Intensional polymorphism, the ability to dispatch to different routines based on types at run
time, enables a variety of advanced implementation techniques for polymorphic languages,
including tag-free garbage collection, unboxed function arguments, polymorphic marshalling
and attened data structures. To date, languages that support intensional polymorphism
have required a type-passing (as opposed to type-erasure) interpretation where types are
constructed and passed to polymorphic functions at run time. Unfortunately, type-passing
suffers from a number of drawbacks: it requires duplication of run-time constructs at the
term and type levels, it prevents abstraction, and it severely complicates polymorphic closure
conversion. We present a type-theoretic framework that supports intensional polymorphism,
but avoids many of the disadvantages of type passing. In our approach, run-time type
information is represented by ordinary terms. This avoids the duplication problem, allows us
to recover abstraction, and avoids complications with closure conversion. In addition, our
type system provides another improvement in expressiveness; it allows unknown types to be
refined in place, thereby avoiding certain beta-expansions required by other frameworks.
Compile- and run-time approaches for the selection of efficient data structures for dynamic graph analysis