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In model-driven development of safety-critical systems (like automotive, avionics or railways), well-formedness of models is repeatedly validated in order to detect design flaws as early as possible. In many industrial tools, validation rules are still often implemented by a large amount of imperative model traversal code which makes those rule implementations complicated and hard to maintain. Additionally, as models are rapidly increasing in size and complexity, efficient execution of validation rules is challenging for the currently available tools. Checking well-formedness constraints can be captured by declarative queries over graph models, while model update operations can be specified as model transformations. This paper presents a benchmark for systematically assessing the scalability of validating and revalidating well-formedness constraints over large graph models. The benchmark defines well-formedness validation scenarios in the railway domain: a metamodel, an instance model generator and a set of well-formedness constraints captured by queries, fault injection and repair operations (imitating the work of systems engineers by model transformations). The benchmark focuses on the performance of query evaluation, i.e. its execution time and memory consumption, with a particular emphasis on reevaluation. We demonstrate that the benchmark can be adopted to various technologies and query engines, including modeling tools; relational, graph and semantic databases. The Train Benchmark is available as an open-source project with continuous builds from https://github.com/FTSRG/trainbenchmark.

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The current release of VIATRA provides opensource tool support for an event-driven, reactive model transformation engine built on top of highly scalable incremental graph queries for models with millions of elements and advanced features such as rule-based design space exploration complex event processing or model obfuscation. However, the history of the VIATRA model transformation framework dates back to over 16 years. Starting as an early academic research prototype as part of the M.Sc project of the the first author it first evolved into a Prolog-based engine followed by a family of open-source projects which by now matured into a component integrated into various industrial and open-source tools and deployed over multiple technologies. This invited paper briefly overviews the evolution of the VIATRA/IncQuery family by highlighting key features and illustrating main transformation concepts along an open case study influenced by an industrial project. Software tools in systems engineeringModel-driven engineering (MDE) plays an important role in the design of critical embedded and cyber-physical systems in various application domains such as automotive, avionics or telecommunication. MDE tools aim to simultaneously improve quality and decrease costs by early validation by highlighting conceptual design flaws well before traditional testing phases in accordance with the correct-by-construction principle. Furthermore, they improve productivity of engineers by automatically synthesizing different design artifacts (source code, configuration tables, test cases, fault trees, etc.) necessitated by certification standards (like DO-178C [117], DO-330 [116] or ISO 26262[78]).Certain shares in the software tool market of systems engineering are dominated by very few industrial tools (e.g., MATLAB Simulink, Dymola, DOORS, MagicDraw) each of which typically provides advanced support for certain development stages (requirements engineering, simulation, allocation, test generation, etc). To protect their intellectual property rights, these tools are of closed nature, which implies huge tool integration costs for system integrators (such as airframers or car manufacturers). On the other hand, recent initiatives (such as PolarSys, OpenModelica) have started to promote open language standards and the systematic use of open-source software components in tools for critical systems to reduce licensing costs and risks of vendor lock-in.Certification standards of critical cyber-physical systems require that software tools used for developing such critical system are validated with the same scrutiny as the system under design by software tool qualification [87,116], especially, when no further human checking is carried out on the outputs of such tools. Software tool qualification distinguishes between design tools which, by definition, may 123

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International audienceAs Model-Driven Engineering (MDE) is increasingly applied to larger and more complex systems, the current generation of modelling and model management technologies are being pushed to their limits in terms of capacity and eciency. Additional research and development is imperative in order to enable MDE to remain relevant with industrial practice and to continue delivering its widely recognised productivity , quality, and maintainability benefits. Achieving scalabil-ity in modelling and MDE involves being able to construct large models and domain-specific languages in a systematic manner, enabling teams of modellers to construct and refine large models in a collaborative manner, advancing the state of the art in model querying and transformations tools so that they can cope with large models (of the scale of millions of model elements), and providing an infrastructure for ecient storage, indexing and retrieval of large models. This paper attempts to provide a research roadmap for these aspects of scalability in MDE and outline directions for work in this emerging research area

Incremental pattern matching is a key challenge for many tool integration, model synchronization and (discrete-event) model simulation tasks. An incremental pattern matching engine explicitly stores existing matches, while these matches are maintained incrementally with respect to the changes of the underlying model. In the current paper, we present an adaptation of RETE networks [6] in order to provide incremental support for the transformation language of the VIATRA2 framework. We evaluate the performance of the incremental engine on a benchmark problem assessing the speedup of incremental processing in the case of as-long-as-possible type of rule applications.

Abstract-Model-driven analysis aims at detecting design flaws early in high-level design models by automatically deriving mathematical models. These analysis models are subsequently investigated by formal verification and validation (V&V) tools, which may retrieve traces violating a certain requirement. Back-annotation aims at mapping back the results of V&V tools to the design model in order to highlight the real source of the fault, to ease making necessary amendments.Here we propose a technique for the back-annotation of simulation traces based on change-driven model transformations. Simulation traces of analysis models will be persisted as a change model with high-level change commands representing macro steps of a trace. This trace is back-annotated to the design model using change-driven transformation rules, which bridge the conceptual differences between macro steps in the analysis and design traces. Our concepts will be demonstrated on the back-annotation problem for analyzing BPEL processes using a Petri net simulator.