Model-Based Engineering of Collaborative Embedded Systems

This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years

Innovation Modeling Grid

This technical document presents the committee driven innovation modeling methodology "Innovation Modeling Grid" in detail. This document is the successor of three publications on IMoG and focuses on presenting all details of the methodologyComment: ~170p, many figures, technical documen

Effects of variability in models: a family of experiments

The ever-growing need for customization creates a need to maintain software systems in many different variants. To avoid having to maintain different copies of the same model, developers of modeling languages and tools have recently started to provide implementation techniques for such variant-rich systems, notably variability mechanisms, which support implementing the differences between model variants. Available mechanisms either follow the annotative or the compositional paradigm, each of which have dedicated benefits and drawbacks. Currently, language and tool designers select the used variability mechanism often solely based on intuition. A better empirical understanding of the comprehension of variability mechanisms would help them in improving support for effective modeling. In this article, we present an empirical assessment of annotative and compositional variability mechanisms for three popular types of models. We report and discuss findings from a family of three experiments with 164 participants in total, in which we studied the impact of different variability mechanisms during model comprehension tasks. We experimented with three model types commonly found in modeling languages: class diagrams, state machine diagrams, and activity diagrams. We find that, in two out of three experiments, annotative technique lead to better developer performance. Use of the compositional mechanism correlated with impaired performance. For all three considered tasks, the annotative mechanism was preferred over the compositional one in all experiments. We present actionable recommendations concerning support of flexible, tasks-specific solutions, and the transfer of established best practices from the code domain to models

Innovation Modeling Grid

This technical document presents the committee driven innovation modeling methodology "Innovation Modeling Grid" in detail. This document is the successor of three publications on IMoG and focuses on presenting all details of the methodology

A Framework for Seamless Variant Management and Incremental Migration to a Software Product-Line

Context: Software systems often need to exist in many variants in order to satisfy varying customer requirements and operate under varying software and hardware environments. These variant-rich systems are most commonly realized using cloning, a convenient approach to create new variants by reusing existing ones. Cloning is readily available, however, the non-systematic reuse leads to difficult maintenance. An alternative strategy is adopting platform-oriented development approaches, such as Software Product-Line Engineering (SPLE). SPLE offers systematic reuse, and provides centralized control, and thus, easier maintenance. However, adopting SPLE is a risky and expensive endeavor, often relying on significant developer intervention. Researchers have attempted to devise strategies to synchronize variants (change propagation) and migrate from clone&own to an SPL, however, they are limited in accuracy and applicability. Additionally, the process models for SPLE in literature, as we will discuss, are obsolete, and only partially reflect how adoption is approached in industry. Despite many agile practices prescribing feature-oriented software development, features are still rarely documented and incorporated during actual development, making SPL-migration risky and error-prone.Objective: The overarching goal of this PhD is to bridge the gap between clone&own and software product-line engineering in a risk-free, smooth, and accurate manner. Consequently, in the first part of the PhD, we focus on the conceptualization, formalization, and implementation of a framework for migrating from a lean architecture to a platform-based one.Method: Our objectives are met by means of (i) understanding the literature relevant to variant-management and product-line migration and determining the research gaps (ii) surveying the dominant process models for SPLE and comparing them against the contemporary industrial practices, (iii) devising a framework for incremental SPL adoption, and (iv) investigating the benefit of using features beyond PL migration; facilitating model comprehension.Results: Four main results emerge from this thesis. First, we present a qualitative analysis of the state-of-the-art frameworks for change propagation and product-line migration. Second, we compare the contemporary industrial practices with the ones prescribed in the process models for SPL adoption, and provide an updated process model that unifies the two to accurately reflect the real practices and guide future practitioners. Third, we devise a framework for incremental migration of variants into a fully integrated platform by exploiting explicitly recorded metadata pertaining to clone and feature-to-asset traceability. Last, we investigate the impact of using different variability mechanisms on the comprehensibility of various model-related tasks.Future work: As ongoing and future work, we aim to integrate our framework with existing IDEs and conduct a developer study to determine the efficiency and effectiveness of using our framework. We also aim to incorporate safe-evolution in our operators

