Abstract
Software product family approaches have found broad adoption in the embedded systems industry, where systems are modelled from several views such as the software view and the hardware view. A view uses the feature perceived only from the view’s perspective. For example, from a hardware view we perceive only the hardware features. Generating the feasible products of the considered family from these views and the constraints imposed on them is called view reconciliation.
The paper presents a mathematical framework to reason on view reconciliation. It articulates this process as a product of sets of product families. We give the conditions under which the product forms a direct product. We also demonstrate that (multi-) view reconciliation is an operation that is indifferent to the order of integrating the views. Finally, we show that personalizing medical devices is a simple view reconciliation operation that gives a direct-product allowing, using projections, the retrieval of any of the involved views from the conciliated view.
This research is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) through the grant RGPIN 2014-06115, by the National Natural Science Foundation of China through the grants No. 61602293 and No. 61572306, and by the Science and Technology Commission of Shanghai Municipality through the grant No. 15YF1403900.
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Notes
- 1.
Throughout this paper, we adopt the uniform linear notation provided. The general form of the notation is
where \(\star \) is the quantifier, x is the dummy or quantified variable, R is predicate representing the range, and P is an expression representing the body of the quantification. An empty range is taken to mean \(\mathsf{true}\) and we write 
; in this case the range is over all values of variable x.
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Chen, Y., Zhang, B., Khedri, R., Miao, H. (2017). A Framework for Multi-view Reconciliation and for Medical Devices Personalization. In: Duan, Z., Ong, L. (eds) Formal Methods and Software Engineering. ICFEM 2017. Lecture Notes in Computer Science(), vol 10610. Springer, Cham. https://doi.org/10.1007/978-3-319-68690-5_5
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