Pablo Oliveira Antonino

Philipp Zech, Yanis Mair, Michael Vierhauser et al.

The adoption of Digital Twin technologies is rapidly expanding in diverse industrial, economic, and societal domains. Over the past decade, a multitude of studies, surveys, and investigations have been conducted, examining the nature, applications, and advantages of Digital Twins. However, up until now, no proposal for a comprehensive feature model exists that effectively captures the mandatory and optional features of Digital Twins. To address this shortcoming, in this article, we present a general feature model for Digital Twins. Based on a systematic mapping study of existing literature, we developed a generalized feature model for Digital Models, Shadows, and Twins. To assess the validity of our proposed feature model, we have applied them to three use cases from the emergency, vehicular, and manufacturing domain. We conjecture that our proposed general feature model advances the field around Digital Twins by facilitating informed decision-making during design, enabling improved model-driven development of Digital Twins, and, eventually, fostering verification~\&~validation of Digital Twins by delivering a model-based foundation for test case inference.

Jens Heidrich, Michael Kläs, Andreas Morgenstern et al.

In recent years, the role and the importance of software in the automotive domain have changed dramatically. Being able to systematically evaluate and manage software quality is becoming even more crucial. In practice, however, we still find a largely static approach for measuring software quality based on a predefined list of complexity metrics with static thresholds to fulfill. We propose using a more flexible framework instead, which systematically derives measures and evaluation rules based on the goals and context of a development project.

Cristiane Aparecida Lana, Milena Guessi, Pablo Oliveira Antonino et al.

Software-intensive Systems-of-Systems (SoS) refer to an arrangement of managerially and operationally independent systems(i.e., constituent systems), which work collaboratively towards the achievement of global missions. Because some SoS are developed for critical domains, such as healthcare and transportation, there is an increasing need to attain higher quality levels, which often justifies additional costs that can be incurred by adopting formal and semi-formal approaches (i.e., languages and techniques) for modeling requirements. Various approaches have been employed, but a detailed landscape is still missing, and it is not well known whether they are appropriate for addressing the inherent characteristics of SoS. The main contribution of this article is to present this landscape by reporting on the state of the art in SoS requirements modeling. This landscape was built by means of a systematic mapping and shows formal and semi-formal approaches grouped from model-based to property-oriented ones. Most of them have been tested in safety-critical domains, where formal approaches such as finite state machines are aimed at critical system parts, while semi-formal approaches (e.g., UML and i*) address non-critical parts. Although formal and semi-formal modeling is an essential activity, the quality of SoS requirements does not rely solely on which formalism is used, but also on the availability of supporting tools/mechanisms that enable, for instance, requirements verification along the SoS lifecycle