Marius Lauder

A Survey of Triple Graph Grammar Tools

Model transformation plays a central role in Model-Driven Engineer- ing (MDE) and supporting bidirectionality 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 promising and useful in practice. TGGs have been researched for more than 15 years and multiple TGG tools are under active development. Although a common theoreti- cal foundation is shared, TGG tools differ considerably concerning expressiveness, applicability, efficiency, and the underlying translation algorithm. There currently exists neither a quantitative nor a qualitative overview and comparison of TGG tools and it is quite difficult to understand the different foci and corresponding strengths and weaknesses. Our contribution in this paper is to develop a set of criteria for com- paring TGG tools and to provide a concrete quantitative and qualitative comparison of three TGG tools.

Extended triple graph grammars with efficient and compatible graph translators

Model-based software development processes often force their users to translate instances of one modeling language into related instances of another modeling language and vice-versa. The underlying data structure of such languages usually are some sort of graphs. Triple graph grammars (TGGs) are a formally founded language for describing correspondence relationships between two graph languages in a declarative way. Bidirectional graph language translators can be derived from a TGG, which maps pairs of related graph instances onto each other. These translators must fulfill certain compatibility properties with respect to the correspondence relationships established by their TGG. These properties are guaranteed for the original TGG approach as published 15 years ago. However, its expressiveness is pushed to the limit in most real world scenarios. Furthermore, the original approach relies on a parsing algorithm with exponential runtime complexity. In this contribution, we study a more expressive class of TGGs with negative application conditions and show for the first time that derived translators with a polynomial runtime complexity still preserve the above mentioned compatibility properties. For this purpose, we introduce a new characterization of wellformed TGGs together with a new translation rule scheduling algorithm that considers dangling edges of input graphs.

Efficient model synchronization with precedence triple graph grammars

Triple Graph Grammars (TGGs) are a rule-based technique with a formal background for specifying bidirectional and incremental model transformation. In practical scenarios, unidirectional rules for incremental forward and backward transformation are automatically derived from the TGG rules in the specification, and the overall transformation process is governed by a control algorithm. Current incremental implementations either have a runtime complexity that depends on the size of related models and not on the number of changes and their affected elements, or do not pursue formalization to give reliable predictions regarding the expected results. In this paper, a novel incremental model synchronization algorithm for TGGs is introduced, which employs a static analysis of TGG specifications to efficiently determine the range of influence of model changes, while retaining all formal properties.

Surveying Rule Inheritance in Model-to-Model Transformation Languages

Model transformations play a significant role in Model-Driven Engineering. However, their reuse mechanisms have yet to receive much attention. In this paper, we propose a comparison framework for rule inheritance in model-to-model transformation languages, and provide an in-depth evaluation of prominent representatives of imperative, declarative and hybrid transformation languages. The framework provides criteria for comparison along orthogonal dimensions, covering static aspects, which indicate whether a set of inheriting transformation rules is well-formed at compile-time, and dynamic aspects, which describe how inheriting rules behave at run-time. The application of this framework to dedicated transformation languages shows that, while providing similar syntactical inheritance concepts, they exhibit different dynamic inheritance semantics and offer basic support for checking static inheritance semantics, only.

Bidirectional model transformation with precedence triple graph grammars

Triple Graph Grammars (TGGs) are a rule-based technique with a formal background for specifying bidirectional model transformation. In practical scenarios, the unidirectional rules needed for the forward and backward transformations are automatically derived from the TGG rules in the specification, and the overall transformation process is governed by a control algorithm. Current implementations either have a worst case exponential runtime complexity, based on the number of elements to be processed, or pose such strong restrictions on the class of supported TGGs that practical real-world applications become infeasible. This paper, therefore, introduces a new class of TGGs together with a control algorithm that drops a number of practice-relevant restrictions on TGG rules and still has a polynomial runtime complexity.

A comparison of rule inheritance in model-to-model transformation languages

Although model transformations presumably play a major role in Model-Driven Engineering, reuse mechanisms such as inheritance have received little attention so far. In this paper, we propose a comparison framework for rule inheritance in declarative model-to-model transformation languages, and provide an in-depth evaluation of three prominent representatives thereof, namely ATL, ETL (declarative subsets thereof), and TGGs. The framework provides criteria for comparison along orthogonal dimensions, covering static aspects, which indicate whether a set of inheriting transformation rules is well-formed at compile-time, and dynamic aspects, which describe how inheriting rules behave at run-time. The application of this framework to dedicated transformation languages shows that, while providing similar syntactical inheritance concepts, they exhibit different dynamic inheritance semantics and offer basic support for checking static inheritance semantics, only.

A Multidimensional Approach for Concurrent Model-Driven Automation Engineering

Mechatronic engineering is about integration of different engineering disciplines, mainly mechanical engineering, electrical engineering, and software engineering. Within the machine and plant engineering process, software engineering is part of automation engineering, which deals with configuration and programming of devices like programmable logic controllers (PLC), motion controllers, and human machine interface (HMI) ABstrAct

Support for Bidirectional Model-to-Text Transformations

In recent years, model-driven approaches and processes have established themselves as pragmatic and feasible solutions with tangible advantages. Transformations play a central role in any model-driven solution and, as interest in textual modelling grows, providing concepts and tools for supporting a high-level and declarative specification of bidirectional model-to-text transformations becomes a vital area of research. Our paper identifies important areas and scenarios for model-to-text transformations that are not or only partially supported by currently existing solutions. Based on the requirements of a real-world case study, we introduce a new concept that has been inspired by a successful bidirectional model-to-model transformation approach: Triple Graph Grammars.

A Solution to the Flowgraphs Case Study using Triple Graph Grammars and eMoflon

After 20 years of Triple Graph Grammars (TGGs) and numerous actively maintained implementations, there is now a need for challenging examples and success stories to show that TGGs can be used for real-world bidirectional model transformations. Our primary goal in recent years has been to increase the expressiveness of TGGs by providing a set of pragmatic features that allow a controlled fallback to programmed graph transformations and Java. Based on the Flowgraphs case study [7] of the Transformation Tool Contest (TTC 2013), we present (i) attribute constraints used to express complex bidirectional attribute manipulation, (ii) binding expressions for specifying arbitrary context relationships, and (iii) post-processing methods as a black box extension for TGG rules. In each case, we discuss the enabled trade-off between guaranteed formal properties and expressiveness. Our solution, implemented with eMoflon (www.emoflon.org) our metamodelling and model transformation tool, is available as a virtual machine hosted on Share [15].

Integrated Graph Transformations in Automation Systems

Abstract A crucial part of the automation system engineering consists of the reconciliation of engineering models. Hence, information from a source model is used to generate instances of a target model. For example, for each element in the plant and instrumentation diagram (P&ID) a corresponding representative is generated on the operator screen of the human machine interface (HMI). Most of those reconciliations follow simple rules. Nevertheless, due to the lack of tool support, most of this work is done manually. On the other hand, well studied transformation techniques exist, whichin the field of model driven development. The paper combines the concept of model transformation with the help of triple graph grammars (TGGs) and the approach of an integrated rule-based system to gain a formal background for the model transformation at runtime of an automation system. It will be demonstrated that TGGs are suitable to formulate the transformation rules in automation system engineering and that the rules can be generated by the system engineer without additional knowledge. Further, the paper proposes the adaption of the existing rule-based system ACPLT/RE to the concepts of bidirectional TGG rules to benefit from the possibilities of the TGG concept for model transformation at runtime. Finally the potential of model transformation at runtime with special focus on automation system engineering is demonstrated with the help of the flow analysis example.