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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.