Avoiding Unnecessary Information Loss: Correct and Efficient Model Synchronization Based on Triple Graph Grammars

Model synchronization, i.e., the task of restoring consistency between two interrelated models after a model change, is a challenging task. Triple Graph Grammars (TGGs) specify model consistency by means of rules that describe how to create consistent pairs of models. These rules can be used to automatically derive further rules, which describe how to propagate changes from one model to the other or how to change one model in such a way that propagation is guaranteed to be possible. Restricting model synchronization to these derived rules, however, may lead to unnecessary deletion and recreation of model elements during change propagation. This is inefficient and may cause unnecessary information loss, i.e., when deleted elements contain information that is not represented in the second model, this information cannot be recovered easily. Short-cut rules have recently been developed to avoid unnecessary information loss by reusing existing model elements. In this paper, we show how to automatically derive (short-cut) repair rules from short-cut rules to propagate changes such that information loss is avoided and model synchronization is accelerated. The key ingredients of our rule-based model synchronization process are these repair rules and an incremental pattern matcher informing about suitable applications of them. We prove the termination and the correctness of this synchronization process and discuss its completeness. As a proof of concept, we have implemented this synchronization process in eMoflon, a state-of-the-art model transformation tool with inherent support of bidirectionality. Our evaluation shows that repair processes based on (short-cut) repair rules have considerably decreased information loss and improved performance compared to former model synchronization processes based on TGGs.Comment: 33 pages, 20 figures, 3 table

Enterprise Modelling using Algebraic Graph Transformation - Extended Version

An analysis of today's situation at Credit Suisse has shown severe problems, because it is based on current best practices and ad-hoc modelling techniques to handle important aspects of security, risk and compliance. Based on this analysis we propose in this paper a new enterprise model which allows the construction, integration, transformation and evaluation of different organizational models in a big decentralized organization like Credit Suisse. The main idea of the new model framework is to provide small decentralized models and intra-model evaluation techniques to handle services, processes and rules separately for the business and IT universe on one hand and for human-centric and machine-centric concepts on the other hand. Furthermore, the new framework provides inter-modelling techniques based on algebraic graph transformation to establish the connection between different kinds of models and to allow integration of the decentralized models. In order to check for security, risk and compliance in a suitable way, our models and techniques are based on different kinds of formal methods. In this paper, we show that algebraic graph transformation techniques are useful not only for intra-modelling - using graph grammars for visual languages and graph constraints for requirements - but also for inter-modelling - using triple graph grammars for model transformation and integration. Altogether, we present the overall idea of our new model framework and show how to solve specific problems concerning intra- and inter-modelling as first steps. This should give evidence that our framework can also handle important other requirements for enterprise modelling in a big decentralized organization like Credit Suisse

Automating the transformation-based analysis of visual languages

The final publication is available at Springer via http://dx.doi.org/10.1007/s00165-009-0114-yWe present a novel approach for the automatic generation of model-to-model transformations given a description of the operational semantics of the source language in the form of graph transformation rules. The approach is geared to the generation of transformations from Domain-Specific Visual Languages (DSVLs) into semantic domains with an explicit notion of transition, like for example Petri nets. The generated transformation is expressed in the form of operational triple graph grammar rules that transform the static information (initial model) and the dynamics (source rules and their execution control structure). We illustrate these techniques with a DSVL in the domain of production systems, for which we generate a transformation into Petri nets. We also tackle the description of timing aspects in graph transformation rules, and its analysis through their automatic translation into Time Petri netsWork sponsored by the Spanish Ministry of Science and Innovation, project METEORIC (TIN2008-02081/TIN) and by the Canadian Natural Sciences and Engineering Research Council (NSERC)

Propagation of Constraints along Model Transformations Based on Triple Graph Grammars: Long Version

Model transformations based on triple graph grammars (TGGs) have been applied in several practical case studies and they convince by their intuitive and descriptive way of specifying bidirectional model transformations. Moreover, fundamental properties have been extensively studied including syntactical correctness, completeness, termination and functional behaviour. But up to now, it is an open problem how domain specific properties that are valid for a source model can be preserved along model transformations such that the transformed properties are valid for the derived target model. In this paper, we analyse in the framework of TGGs how to propagate constraints from a source model to an integrated and target model such that, whenever the source model satisfies the source constraint also the integrated and target model satisfy the corresponding integrated and target constraint. In our main new results we show under which conditions this is possible. The case study shows how this result is successfully applied for the propagation of security constraints in enterprise modelling between business and IT models

