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Astract: The reliable, efficient and seamless exchange of business information is essential for a successful execution of the interwoven business processes. However, development of the contents for electronic data exchange is time consuming and usually can not follow the agile demands of the today's business. If we could contextualize the pieces of the currently valid business information, we could predict its possible context specific variations. Therefore, the business contextual knowledge in which the already existing data contents are valid could be exploited to (semi-) automatically generate new, more homogeneous contents for electronic data interchange.

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Astract: In model-driven engineering (MDE), models constitute the main development artifacts. As a consequence, their quality significantly affects the quality of the final product. Thus, adequate techniques are required for ensuring the quality of models. We present a testing framework, comprising a test specification language and an interpreter, for validating the functional correctness of UML activities. For this purpose, we utilize the executability of a subset of UML provided by the fUML standard. As UML activities are employed for different purposes, from high-level process specifications to low-level object manipulations, the proposed testing framework not only allows to validate the correctness in terms of input/output relations, but also supports testing intermediate results, as well as the execution order of activity nodes. First experiments indicate that the proposed testing framework is useful for ensuring the correct behavior of fUML activities.

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Astract: Business transactions between companies are more and more executed by a flow of well-defined electronic business documents. The resulting inter-organizational business processes are often realized by concepts known from service-oriented computing. Exchanging a business document corresponds to a service call and the input/output of the service calls commonly follows a certain business document standard. However, these standards typically present the superset of all required elements used in any business context. In a specific context (in a specific industry, in a specific geopolitical region, etc.) the input/output is adjusted to this context by constraints on the generic structure. Accordingly, a specific service is always used in a specific context. It follows that it is important to define the business context of a service (in a structured format). For this purpose we have developed the Business Context Ontology model (BCOnt). In this paper we elaborate on the theoretical concepts and the underlying algorithms as well as on their implementation in practice.

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Astract: We steadily aim at improving our first year´s university course Introduction to Object-Oriented Modelling. To that end we explore how technological teaching support may be used to extend the classical classroom experience for the students. For several years, we used Web-based out-of-the-box e-learning tools for providing additional teaching support. This solution works well, but has some severe restrictions. In this paper, we show how to overcome these restrictions with a custom implementation. Further, we are now starting to explore mobile facilities as offered by smartphone Apps as well as social media facilities in order to enhance the learning experience in our modelling course. We report on our first experiences with these kinds of technologies.

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Astract: The Resource-Event-Agent (REA) ontology is a powerful and well accepted approach towards the design of enterprise information systems in the academic world. However, it still lacks application in industry products. Software like ERP applications might benefit from REA data structure by building their product's core on a robust, economic theory based, business ontology. Consequently, we have lately started a feasibility study with an Austrian ERP vendor, in which we investigate whether or not the ERP vendor can use the REA ontology as basis for their new ERP system. This paper is aimed at raising questions about uncertainties in REA we came across in our study so far.

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Astract: Model-Driven Engineering promotes the use of models to conduct the different phases of the software development. In this way, models are transformed between different languages and notations until code is generated for the final application. Hence, the construction of correct Model-to-Model (M2M) transformations becomes a crucial aspect in this approach. Even though many languages and tools have been proposed to build and execute M2M transformations, there is scarce support to specify correctness requirements for such transformations in an implementation-independent way, i.e., irrespective of the actual transformation language used. In this paper we fill this gap by proposing a declarative language for the specification of visual contracts, enabling the verification of transformations defined with any transformation language. The verification is performed by compiling the contracts into QVT to detect disconformities of transformation results with respect to the contracts. As a proof of concept, we also report on a graphical modeling environment for the specification of contracts, and on its use for the verification of transformations in several case studies.

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