The Essence of Software Engineering

Software Engineering; Software Development; Software Processes; Software Architectures; Software Managemen

Interdisziplinäre Variabilitätsmodellierung und Performance Analyse für langlebige Systeme in der Automatisierungstechnik

In this day and age, automation systems have to deal with differing customer needs, environmental requirements and multiple application contexts. Automation systems have to be variable enough to satisfy all of these demands. The development and maintenance of such highly-customizable systems is a challenging task and becomes increasingly more difficult considering multiple involved engineering disciplines and long lifetimes, which is characteristic for industrial systems of the automation domain. Software product line engineering provides developers with fundamental concepts to manage the variability of such systems. However, these concepts are not established in the domain of automation systems. In addition, the involvement of multiple engineering disciplines poses a threat to existing SPL techniques. This thesis contributes novel approaches to improve the development and maintenance of software-intensive automation product lines. In total, three major contributions are made, spanning across the complete design phase of an automation system. (1) The feature modeling process is improved by detecting hidden dependencies between interrelated feature models from separate engineering disciplines. Furthermore, hidden dependencies and occurring defects in the feature models are explained in a user-friendly manner. (2) A model-driven development approach is introduced consisting of UML models, which are extended with delta modeling to manage variability in the automation product line. The models encompass information that is needed to automatically derive and analyze a performance model. (3) Subsequently, an efficient family-product-based performance analysis is proposed for the previously derived UML models that is vastly superior compared to common product-based approaches. All of these techniques have been evaluated using multiple case studies, with one being a real-world automation system.In der heutigen Zeit sehen sich Automatisierungssysteme mit einer steigenden Komplexität konfrontiert. Einzelne Kunden haben unterschiedliche Ansprüche an das System und ebenso müssen Umweltbedingungen der verschiedenen Betriebsumgebungen sowie abweichende Anwendungsgebiete bei der Entwicklung eines Automatisierungssystems berücksichtigt werden. Diese Komplexitätsaspekte werden unter dem Stichwort Variabilität zusammengefasst. Ein Automatisierungssystem muss in der Lage sein, sämtliche Anforderungen zu erfüllen. Die Entwicklung und Wartung dieser Systeme wird jedoch durch die stetig wachsende Variabilität und eine potentiell lange Lebensdauer immer schwieriger. Zusätzlich sind an dem Entwicklungsprozess eines Automatisierungssystems mehrere Ingenieursdisziplinen beteiligt. Die Techniken aus dem Bereich der Software-Produktlinienentwicklung bilden Lösungen, um die Variabilität beherrschbar zu machen. In der Automatisierungstechnik sind diese Techniken weitgehend unbekannt und durch den interdisziplinären Charakter oft nicht ausreichend. Daher werden in dieser Dissertation neue Ansätze entwickelt und vorgestellt, die auf die Domäne der Automatisierungstechnik zugeschnitten sind. Insgesamt leistet diese Dissertation folgende drei wissenschaftlichen Beiträge: (1) Die Entwicklung von Feature-Modellen wird durch die Detektion von verborgenen Abhängigkeiten, die zwischen Feature-Modellen der unterschiedlichen Ingenieursdisziplinen existieren, verbessert. Gleichzeitig liefert der vorgestellte Algorithmus die Erklärung für die Existenz dieser Abhängigkeiten. Dieses Konzept wird auf weitere Defekte in Feature-Modellen ausgeweitet. (2) Einen modell-basierten Ansatz zur Entwicklung eines Automatisierungssystems. Der Ansatz basiert auf Modellen aus der UML, die mit Hilfe der Delta Modellierung Variabilität abbilden können. Zusätzlich sind die Modelle mit Informationen über Performance Eigenschaften angereichert und erlauben die automatische Ableitung eines Performance-Modells. (3) Eine effiziente Performance Analyse von allen Varianten des Automatisierungssystems, die auf den zuvor abgeleiteten Performance-Modellen basiert. Alle Beiträge wurden mit Fallstudien evaluiert. Eine Fallstudie repräsentiert ein reales Automatisierungssystem