  Relational databases play a central role in many information systems. Their
schema contains structural (e.g. tables and columns) and behavioral (e.g.
stored procedures or views) entity descriptions. Then, just like for ``normal''
software, changes in legislation, offered functionalities, or functional
contexts, impose to evolve databases and their schemas. But in some scenarios,
it is not so easy to deconstruct a wished evolution of the schema into a
precise sequence of operations. Changing a database schema may impose manually
dropping and recreating dependent entities, or manually searching for
dependencies in stored procedures. This is important because getting even the
order of application of the operators can be difficult and have profound
consequences. This meta-model allows us to compute the impact of planned
changes and recommend additional changes that will ensure that the RDBMS
constraints are always verified. The recommendations can then be compiled into
a valid SQL patch actually updating the database schema in an orderly way. We
replicated a past evolution showing that, without detailed knowledge of the
database, we could perform the same change in 75\% less time than the expert
database architect. We also exemplify the use of our approach on other planned
changes.
