This paper proposes a real-time power system simulation framework that is capable of simulating steady state and electromechanical transients of power systems, with sub-millisecond time resolution. The framework can integrate power system component models packed as reusable Functional Mockup Units (FMUs) to flexibly create power system simulations without the need to recreate new models for different power systems. The integration of individual components is based on a novel model decomposition method, which enables the FMU reuse in different system contexts, as well as a parallel simulation execution onto multi-core machines. Furthermore, the paper proposes methods to optimize the allocation of components to cores and shows that the framework can simulate a medium voltage distributed electrical grid of about 20 components in real-time on a commodity multi-core machine.

This paper advances the state-of-the-art by enhancing an existing provider-independent modelling language towards the complete specification of both serverless and hybrid multi-cloud applications. This extension has been validated by a use case developed in the context of the Functionizer project.

Refactoring is a prevalent technique that can be applied for improving software structural quality. Refactorings can be applied at different levels of granularity to resolve 'bad smells' that can be identified in various artifacts (e.g., methods, classes, packages). A fundamental software engineering principle that can be applied at various levels of granularity is the Single Responsibility Principle (SRP), whose violation leads to the creation of lengthy, complex and non-cohesive artifacts; incurring smells like Long Method, God Class, and Large Package. Such artifacts, apart from being large in size tend to implement more than one functionalities, leading to decreased cohesion, and increased coupling. In this paper, we study the effect of applying refactorings that lead to conformance to the SRP, at all three levels of granularity to identify possible differences between them. To study these differences, we performed an industrial case study on two large-scale software systems (more than 1,500 classes). Since SRP is by definition related to modularity, as a success measure for the refactoring we use coupling and cohesion metrics. The results of the study can prove beneficial for both researchers and practitioners, since various implications can be drawn.

The concepts of decision forces and the decision forces viewpoint were proposed to help software architects to make architectural decisions more transparent and the documentation of their rationales more explicit. However, practical experience reports and guidelines on how to use the viewpoint in typical industrial project setups are not available. Existing works mainly focus on basic tool support for the documentation of the viewpoint or show how forces can be used as part of focused architecture review sessions. With this paper, we share experiences and lessons learned from applying the decision forces viewpoint in a distributed industrial project setup, which involves consultants supporting architects during the re-design process of an existing large software system. Alongside our findings, we describe new forces that can serve as template for similar projects, discuss challenges applying them in a distributed consultancy project, and share ideas for potential extensions.

Hardware-in-the-loop (HIL) testing is an integral part of the development of power system automation solutions. HIL test beds facilitate system-level testing and validation of controllers against their specifications. The information required for HIL test bed configurations is typically scattered across different tools used in the development of power system automation solutions. These tools often have different formats and naming schemes. This implies that a significant effort is required for consolidating data from the tools and for creating valid test configurations from the consolidated data. This paper presents a Model-Driven Engineering (MDE) approach for creating HIL test configurations in a tool-, platform-, and protocol-agnostic manner. It shows how the MDE approach can be applied in practice to derive test configurations based on the information originating from different tools in a semi-automated fashion.