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Detecting and Explaining Conflicts in Attributed Feature Models
Product configuration systems are often based on a variability model. The
development of a variability model is a time consuming and error-prone process.
Considering the ongoing development of products, the variability model has to
be adapted frequently. These changes often lead to mistakes, such that some
products cannot be derived from the model anymore, that undesired products are
derivable or that there are contradictions in the variability model. In this
paper, we propose an approach to discover and to explain contradictions in
attributed feature models efficiently in order to assist the developer with the
correction of mistakes. We use extended feature models with attributes and
arithmetic constraints, translate them into a constraint satisfaction problem
and explore those for contradictions. When a contradiction is found, the
constraints are searched for a set of contradicting relations by the
QuickXplain algorithm.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301
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Evaluating Patient Preferences of Maintenance Therapy for the Treatment of Chronic Obstructive Pulmonary Disease: A Discrete Choice Experiment in the UK, USA and Germany.
Introduction: With increasing availability of different treatments for chronic obstructive pulmonary disease (COPD), we sought to understand patient preferences for COPD treatment in the UK, USA, and Germany using a discrete choice experiment (DCE). Methods: Qualitative research identified six attributes associated with COPD maintenance treatments: ease of inhaler use, exacerbation frequency, frequency of inhaler use, number of different inhalers used, side effect frequency, and out-of-pocket costs. A DCE using these attributes, with three levels each, was designed and tested through cognitive interviews and piloting. It comprised 18 choice sets, selected using a D-efficient experimental design. Demographics and disease history were collected and the final DCE survey was completed online by participants recruited from panels in the UK, USA and Germany. Responses were analyzed using mixed logit models, with results expressed as odds ratios (ORs). Results: Overall, 450 participants (150 per country) completed the DCE; most (UK and Germany, 97.3%; USA, 98.0%) were included in the final analysis. Based on relative attribute importance, avoidance of side effects was found to be most important (UK: OR 11.65; USA: OR 7.17; Germany: OR 11.45; all p<0.0001), followed by the likelihood of fewer exacerbations (UK: OR 2.22; USA: OR 1.63; Germany: OR 2.54; all p<0.0001) and increased ease of use (UK: OR 1.84; USA: OR 1.84; Germany: OR 1.60; all p<0.0001). Number of inhalers, out-of-pocket costs, and frequency of inhaler use were found to be less important. Preferences were relatively consistent across the three countries. All participants required a reduction in exacerbations to accept more frequent inhaler use or use of more inhalers. Conclusion: When selecting COPD treatment, individuals assigned the highest value to the avoidance of side effects, experiencing fewer exacerbations, and ease of inhaler use. Ensuring that patients' preferences are considered may encourage treatment compliance
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