Attribute Handling for Bidirectional Model Transformations: The Triple Graph Grammar Case

When describing bidirectional model transformations in a declarative (relational) way, the relation between structures in source and target models is specified. But not only structural correspondences between source and target models need to be described. Another important aspect is the specification of the relation between attribute values of elements in source and target models. However, most existing approaches either do not allow such a relational kind of specification for attributes or allow it only in a restricted way.We consider the challenge of bridging the gap between a flexible declarative attribute specification and its operationalization for the triple graph grammar (TGG) specification technique as an important representative for describing bidirectional model transformations in a relational way. First, we present a formal way to specify attributes in TGG rules in a purely declarative (relational) way. Then, we give an overview of characteristic barriers that bidirectional model transformation tool developers are confronted with when operationalizing relational attribute constraints for different TGG application scenarios. Moreover, we present pragmatic solutions to overcome the operationalization barriers for different TGG application scenarios in our own TGG implementation

Complex Attribute Manipulation in TGGs with Constraint-Based Programming Techniques

Model transformation plays a central role in Model-Driven Engineering (MDE) and providing bidirectional transformation languages is a current challenge with important applications.  Triple Graph Grammars (TGGs) are a formally founded,  bidirectional model transformation language shown by numerous case studies to be quite promising and successful.  Although TGGs provide adequate support for structural aspects via object  patterns in TGG rules, support for handling complex relationships between different attributes is still missing in current implementations.  For certain applications, such as bidirectional model-to-text transformations, being able to manipulate attributes via string manipulation or arithmetic operations in TGG rules is vital.  Our contribution in this paper is to formalize a TGG extension that provides a means for complex attribute manipulation in TGG rules.  Our extension is compatible with the existing TGG formalization, and retains the "single specification'' philosophy of TGGs

Conformance Analysis of Organizational Models in a new Enterprise Modeling Framework using Algebraic Graph Transformation - Extended Version

Organizational models play a key role in today's enterprise modeling. These models often show up as partial models produced by people with different conceptual understandings in a usually decentralized organization, where they are modeled in a distributed and non-synchronized fashion. For this reason, there is a first major need to organize partial organizational models within a suitable modeling framework, and there is a second major need to check their mutual conformance. This builds the basis to integrate the partial organizational models later on into one holistic model of the organization. Moreover, the partial models can be used for model checking certain security, risk, and compliance constraints. In order to satisfy the two major needs, this paper presents two mutually aligned contributions. The first one is a new enterprise modeling framework the EM-Cube. The second contribution is a new approach for checking conformance of models that are developed based on the suggested formal modeling technique associated with the proposed framework. In addition to that, we evaluate our potential solution against concrete requirements derived from a real-world scenario coming out of the finance industry

20 years of triple graph grammars: A roadmap for future research

Triple graph grammars (TGGs) provide a declarative, rule-based means of specifying binary consistency relationships between different types of graphs. Over the last 20 years, TGGs have been applied successfully in a range of application scenarios including: model generation, conformance testing, bidirectional model transformation, and incremental model synchronisation. In this paper, we review the progress made in TGG research up until now by exploring multiple research dimensions, including both the current frontiers of TGG research as well as important future challenges. Our aim is to provide a roadmap for the coming years of TGG research by stating clearly what we regard as adequately researched, and what we view as still unexplored potential

What Algebraic Graph Transformations Can Do For Model Transformations

Model transformations are key activities in model-driven development (MDD). A number of model transformation approaches have emerged for different purposes and with different backgrounds. This paper focusses on the use of algebraic graph transformation concepts to specify and verify model transformations in MDD

A Comparison of Incremental Triple Graph Grammar Tools

Triple Graph Grammars (TGGs) are a graph-based and visual technique for specifying bidirectional model transformation. TGGs can be used to transform models from scratch (in the batch mode), but the real potential of TGGs lies in propagating updates incrementally. Existing TGG tools differ considerably in their incremental mode concerning underlying algorithms, user-oriented aspects, incremental update capabilities, and formal properties. Indeed, the different foci, strengths, and weaknesses of current TGG tools in the incremental mode are difficult to discern, especially for non-developers. In this paper, we close this gap by (i) identifying a set of criteria for a qualitative comparison of TGG tools in the incremental mode, (ii) comparing three prominent incremental TGG tools with regard to these criteria, and (iii) conducting a quantitative comparison by means of runtime measurements