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Uncertainty is present in model-based developments in many different ways. In the context of composing model-based analysis tools, this chapter discusses how the combination of different models can increase or decrease the overall uncertainty. It explores how such uncertainty could be more explicitly addressed and systematically managed, with the goal of defining a conceptual framework to deal with and manage it. We proceed towards this goal both with a theoretical reasoning and a practical application through an example of designing a peer-to-peer file-sharing protocol. We distinguish two main steps: (i) software system modelling and (ii) model-based performance analysis by highlighting the challenges related to the awareness that model-based development in software engineering needs to coexist with uncertainty. This core chapter addresses Challenge 5 introduced in Chap. 3 of this book (living with uncertainty).

The work presents a scalable process implementation for modular, highly-automated model-based development of safety-critical flight-control software based on current standards for airborne software development. Central element is a modular design and code generation process including the respective development rules and artifacts. New software tools support the management of bidirectional traceability between requirements and models as well as the automated build of artifacts and verification of their up-to-dateness, consistency, and completeness., Die Arbeit stellt eine skalierbare Prozessimplementierung für modulare, hochautomatisierte modellbasierte Entwicklung sicherheitskritischer Flugsteuerungssoftware auf Basis aktueller Luftfahrtstandards vor. Zentrales Element ist ein modularer Design- und Codegenerierungsprozess mit Entwicklungsrichtlinien und zugehörigen Artefakten. Neue Softwarewerkzeuge unterstützen die Verwaltung von bidirektionaler Rückverfolgbarkeit zwischen Anforderungen und Modellen sowie die automatisierte Erstellung von Softwareartefakten und deren Überprüfung auf Aktualität, Konsistenz und Vollständigkeit.

Fueled by an increasing demand for computational power and high data-rate low-latency on-board communication, the automotive electrical and electronic architectures are evolving from distributed to consolidated domain and centralised architectures. Future electrical and electronic automotive architectures are envisioned to leverage heterogeneous computing platforms, where several different processing units will be embedded within electronic control units. These powerful control units are expected to be connected by high-bandwidth and low-latency on-board backbone networks. This paper draws on the industrial collaboration with the Swedish automotive industry for tackling the challenges associated to the model-based development of predictable embedded software for contemporary and evolving automotive E/E architectures., DPAC - Dependable Platforms for Autonomous systems and Control, HERO: Heterogeneous systems - software-hardware integration, DESTINE: Developing Predictable Vehicle Software Utilizing Time Sensitive Networking, Automation in High-performance Cyber Physical Systems Development, PANORAMA - Boosting Design Efficiency for Heterogeneous³ Systems

Model-based development and continuous integration each separately are methods to improve the productivity of development of complex modern software systems. We investigate industrial adoption of these two phenomena in combination, i.e., applying continuous integration practices in model-based development projects. Through semi-structured interviews, eleven engineers at three companies with different modelling practices share their views on perceived and experienced impediments to this adoption. We find some cases in which this introduction is undesired and expected to not be beneficial. For other cases, we find and categorize several impediments and discuss how they are dealt with in industrial practice. Model synchronization and tool interoperability are found the most challenging to overcome and the ways in which they are circumvented in g to overcome and the ways in which they are circumvented in practice are detrimental for introducing continuous integration.

Model-based development of complex embedded systems commonly leverages multiple models to describe systems at different levels of abstraction and from different viewpoints. Inconsistencies between these models may cause delays or late changes throughout system design, development and maintenance. Therefore, an efficient model-based development practice requires support for managing consistency between different models. This is complicated in practice because these models are possibly created in several different modelling languages and modelling tools. Furthermore, in order to be suitable for industrial adoption, consistency checking support must fit within current development processes and environments. This extended abstract describes a model-based development scenario from which a need for consistency checking emerges, followed by a discussion of requirements for consistency checking from a development process point of view. We also include a brief summary of early work on a prototype tool addressing these requirements. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)., Export Date: 2 January 2020; Conference Paper; Correspondence Address: Jongeling, R.; Mälardalen UniversitySweden; email: robbert.jongeling@mdh.se

In model-based development projects, models at different abstraction levels capture different aspects of a software system, e.g., specification or design. Inconsistencies between these models can cause inefficient and incorrect development. A tool-based framework to assist developers creating and maintaining models conforming to different languages (i.e. heterogeneous models) and consistency between them is not only important but also much needed in practice. In this work, we focus on assisting developers bringing about multi-view consistency in the context of agile model-based development, through frequent, lightweight consistency checks across views and between heterogeneous models. The checks are lightweight in the sense that they are easy to create, edit, use and maintain, and since they find inconsistencies but do not attempt to automatically resolve them. With respect to ease of use, we explicitly separate the two main concerns in defining consistency checks, being (i) which modelling elements across heterogeneous models should be consistent with each other and (ii) what constitutes consistency between them. We assess the feasibility and illustrate the potential usefulness of our consistency checking approach, from an industrial agile model-based development point-of-view, through a proof-of-concept implementation on a sample project leveraging models expressed in SysML and Simulink. A continuous integration pipeline hosts the initial definition and subsequent execution of consistency checks, it is also the place where the user can view results of consistency checks and reconfigure them.

Physical protection system (PPS) is developed to protect the assets or facilities against threats. A systematic analysis of the capabilities and intentions of potential threat capabilities is needed resulting in a so-called Design Basis Threat (DBT) document. A proper development of DBT is important to identify the system requirements that are required for adequately protecting a system and to optimize the resources needed for the PPS. In this paper we propose a model-based systems engineering approach for developing a DBT based on feature models. Based on a domain analysis process, we provide a metamodel that defines the key concepts needed for developing DBT. Subsequently, a reusable family feature model for PPS is provided that includes the common and variant properties of the PPS concepts detection, deterrence and response. The configuration processes are modeled to select and analyze the required features for implementing the threat scenarios. Finally, we discuss the integration of the DBT with the PPS design process.

A-CPS - Automation in High-performance Cyber Physical Systems Development, PANORAMA - Boosting Design Efficiency for Heterogeneous³ Systems