VIATRA

Abstract: Model-driven tools frequently rely on advanced technologies to support model queries, view maintenance, design rule validation, model transformations or design space exploration. Some of these features are initiated explicitly by domain engineers batch execution while others are executed automatically when certain trigger events are detected live execution. Unfortunately, their integration into a complex industrial modeling environment is difficult due to hidden interference and unspecified interaction between different features. In this paper, we present a reactive, event-driven model transformation platform over EMF models, which captures tool features as model queries and transformations, and provides a systematic, well-founded integration between a variety of such tool features. Viatra 3 offers a family of internal DSLs i.e. dedicated libraries to specify advanced tool features built on top of existing languages like EMF-IncQuery and Xtend. Its main innovation is a source incremental execution scheme built on the reactive programming paradigm ssupported by an event-driven virtual machine.

Abstract: Tools to support modelling in system and software engineering are widespread, and have reached a degree of maturity where their use and availability are accepted. Tools to support model-driven development (MDD)--where models are manipulated and managed throughout the system/software engineering lifecycle--have, over the last 10 years, seen much research and development attention. Over the last 10 years, we have had significant experience in the design, development and deployment of MDD tools in practical settings. In this paper, we distill some of the important lessons we have learned in developing and deploying two MDD tools: Epsilon and VIATRA. In doing so, we aim to identify some of the key principles of developing successful MDD tools, as well as some hints of the pitfalls and risks.

Abstract: Model transformation (MT) of very large models (VLMs), with millions of elements, is a challenging cornerstone for applying Model-Driven Engineering (MDE) technology in industry. Recent research efforts that tackle this problem have been directed at distributing MT on the Cloud, either directly, by managing clusters explicitly, or indirectly, via external NoSQL data stores. In this paper, we draw attention back to improving efficiency of model transformations that use EMF natively and that run on non-distributed environments, showing that substantial performance gains can still be reaped on that ground. We present Yet Another Model Transformation Language (YAMTL), a new internal domain-specific language (DSL) of Xtend for defining declarative MT, and its execution engine. The part of the DSL for defining MT is similar to ATL in terms of expressiveness, including support for advanced modelling contructs, such as multiple rule inheritance and module composition. In addition, YAMTL provides support for specifying execution control strategies. We experimentally demonstrate that the presented transformation engine outperforms other representative MT engines by using the batch transformation component of the VIATRA CPS benchmark. The improvement is, at least, one order of magnitude over the up-to-now fastest solution in all of the assessed scenarios. The software artefacts accompanying this work have been approved by the artefact evaluation committee and are available at http://remodd.org/node/585.

Abstract: Viatra Solver [1] is a novel open source software tool to automatically synthesize consistent and diverse domain-specific graph models to be used as a test suite for the systematic testing of CPS modelling tools. Taking a metamodel, and a set of well-formedness constraints of a domain as input, the solver derives a diverse set of consistent graph models where each graph is compliant with the metamodel, satisfies consistency constraints, and structurally different from each other. The tool is integrated into the Eclipse IDE or it is executable from the command line. Video demonstration: https://youtu.be/fUopeDFIUKA