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Applications of model transformations include creating models, handling model co-evolution, model merging, and understanding model evolution. In the past, various (semi-)automatic approaches to derive model transformations from meta-models or from examples have been proposed. These approaches require time-consuming handcrafting or the recording of concrete examples, or they are unable to derive complex transformations. We propose a novel\n                    <jats:italic>unsupervised<\/jats:italic>\n                    approach, called\n                    <jats:sc>Ockham<\/jats:sc>\n                    , which is able to learn edit operations from model histories in model repositories.\n                    <jats:sc>Ockham<\/jats:sc>\n                    is based on the idea that meaningful domain-specific edit operations are the ones that\n                    <jats:italic>compress<\/jats:italic>\n                    the model differences. It employs frequent subgraph mining to discover frequent structures in model difference graphs. We evaluate our approach in two controlled experiments and one real-world case study of a large-scale industrial model-driven architecture project in the railway domain. We found that our approach is able to discover frequent edit operations that have actually been applied before. Furthermore,\n                    <jats:sc>Ockham<\/jats:sc>\n                    is able to extract edit operations that are meaningful\u2014in the sense of explaining model differences through the edit operations they comprise\u2014to practitioners in an industrial setting. We also discuss use cases (i.e., semantic lifting of model differences and change profiles) for the discovered edit operations in this industrial setting. We find that the edit operations discovered by\n                    <jats:sc>Ockham<\/jats:sc>\n                    can be used to better understand and simulate the evolution\u00a0of models.\n                  <\/jats:p>","DOI":"10.1007\/s10515-023-00381-1","type":"journal-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T07:02:50Z","timestamp":1682492570000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Mining domain-specific edit operations from model repositories with applications to semantic lifting of model differences and change profiling"],"prefix":"10.1007","volume":"30","author":[{"given":"Christof","family":"Tinnes","sequence":"first","affiliation":[]},{"given":"Timo","family":"Kehrer","sequence":"additional","affiliation":[]},{"given":"Mitchell","family":"Joblin","sequence":"additional","affiliation":[]},{"given":"Uwe","family":"Hohenstein","sequence":"additional","affiliation":[]},{"given":"Andreas","family":"Biesdorf","sequence":"additional","affiliation":[]},{"given":"Sven","family":"Apel","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,26]]},"reference":[{"issue":"4","key":"381_CR1","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1007\/s10270-016-0546-9","volume":"17","author":"V Acre\u0163oaie","year":"2018","unstructured":"Acre\u0163oaie, V., St\u00f6rrle, H., Str\u00fcber, D.: VMTL: a language for end-user model transformation. 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