Why dependent types matter

Abstract

Language designers have in recent years proposed a wealth of richer type systems for programming which seek to extend the range of statically enforced guarantees on data and code. Most such proposals have been evolutionary extensions of ML or Haskell, offering programmers a balanced compromise between expressive strength and existing well-understood technology. Typically they revolve around type- or kind-indexed types such as GADTs, supported by limited equality reasoning at the type-checking level, thus separating the dynamic behaviour of programs from the (simpler) static behaviour of indexing information occurring in their types.I want to argue in this talk for a more radical departure from such practice by examining full spectrum type dependency, lifting such restrictions on the data upon which types may depend. Conor McBride and I designed the language EPIGRAM for experiments in programming with inductive families of data (of which GADTs are a special case). Using it for illustration, I will explore some of the possibilities and challenges afforded by full spectrum type dependency at the static and dynamic level: