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Astract: In optimistic versioning, multiple developers are allowed to modify an artifact at the same time. On the one hand this approach increases productivity as the development process is never stalled due to locks on an artifact. On the other hand conflicts may arise when it comes to merging the different modifications into one consolidated version. In general, the resolution of such conflicts is not only cumbersome, but also error-prone. Especially if the artifacts under version control are models, little support is provided by standard versioning systems. In this paper we present the enhanced versioning process of the model versioning system AMOR. We show how AMOR is configured in order to obtain a precise conflict report which allows the recommendation of automatically executable resolution patterns. The user of AMOR chooses either one of the recommendations or performs manual resolution. The manual resolution may be in collaboration with other developers and allows to infer new resolution patterns which may be applied in similar situations.

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Astract: During the last decade several approaches have been proposed for easing the burden of writing model transformation rules manually. Among them are Model Transformation By-Demonstration (MTBD) approaches which record actions performed on example models to derive general operations. A current restriction of MTBD is that until now they are only available for in-place transformations, but not for model-to-model (M2M) transformations. In this paper, we extend our MTBD approach, which is designed for in-place transformations, to also support M2M transformations. In particular, we propose to demonstrate each transformation rule by modeling a source model fragment and a corresponding target model fragment. From these example pairs, the applied edit operations are computed which are input for a semi-automatic process for deriving the general transformation rules. For showing the applicability of the approach, we developed an Eclipse-based prototype supporting the generation of ATL code out of EMF-based example models.

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Astract: Model transformations play a key role in the vision of Model-Driven Engineering. Nevertheless, mechanisms like abstraction, variation and composition for specifying and applying reusable model transformations - like urgently needed for resolving recurring structural heterogeneities - are insufficiently supported so far. Therefore, we propose to specify model transformations by a set of pre-defined mapping operators (MOps), each resolving a certain kind of structural heterogeneity. Firstly, these MOps can be used in the context of arbitrary metamodels since they abstract from concrete metamodel types. Secondly, MOps can be tailored to resolve certain structural heterogeneities by means of black-box reuse. Thirdly, based on a systematic set of kernel MOps resolving basic heterogeneities, composite ones can be built in order to deal with more complex scenarios. Finally, an extensible library of MOps is proposed, allowing for automatically executable mapping specifications since every MOp exhibits a clearly defined operational semantics.

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Astract: Model transformations play a key role in the vision of Model- Driven Engineering (MDE) whereby the overcoming of structural heterogeneities, being a result of applying different meta-modeling constructs for the same semantic concept, is a challenging, recurring problem, urgently demanding for reuse of transformations. In this respect, an approach is required which (i) abstracts from the concrete execution language allowing to focus on the resolution of structural heterogeneities, (ii) keeps the impedance mismatch between specification and execution low enabling seamless debuggability, and (iii) provides formal underpinnings enabling model checking. Therefore, we propose to specify model transformations by applying a set of abstract mapping operators (MOPs), each resolving a certain kind of structural heterogeneity. For specifying the operational semantics of the MOPs, we propose to use Transformation Nets (TNs), a DSL on top of Colored Petri Nets (CPNs), since it allows (i) to keep the impedance mismatch between specification and execution low and (ii) to analyze model transformations by evaluating behavioral properties of CPNs.

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Astract: Social networks have seen enormous growth over the past few years, providing also a powerful new channel for distributing personalized services. Personalization, however, is exacerbated because social content is scattered across different social networks serving specific human needs and social networkers are particularly reluctant to share social content with service providers, if not under their full control. This paper sketches TheHiddenU, a social nexus exploiting semantic techniques for integrating, profiling and privatising social content, thereby providing the technical prerequisites for personalized brokerage, a new, sustainable business model in the Social Web.