Semantics and implementation of schema evolution in object-oriented databases
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Schema Evolution in Heterogeneous Database Architectures, A Schema Transformation Approach
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
Preserving mapping consistency under schema changes
The VLDB Journal — The International Journal on Very Large Data Bases
Semantic adaptation of schema mappings when schemas evolve
VLDB '05 Proceedings of the 31st international conference on Very large data bases
An online bibliography on schema evolution
ACM SIGMOD Record
Compiling mappings to bridge applications and databases
ACM Transactions on Database Systems (TODS)
Worry-free database upgrades: automated model-driven evolution of schemas and complex mappings
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Evolving the implementation of ISA relationships in EER schemas
CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
The ADO.NET entity framework: making the conceptual level real
ER'06 Proceedings of the 25th international conference on Conceptual Modeling
Report on the third workshop on hot topics in software upgrades (HotSWUp'11)
ACM SIGOPS Operating Systems Review
Incremental mapping compilation in an object-to-relational mapping system
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Online, asynchronous schema change in F1
Proceedings of the VLDB Endowment
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Schema evolution is an unavoidable consequence of the application development lifecycle. The two primary schemas in an application, the conceptual model and the persistent database model, must co-evolve or risk quality, stability, and maintainability issues. We study application-driven scenarios, where the conceptual model changes and the database and mapping must evolve in kind. We present a technique that, in most cases, allows those evolutions to progress automatically. We treat the mapping as data, and mine that data for patterns. Then, given an incremental change to the conceptual model, we can derive the proper store and mapping changes without user intervention. We characterize the significant subset of mappings for which automatic evolution is possible, and present our techniques for evolution propagation.