A validation of QDAcity-RE for domain modeling using qualitative data analysis

Using qualitative data analysis (QDA) to perform domain analysis and modeling has shown great promise. Yet, the evaluation of such approaches has been limited to single-case case studies. While these exploratory cases are valuable for an initial assessment, the evaluation of the efficacy of QDA to solve the suggested problems is restricted by the common single-case case study research design. Using our own method, called QDAcity-RE, as the example, we present an in-depth empirical evaluation of employing qualitative data analysis for domain modeling using a controlled experiment design. Our controlled experiment shows that the QDA-based method leads to a deeper and richer set of domain concepts discovered from the data, while also being more time efficient than the control group using a comparable non-QDA-based method with the same level of traceability.

Formal requirements modeling for cyber-physical systems engineering: an integrated solution based on FORM-L and Modelica

The increasing complexity of cyber-physical systems (CPSs) makes their design, development and operation extremely challenging. Due to the nature of CPS that involves many heterogeneous components, which are often designed and developed by organizations belonging to different engineering domains, it is difficult to manage, trace and verify their properties, requirements and constraints throughout their lifecycle by using classical techniques. In this context, the paper presents an integrated solution to formally define system requirements and automate their verification through simulation. The solution is based on the FOrmal Requirements Modeling Language and the Modelica language. The solution is exemplified through two case studies concerning a Trailing-Edge High-Lift system and a Heating, Ventilation and Air Conditioning system.