  Model transformations operate on models conforming to precisely defined
metamodels. Consequently, it often seems relatively easy to chain them: the
output of a transformation may be given as input to a second one if metamodels
match. However, this simple rule has some obvious limitations. For instance, a
transformation may only use a subset of a metamodel. Therefore, chaining
transformations appropriately requires more information. We present here an
approach that automatically discovers more detailed information about actual
chaining constraints by statically analyzing transformations. The objective is
to provide developers who decide to chain transformations with more data on
which to base their choices. This approach has been successfully applied to the
case of a library of endogenous transformations. They all have the same source
and target metamodel but have some hidden chaining constraints. In such a case,
the simple metamodel matching rule given above does not provide any useful
information.
