Model Management addresses the problem of managing an evolving collection of models, by capturing the relationships between models and providing well-defined operators to manipulate them. In this paper, we describe two such operators for manipulating hierarchical Statecharts: Match, for finding correspondences between models, and Merge, for combining models with respect to known correspondences between them. Our Match operator is heuristic, making use of both static and behavioural properties of the models to improve the accuracy of matching. Our Merge operator preserves the hierarchical structure of the input models, and handles differences in behaviour through parameterization. In this way, we automatically construct merges that preserve the semantics of Statecharts models. We illustrate and evaluate our work by applying our operators to AT&T telecommunication features. 1

Requirements elicitation involves the construction of large sets of conceptual models. An important step in the analysis of these models is checking their consistency. Existing research largely focuses on checking consistency of individual models and of relationships between pairs of models. However, such strategy does not guarantee global consistency. In this paper, we propose a consistency checking approach that addresses this problem for homogeneous models. Given a set of models and a set of relationships between them, our approach works by first constructing a merged model and then verifying this model against the consistency constraints of interest. By keeping proper traceability information, consistency diagnostics obtained over the merge are projected back to the original models and their relationships. The paper also presents a set of reusable expressions for defining consistency constraints in conceptual modelling. We demonstrate the use of the developed expressions in the specification of consistency rules for class and ER diagrams, and i ∗ goal models. 1

Abstract. Many different types of models are used in various scientific and engineering fields, reflecting the subject matter and the kinds of understanding that is sought in each field. Conceptual modeling techniques in software and information systems engineering have in the past focused mainly on describing and analyzing behaviours and structures that are implementable in software. As software systems become ever more complex and densely intertwined with the human social environment, we need models that reflect the social characteristics of complex systems. This chapter reviews the approach taken by the i* framework, highlights its application in several areas, and outlines some open research issues. 1 Why Social Modeling In many scientific and engineering disciplines, the principles, premises, and objectives of the field are embedded in and manifested through the models that are the daily conceptual tools of the profession. The models reflect the kinds of understanding that is sought by practitioners of the field. In software and information

Abstract. Schema merging is the process of integrating several schemas into a common, unified schema. There have been various approaches to schema merging, metamodel. Having a semantically rich representation of models and mappings is particularly important for merging as semantic information is required to resolve the conflicts encountered. Therefore, our approach to schema merging is based on the generic role-based metamodel GeRoMe and intensional mappings based on the real world states of model elements. We give a formal definition of the merged schema and present an algorithm implementing these formalizations. 1

We present TReMer+, a tool for consistency checking of distributed models (i.e., models developed by distributed teams). TReMer+ works by first constructing a merged model before checking consistency. This enables a flexible way of verifying global consistency properties that is not possible with other existing tools. 1.

This paper presents an approach to model features and function nets of automotive systems comprehensively. In order to bridge the gap between feature requirements and function nets, we describe an approach to describe both using a SysML-based notation. If requirements on the automotive system are changed by several developers responsible for different features, it is important for developers to have a good overview and understanding of the functions affected. We show that this can be comprehensively modeled using so called “feature views”. In order to validate these views against the complete function nets, consistency checks are provided. 1.

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A key problem in model-based development is merging a set of distributed models into a single seamless model. To merge a set of models, we need to know how they are related. In this position paper, we discuss the methodological aspects of describing the relationships between models. We argue that relationships between models should be treated as first-class artifacts in the merge problem and propose a general framework for model merging based on this argument. We illustrate the usefulness of our framework by instantiating it to the state-machine modelling domain and developing a flexible tool for merging state-machines.

Abstract: This paper presents an approach of modeling variability of automotive system architectures using function nets, views and feature diagrams. A function net models an architecture hierarchically and views are used to omit parts of such a model to focus on certain functionalities. In combination with feature diagrams that describe valid variants, the concepts of feature and variant views are introduced to model architectural variants. The relationship between views, variants and the underlying complete architectural model is discussed. Methodological aspects that come along with this approach are considered.

In large-scale model-based development, developers periodically need to combine collections of interrelated models. These models may capture different features of a system, describe alternative perspectives on a single feature, or express ways in which different features may alter one another’s structure or behaviour. We refer to the process of combining a set of interrelated models as model fusion. In this position paper, we provide an overview of our work on two key fusion activities, merging and composition, for behavioural models. The practical basis of our work comes from two case studies that we conducted using models from the telecommunications domain. We illustrate our work using these case studies, summarize the results our research has led to so far, and describe the future research challenges.