M. Kessentini, W. Werda, P. Langer, M. Wimmer: Search-based Model Merging, Vortrag: Genetic and Evolutionary Computation Conference (GECCO), Amsterdam, July 6-10, 2013, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), New York, NY, USA (2013), ISBN: 978-1-4503-1963-8, pages 1453 - 1460. Doi: 10.1145/2463372.2463553
In Model-Driven Engineering (MDE) adequate means for collaborative modeling among multiple team members is crucial for large projects. To this end, several approaches exist to identify the operations applied in parallel, to detect conflicts among them, as well as to construct a merged model by incorporating all non-conflicting operations. Conflicts often denote situations where the application of one operation disables the applicability of another operation. Whether one operation disables the other, however, often depends on their application order. To obtain a merged model that maximizes the combined effect of all parallel operations, we propose an automated approach for finding the optimal merging sequence that maximizes the number of successfully applied operations. Therefore, we adapted and used a heuristic search algorithm to explore the huge search space of all possible operation sequences. The validation results on merging various versions of real-world models confirm that our approach finds operation sequences that successfully incorporate a high number of conflicting operations, which are otherwise not reflected in the merge by current approaches.