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. 14,18] 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. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org.

Large-scale model-driven system engineering projects are carried out collaboratively. Engineering artifacts stored in model repositories are developed in either offline (checkoutmodify-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.

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.

Abstract. 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 dierencing and merging have turned out to be a dicult challenge, due to (i) the graphlike 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 conict-free merged models. Our method also allows engineers to easily incorporate domain-specic knowledge into the merge process to provide better solutions. The merge process automatically calculates multiple merge candidates to be presented to domain experts for nal 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.

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 (GoogleDocstyle) 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.