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 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.

Model-driven engineering relies on effective collaboration between different teams which introduces complex model management challenges. DSE Merge aims to efficiently merge model versions created by various collaborators using search-based exploration of solution candidates that represent conflict-free merged models guided by domain-specific knowledge. In this paper, we report how we systematically evaluated the efficiency of the DSE Merge technique from the user point of view using a reactive experimental Software engineering approach. The empirical tests included the involvement of the intended end users (i.e. engineers), namely undergraduate students, which were expected to confirm the impact of design decisions. In particular, we asked users to merge the different versions of the same model using DSE Merge when compared to using Diff Merge. The experiment showed that to use DSE Merge participant required lower cognitive effort, and expressed their preference and satisfaction with it.

Large-scale model-driven engineering projects are carried out collaboratively. Enabling a high degree of concurrency is required to make the traditionally rigid development processes more agile. The increasing number of collaborators increases the probability of introducing conflicts which need to be resolved manually by the collaborators. In case of highly interdependent models, avoiding conflicts by the use of locks can save valuable time. However, traditional locking techniques such as fragment-based and object-based strategies may impose unnecessary restrictions on editing, which can decrease the efficiency of collaboration.In this paper, we propose a property-based locking approach that generalizes traditional locking techniques, and further allows more fine-grained locks in order to restrict modifications only when necessary. A lock is considered to be violated if a match appears or disappears for its associated graph pattern (formula), which captures the property of the model that the upcoming edit transaction can be freely executed. An initial evaluation has been carried out using a case study of the MONDO EU project.

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.

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.