Parallelization of Graph Transformation Based on Incremental Pattern Matching

oai:journal.ub.tu-berlin.de:article/265Graph transformation based on incremental pattern matching explicitly stores all occurrences of patterns (left-hand side of rules) and updates this result cache upon model changes. This allows instantaneous pattern queries at the expense of costlier model manipulation and higher memory consumption. Up to now, this incremental approach has considered only sequential execution despite the inherently distributed structure of the underlying match caching mechanism. The paper explores various possibilities of parallelizing graph transformation to harness the power of modern multi-core, multi-processor computing environments: (i) incremental pattern matching enables the concurrent execution of model manipulation and pattern matching; moreover, (ii) pattern matching itself can be parallelized along caches

The Train Benchmark: cross-technology performance evaluation of continuous model queries

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 indus- trial 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 increas- ing 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 engi- neers by model transformations). The benchmark focuses on the performance of query evaluation, i.e. its execution time and memory consumption, with a particular empha- sis 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

Property-Based Methods for Collaborative Model Development

Industrial applications of mo del-driven engineering to de- velop large and complex systems resulted in an increasing demand for collab oration features. However, use cases such as mo del di�erencing and merging have turned out to b e a di�cult challenge, due to (i) the graph- like nature of mo dels, and (ii) the complexity of certain op erations (e.g. hierarchy refactoring) that are common to day. In the pap er, we present a novel search-based automated mo del merge approach where rule-based design space exploration is used to search the space of solution candi- dates that represent con�ict-free merged mo dels. Our metho d also allows engineers to easily incorp orate domain-sp eci�c knowledge into the merge pro cess to provide b etter solutions. The merge pro cess automatically cal- culates multiple merge candidates to b e presented to domain exp erts for �nal selection. Furthermore, we prop ose to adopt a generic synthetic b enchmark to carry out an initial scalability assessment for mo del merge with large mo dels and large change sets

Deriving Effective Permissions for Modeling Artifacts from Fine-grained Access Control Rules

In case of collaborative modeling, complex systems are de- veloped by different stakeholders. To guarantee security, access control policies need to be enforced during the col- laboration. Levels of required confidentiality and integrity may vary across modeling artifacts, and even features of a single model element. Fine-grained rule-based access control was proposed to meet the needs of flexible and concise access control. Rule- based policies are inherently subject to conflicts between the rules; these conflicts should be interpreted in a consis- tent but also predictable way that caters to the preferences of the policy engineer. We propose a deterministic, parameterizable resolution strategy between conflicting rules to calculate effective ac- cess permissions for each fact in the model. Our approach is illustrated using a case study of the MONDO EU projec