Thorsten Weyer

Model inspections are important to ensure high‐quality software and to satisfy legal obligations in model‐based engineering processes. As model‐based specifications are typically documented on type‐level, errors concerning the interactions between multiple system instances can go unnoticed. For collaborative cyber‐physical systems (CPS), a plethora of possible instance‐level configurations need to be taken into account. Therefore, we propose the definition of instance‐level review diagrams that show representative interactions of instance‐level configurations that help detect defects in the system specification. To evaluate the approach, we conducted a controlled experiment whose results indicate that instance‐level review diagrams have—compared with type‐level diagrams—important positive effects on reviewing processes for behavioral specifications of CPS. Specifically, the experiment provides empirical evidence that instance‐level review diagrams are significantly more expressive and effective than type‐level diagrams.

Digitalization changes the products the software profession develops. Digitalization also changes the way we develop products. Many companies of the software industry move away from rigid engineering processes towards agility, design thinking, and continuous delivery. In this article, we investigate embedded and cyber-physical systems using core technologies of the digital transformation and explore how these technologies change the role of the requirements engineer in the embedded industry. We sketch out skills that the next generation of requirements engineers must possess.

Software-intensive cyber-physical systems (CPS) perform essential tasks such as controlling automated production processes in industrial production plants. The required levels of autonomy, openness, and self-adaptation, as well as the dynamic nature of the context of such CPS, result in challenging tasks for their engineering. During operation, unexpected situations in which the system has insufficient knowledge about the current state of the system itself as well as its context may occur. Engineering CPS, e.g., for industrial production sites, must account for such uncertainties the system will have to cope with during its lifetime in a structured and systematic way. Since the development of CPS requires consideration of different system perspectives, current uncertainty modeling approaches cannot be applied right away, as they do not explicitly consider uncertainty aspects that affect different artifacts. To aid the engineering of CPS, this article presents a model-based approach to document uncertainty. We propose "Orthogonal Uncertainty Models," which closely integrate with other engineering artifacts from different perspectives, as a means for capturing a dedicated uncertainty viewpoint. Our approach has been evaluated in the industry automation domain. The application shows that the idea of regarding uncertainty within a dedicated perspective is highly beneficial. Particularly, our approach helps to uncover and document uncertainties related to behavioral, functional, and structural properties of a system, as well as uncertainties related to business models that would otherwise possibly remain covert.

Introduction: Technology transfer aims at supporting the transfer of results from software engineering research from academia to industrial application.Objective: This paper reports on the current state of technology transfer in software engineering.Method: We conducted a systematic literature review, in which we investigated 3070 papers. We identified in total 70 relevant papers, which were subject of a detailed analysis.Results: Many different approaches are proposed to foster technology transfer in software engineering. The majority of these approaches suggest direct collaboration between industry and academia or teaching new technologies in industrial training or university education. In addition, a considerable number of experience reports on technology transfer exist. Hence, a multitude of best practices, success stories, and lessons learned is reported. Among others, empirical evidence, maturity, and adaptability of the technology seem important preconditions for successful transfer, while social and organizational factors seem important barriers to successful technology transfer.Conclusion: Our findings can aid software engineering researchers in determining how best to support the transfer of their research results into practice. Furthermore, analysis of the literature also revealed that no reports exist on the combination of various technology transfer approaches, which could increase advantages of existing approaches while reducing their disadvantages.

Cyber-physical systems are increasingly developed for highly-automated purposes, such as industrial production plants. Not only the level of autonomy of these cyber-physical production systems, but also their potential lifespan, and the expectation that the system adapts throughout its life introduces challenges for the development process. To develop such systems in a structured manner, consideration of their context is essential. Suitable abstractions and perspectives must be employed to highlight different aspects of the context, such as structural or functional concerns. To ensure longevity and adaptability, the development process must account for changes in the context at runtime. This introduces a great deal of uncertainty. Current uncertainty modeling approaches cannot be applied right away, as they do not explicitly consider the multiple aspects of context analysis, which need to be documented in different artifacts. To aid the engineering of collaborative cyber-physical production systems, this paper presents a model-based approach to document context uncertainty. We propose “Orthogonal Uncertainty Models”, which closely integrate with context models from different perspectives. The approach has been evaluated using a case example from the industry automation domain, which is also presented herein.