Csaba Debreceni

Multi-objective optimization in rule-based design space exploration

Design space exploration (DSE) aims to find optimal design candidates of a domain with respect to different objectives where design candidates are constrained by complex structural and numerical restrictions. Rule-based DSE aims to find such candidates that are reachable from an initial model by applying a sequence of exploration rules. Solving a rule-based DSE problem is a difficult challenge due to the inherently dynamic nature of the problem. In the current paper, we propose to integrate multi-objective optimization techniques by using Non-dominated Sorting Genetic Algorithms (NSGA) to drive rule-based design space exploration. For this purpose, finite populations of the most promising design candidates are maintained wrt. different optimization criteria. In our context, individuals of a generation are defined as a sequence of rule applications leading from an initial model to a candidate model. Populations evolve by mutation and crossover operations which manipulate (change, extend or combine) rule execution sequences to yield new individuals. Our multi-objective optimization approach for rule-based DSE is domain independent and it is automated by tooling built on the Eclipse framework. The main added value is to seamlessly lift multi-objective optimization techniques to the exploration process preserving both domain independence and a high-level of abstraction. Design candidates will still be represented as models and the evolution of these models as rule execution sequences. Constraints are captured by model queries while objectives can be derived both from models or rule applications.

Query-driven incremental synchronization of view models

Views are key concepts of domain-specific modeling in order to provide specific focus of the designers by abstracting from unnecessary details of the underlying abstract model. Usually, these views are represented as models themselves (view models), computed from the source model. However, the efficient maintenance of views when the source model changes is challenging, as recalculation from scratch has to be avoided to achieve scalability. In the paper, we propose an approach to define view models in a highly automated way, based on declarative model queries. The views are automatically populated in accordance with the lifecycle of regular model elements - however, their existence is entirely bound to the underlying abstract model. This means that view models are automatically and incrementally maintained. Our contribution can also be interpreted as extending the concepts of derived features to derived objects, specified and maintained by incremental queries.

Automated Model Merge by Design Space Exploration

Industrial applications of model-driven engineering to develop large and complex systems resulted in an increasing demand for collaboration features. However, use cases such as model differencing and merging have turned out to be a difficult challenge, due to i the graph-like nature of models, and ii the complexity of certain operations e.g. hierarchy refactoring that are common today. In the paper, we present a novel search-based automated model merge approach where rule-based design space exploration is used to search the space of solution candidates that represent conflict-free merged models. Our method also allows engineers to easily incorporate domain-specific knowledge into the merge process to provide better solutions. The merge process automatically calculates multiple merge candidates to be presented to domain experts for final selection. Furthermore, we propose to adopt a generic synthetic benchmark to carry out an initial scalability assessment for model merge with large models and large change sets.

Query-based access control for secure collaborative modeling using bidirectional transformations*

Large-scale model-driven system engineering projects are carried out collaboratively. Engineering artifacts stored in model repositories are developed in either offline (checkout-modify-commit) or online (GoogleDoc-style) scenarios. Complex systems frequently integrate models and components developed by different teams, vendors and suppliers. Thus confidentiality and integrity of design artifacts need to be protected by access control policies. We propose a technique for secure collaborative modeling where (1) fine-grained access control for models can be defined by model queries, and (2) such access control policies are strictly enforced by bidirectional model transformations. Each collaborator obtains a filtered local copy of the model containing only those model elements which they are allowed to read; write access control policies are checked on the server upon submitting model changes. We illustrate the approach and carry out an initial scalability assessment using a case study of the MONDO EU project.

Incremental backward change propagation of view models by logic solvers

View models are key concepts of domain-specific modeling to provide task-specific focus (e.g., power or communication architecture of a system) to the designers by highlighting only the relevant aspects of the system. View models can be specified by unidirectional forward transformations (frequently captured by graph queries), and automatically maintained upon changes of the underlying source model using incremental transformation techniques. However, tracing back complex changes from one or more abstract view to the underlying source model is a challenging task, which, in general, requires the simultaneous analysis of transformation specifications and well-formedness constraints to create valid changes in the source model. In this paper we introduce a novel delta-based backward transformation technique using SAT solvers to synthetize valid and consistent change candidates in the source model, where only forward transformation rules are specified for the view models.

