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Modern cars exist in an vast number of variants. Thus, variability has to be dealt with in all phases of the development process, in particular during model-based development of software-intensive functionality using Matlab/Simulink. Currently, variability is often encoded within a functional model leading to so called 150%-models which easily become very complex and do not scale for larger product lines.To counter these problems, we propose a modular variability modeling approach for Matlab/Simulink based on the concept of delta modeling [8,9,24]. A functional variant is described by a delta encapsulating a set of modifications. A sequence of deltas can be applied to a core product to derive the desired variant. We present a prototypical implementation, which is integrated into Matlab/Simulink and offers graphical editing of delta models.

Today's cars are characterized by many functional variants. There are many reasons for the underlying variability, from the adaptation to diverse markets to different technical aspects, which are based on a cross-platform reuse of software functions. Inevitably, this variability is reflected in the model-based automotive software development. A modeling language, which is widely used for modeling embedded software in the automotive industry, is MATLAB/Simulink. There are concepts facing the high demand for a systematic handling of variability in Simulinkmodels. However, not every concept is suitable for every automotive application. In order to present a classification of concepts for modeling variability in Simulink, this paper first has to determine the relevant use cases for variant handling in modelbased automotive software development. Existing concepts for modeling variability in Simulink will then be presented before being classified in relation to the previously determined use cases.

Embedded software systems, e.g. automotive, robotic or automation systems are highly configurable and consist of many software components being available in different variants and versions. To identify the degree of reusability between these different occurrences of a component, it is necessary to determine the functional backward and forward compatibility between them. Based on this information it is possible to identify in which system context a component can be replaced safely by another version, e.g. exchanging an older component, or variant, e.g. introducing new features, to achieve the same functionality.This paper presents a model checking approach to determine behavioral compatibility of Simulink models, obtained from different component variants or during evolution. A prototype for automated compatibility checking demonstrates its feasibility. In addition implemented optimizations make the analysis more efficient, when the compared variants or versions are structurally similar.A case study on a driver assistance system provided by Daimler AG shows the effectiveness of the approach to automatically compare Simulink components.

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