Over more than two decades, numerous variability modeling techniques have been introduced in academia and industry. However, little is known about the actual use of these techniques. While dozens of experience reports on software product line engineering exist, only very few focus on variability modeling. This lack of empirical data threatens the validity of existing techniques, and hinders their improvement. As part of our effort to improve empirical understanding of variability modeling, we present the results of a survey questionnaire distributed to industrial practitioners. These results provide insights into application scenarios and perceived benefits of variability modeling, the notations and tools used, the scale of industrial models, and experienced challenges and mitigation strategies
Abstract. Large software product lines need to manage complex variability. A common approach is variability modeling-creating and maintaining models that abstract over the variabilities inherent in such systems. While many variability modeling techniques and notations have been proposed, little is known about industrial practices and how industry values or criticizes this class of modeling. We attempt to address this gap with an exploratory case study of three companies that apply variability modeling. Among others, our study shows that variability models are valued for their capability to organize knowledge and to achieve an overview understanding of codebases. We observe centralized model governance, pragmatic versioning, and surprisingly little constraint modeling, indicating that the effort of declaring and maintaining constraints does not always pay off.
A new error indicator is proposed to guide the -adaptive finite-element analysis of three-dimensional microwave devices. The indicator makes use of the properties of the hierarchal elements to target directly the error in the scattering parameters of the device. The indicator is used to guide the -adaptive analysis of three rectangular waveguide components: a U-bend, a waveguide transformer, and a multiaperture-coupled iris filter. It is shown that the new indicator is able to provide more accurate values at a lower computational cost than a previous indicator.Index Terms-Error indicator, finite-element (FE) method, microwave devices, -adaption, waveguide components.
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