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Astract: Wozu UML @ Classroom? . Für erste Einblicke in die Grundlagen der objektorientierten Modellierung. . Für einen raschen und erfolgreichen Einstieg in die Welt der UML. . Für einen verständlichen Überblick über die Konzepte von UML. . Für ein effektives und effizientes Erlernen der grafischen Notation und Regeln von UML. . Für das Kennenlernen der wichtigsten UMLDiagramme: Anwendungsfalldiagramm, Klassendiagramm, Zustandsdiagramm, Sequenzdiagramm und Aktivitätsdiagramm. . Für ein besseres Verständnis des Zusammenspiels der verschiedenen Diagramme. Profitieren Sie von jahrelanger Erfahrung mit der UML in Lehre und Forschung!

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Astract: Model-Driven Engineering (MDE) places models as first-class artifacts throughout the software lifecycle. In this context, model transformations are crucial for the success of MDE, being comparable in role and importance to compilers for high-level programming languages. Thus, several model transformation approaches have been developed in the last decade, whereby originally most of them are based on the abstract syntax of modeling languages. However, this implementation specific focus makes it difficult for modelers to develop model transformations, because they are familiar with the concrete syntax but not with its computer internal representation. To tackle this problem, model transformation by-example approaches have been proposed which follow the same fundamental idea as query by-example and programming by-example approaches. Instead of using the computer internal representation of models, examples represented in concrete syntax are used to define transformations. Because different transformation scenarios occur in MDE, different by-example approaches have been developed. This chapter gives an overview on the emerging concepts, techniques, and approaches in this young by-example area.

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Astract: Inter-organizational systems span from business models over business process models to their execution on top of a service-oriented architecture. In our project BSopt we have developed an integrated model-driven approach that addresses the different layers and builds up-on well-estabilshed languages on each of these layers. When applying our integrated methodology we recognized that models for the same business case are similar, but still varying for different business partner networks. Accordingly, a systematic approach to derive a model from another model, i.e., from a reference model, is needed. Significant achievements have been made by the reference modeling community in finding ways to leverage the potentials of model reuse in business process modeling. In this paper we outline the potentials of adapting design techniques known from reference modeling to the specific needs of inter-organizational system develpment even if we do not provide a solution yet.

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Astract: The United Nations Centre for Trade Facilitation and eBusiness (UN/CEFACT) provides the Core Components approach for defining standard business document types based on all-embracing, reusable building blocks. For utilizing standard business document types in concrete business scenarios, these standard business document types need customizing resulting in business document type variants. However, the current approach is missing sufficient mechanisms for managing the resulting variants. First, customizing standard business document types is currently based on a textual specification only. Hence, variability within business document types is missing an explicit representation. Second, supporting the process of customizing standard business document types requires dedicated tool-support. In this paper, we formalize variability within the Core Components approach by adopting concepts from variability management and introduce a declarative approach based on variability models for validating the process of business document type customization. Furthermore, we present an evaluation of the approach proposed by means of a feasibility study. The approach provides a generic method for validating customized standard business document types.

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Astract: The most prominent business ontology for accounting information systems is the Resource-Event-Agent (REA) ontology developed by McCarthy, Geerts and others. REA is a widely accepted framework for the design of a conceptual model of the accountability infrastructure of enterprise information systems. Originally, REA targeted the resource flows within and between companies describing what is currently occurring and what has occurred in the past. This is known as the operational layer. Later it was extended by a planning layer and a policy layer capturing what should, could, or must be occurring sometime in the future. Today, REA may be considered as a powerful business ontology capturing all relevant data to generate the conceptual design of an Accounting Information System (AIS). However, we feel that it does not deliver an appropriate representation of the business model which can be understood not only by the IT expert, but also by the business expert. Thus, the use of REA in the design of AIS does not yet reach its full potential. We argue, that an easy-to-understand REA notation will accelerate, streamline, and reduce the costs of the AIS development process. Consequently, we have developed a domain specific modeling language for the REA concepts called the REA-DSL which aims at both (i) delivering an intuitive REA notation and (ii) retaining the full expressiveness of the REA concepts. The step we are conducting right now and covering in this paper is the incorporation of properties and primary keys into our REA-DSL and the final automatic generation of an Entity-Relationship-Diagram (ERD) for an AIS from the REA-DSL using our tool.

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Astract: The Resource-Event-Agent (REA) ontology is a powerful and well accepted approach towards the design of accounting information systems (AIS). However, the REA notation - that is currently based on class diagrams - is not very intuitive for business experts. Accordingly, we aim at a REA domain specific modeling language that facilitates the communication between business experts and IT professionals. In previous work we defined the REA-DSL operational layer reflecting actual business events which "have occurred" or "are occurring". In this paper we extend the REA-DSL by the planning layer capturing what future events "are scheduled" or "are planned" by commitments. Now, our REA-DSL covers all basic concepts to describe a full accounting infrastructure. The REA-DSL may serve as a solid basis for generating a conceptual AIS data model - which is subject to future work.

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Astract: Current optimistic model versioning systems, which are indispensable to coordinate the collaboration within teams, are able to detect several kinds of conflicts between two concurrently modified versions of one model. These systems support the detection of syntactical problems such as contradicting changes, violations of the underlying metamodel, and violations of OCL constraints. However, violations of the models' semantics remain unreported. In this paper, we suggest to use redundant information inherent in multi-view models to check if the semantics is violated during the merge process. In particular, we exploit the information encoded in state machine diagrams to validate evolving sequence diagrams by means of the model checker SPIN.

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Astract: With the emergence of model-driven engineering (MDE), software models are considered as central artifacts in the software engineering process, going beyond their traditional use as sketches. In MDE, models rather act as the single source of information for automatically generating executable software. This shift poses several new research challenges. One of these challenges constitutes model versioning, which targets at enabling efficient team-based development of models. This compelling challenge induced a very active research community, who yielded remarkable methods and techniques ranging from model differencing to merging of models. In this tutorial, we give an introduction to the foundations of model versioning, the underlying technologies for processing models and their evolution, as well as the state of the art in model versioning. Thereby, we aim at equipping students and researchers alike that are new to this domain with enough information for commencing to contribute to this challenging research area.