On the Opportunities of Scalable Modeling Technologies: An Experience Report on Wind Turbines Control Applications Development

Scalability in modeling has many facets, including the ability to build larger models and domain specific languages (DSLs) efficiently. With the aim of tackling some of the most prominent scalability challenges in Model-based Engineering (MBE), the MONDO EU project developed the theoretical foundations and open-source implementation of a platform for scalable modeling and model management. The platform includes facilities for building large DSLs, for splitting large models into sets of smaller interrelated fragments, and enables modelers to construct and refine complex models collaboratively, among other features.

Enforcing Fine-grained Access Control for Secure Collaborative Modelling using Bidirectional Transformations

Large-scale model-driven system engineering projects are carried out collaboratively. Engineering artefacts stored in model repositories are developed in either offline (checkout–modify–commit) or online (GoogleDoc-style) scenarios. Complex systems frequently integrate models and components developed by different teams, vendors and suppliers. Thus, confidentiality and integrity of design artefacts need to be protected in accordance with access control policies. We propose a secure collaborative modelling approach where fine-grained access control for models is strictly enforced by bidirectional model transformations. Collaborators obtain filtered local copies of the model containing only those model elements which they are allowed to read; write access control policies are checked on the server upon submitting model changes. We present a formal collaboration schema which provenly guarantees certain correctness constraints, and its adaption to online scenarios with on-the-fly change propagation and the integration into existing version control systems to support offline scenarios. The approach is illustrated, and its scalability is evaluated using a case study of the MONDO EU project.

The MONDO collaboration framework: secure collaborative modeling over existing version control systems

Model-based systems engineering of critical cyber-physical systems necessitates effective collaboration between different stakeholders while still providing secure protection of intellectual properties of all involved parties. While engineering artifacts are frequently stored in version control repositories, secure access control is limited to file-level strategies in most existing frameworks where models are split into multiple fragments with all-or-nothing permissions, which becomes a scalability and usability bottleneck in case of complex industrial models. In this paper, we introduce the MONDO Collaboration Framework, which provides rule-based fine-grained model-level secure access control, property-based locking and automated model merge integrated over existing version control systems such as Subversion (SVN) for storage and version control. Our framework simultaneously supports offline collaboration (asynchronous checkout-modify-commit) on top of off-the-shelf modeling tools and online scenarios (GoogleDocs-style short transactions) scenarios by offering a web-based modeling frontend. Screencast Demo: https://youtu.be/Ix3CgmsYIU0

Incquery server for teamwork cloud: scalable query evaluation over collaborative model repositories

Large-scale cyber-physical systems are co-engineered, especially in safety-critical industries, by various specialists within an organization and, increasingly, across organizations. The collaborative aspect of the process is facilitated by hosting engineering artifacts in model repositories. In order to validate the adherence to design rules, perform change impact analysis across projects, generate reports etc., engineers specify model queries and evaluate them using query engines, traditionally available in client modeling tools. In this paper we introduce IncQuery Server for Teamwork Cloud (IQS4TWC), a standalone middleware service that connects to Teamwork Cloud model repositories, and builds on Viatra Query to provide fast querying over their content. The new server-side solution provides advanced features including single-model ad-hoc queries as well as repository-wide change impact analysis (correlating projects across branches and revisions); access to version snapshots as well as queries on the latest state; and a range of performance fine-tuning options (such as elasticity and in-memory indexes) to achieve high scalability.

Correction to: Enforcing fine-grained access control for secure collaborative modelling using bidirectional transformations

The article “Enforcing fine-grained access control for secure collaborative modelling using bidirectional transformations”, written by Csaba Debreceni, Gábor Bergmann, István Ráth, Dániel Varró, was originally published electronically on the publisher’s internet portal (https://link.springer.com/journal/10270) on [11/21/2017 6:24:42 AM] without open access.