Additional Publication Information
State-of-the-art optimistic model versioning systems, which are critical to enable efficient team-based development of architectural models, are able to detect and help resolve basic conflicts arising during the merging of model versions. However, it is often overlooked that model merging may also cause severe syntactical and semantic inconsistencies. In this paper, we propose an approach to guide the resolution of inconsistencies detected in a merged architectural model. Our approach automatically finds and presents to the software architects all solutions for resolving all inconsistencies arisen during the merging of model versions. For inconsistencies that preexist in the model, our approach is able to suggest exactly which model elements should be changed to resolve them. Our approach is built upon a repair generation which can quickly derive resolutions for an inconsistency by examining its static and dynamic structure and forming concrete repair actions from changes in the versions to be merged. An empirical validation on a range of industrial models has demonstrated that our approach is scalable to both large models and large differences between model versions.