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Regression testing in very large software ecosystems is notoriously costly, requiring computational resources that even large corporations struggle to cope with. Very large ecosystems contain thousands of rapidly evolving, interconnected projects where client projects transitively depend on library projects. Regression test selection (RTS) reduces regression testing costs by rerunning only tests whose pass/fail behavior may flip after code changes. For single projects, researchers showed that class-level RTS is more effective than lower method-or statement-level RTS. Meanwhile, several very large ecosystems in industry, e.g., at Facebook, Google, and Microsoft, perform project-level RTS, rerunning tests in a changed library and in all its transitive clients. However, there was no previous study of the comparative benefits of class-level and project-level RTS in such ecosystems. We evaluate RTS opportunities in the …