	12.1 Introduction
		12.1.1 Motivation
		12.1.2 Benefits of Using Simulation
	12.2 Challenges in Simulating Collaborative Embedded Systems
		12.2.1 Design Time Challenges
		12.2.2 Runtime Challenges
	12.3 Simulation Methods
	12.4 Application
	12.5 Conclusion
	12.6 Literature
13 Tool Support for CoSimulation-Based Analysis
	13.1 Introduction
	13.2 Interaction of Different Simulations
	13.3 General Tool Architecture
	13.4 Implementing Interoperability for Co-Simulation
	13.5 Distributed Co-Simulation
	13.6 Analysis of Simulation Results
	13.7 Conclusion
	13.8 Literature
14 Supporting the Creation of Digital Twins for CESs
	14.1 Introduction
		14.2.1 Demonstration
			Automotive Smart Ecosystems
			Smart Grids
	14.2 Building Trust through Digital Twin Evaluation
	14.3 Conclusion
	14.4 Literature
15 Online Experiment-Driven Learning and Adaptation
	15.1 Introduction
	15.2 A Self-Optimization Approach for CESs
	15.3 Illustration on CrowdNav
	15.4 Conclusion
	15.5 Literature
16 Compositional Verification using Model Checking and Theorem Proving
	16.1 Introduction
	16.2 Approach
	16.3 Example
		16.3.1 Specification
		16.3.2 Verification
	16.4 Conclusion
	16.5 Literature
17 Artifact-Based Analysis for the Development of Collaborative Embedded Systems
	17.1 Introduction
	17.2 Foundations
		UML/P
		Class Diagrams in UML/P
		Object Diagrams in UML/P
		OCL
	17.3 Artifact-Based Analysis
		Artifact Model Creation
		Specification of Artifact Data Analysis
		Artifact-Based Analyses
	17.4 Artifact Model for Systems Engineering Projects with Doors NG and Enterprise Architect
		17.4.1 Artifact Modeling of Doors NG and Enterprise Architect
		17.4.2 Static Extractor for Doors NG and Enterprise Architect Exports
		17.4.3 Analysis of the Extracted Artifact Data
	17.5 Conclusion
	17.6 Literature
18 Variant and Product Line CoEvolution
	18.1 Introduction
	18.2 Product Line Engineering
	18.3 Propagating Updates from Domain Engineering Level to Application Engineering Level
		18.3.1 The Challenge of Propagating Updates
		18.3.2 Artifact Evolution and Co-Changes
		18.3.3 Changes to the Variant Derivation Process
		18.3.4 Applicability and Limitations
		18.3.5 Implementation
	18.4 Propagating Changes from Application Engineering Level to Domain Engineering Level
		18.4.1 The Challenge of Lifting Changes
		18.4.2 A Process for Lifting Changes
		18.4.3 Deducing Feature Information
			Underlying Model
			Seeding Feature Information
			Assigning Changes to Features
		18.4.4 Applicability and Limitations
	18.5 Conclusion
	18.6 Literature
19 Advanced Systems Engineering
	19.1 Introduction
	19.2 Advanced Systems Engineering
	19.3 MBSE as an Essential Basis
	19.4 The Integrated Approach of SPES and SPES_XT
	19.5 Methodological Extensions: From SPES to ASE
	19.6 Conclusion
	19.7 Literature
Appendices
A – Author Index
B – Partner
	Bertrandt GmbH
	Expleo Germany GmbH
	FEV Europe GmbH
	fortiss GmbH
	Fraunhofer Institute for Open Communication Systems FOKUS
	Fraunhofer Institute for Experimental Software Engineering (IESE)
	Helmut Schmidt University Hamburg
	Humboldt-Universität zu Berlin
	INCHRON AG
	InSystems Automation GmbH
	itemis AG
	Model Engineering Solutions GmbH
	OFFIS e.V.
	PikeTec GmbH
	pure-systems GmbH
	Robert Bosch GmbH
	RWTH Aachen University
	Siemens AG
	Technical University of Kaiserslautern
	Technical University of Munich
	Technische Universität Berlin – Daimler Center for Automotive Information Technology Innovations (DCAITI)
	Technische Universität Braunschweig
	University of Duisburg-Essen, paluno – The Ruhr Institute for Software Technology
C – List of Publications