Dependent ML

Source: Wikipedia, the free encyclopedia.

Dependent ML is an experimental

dependent types: types may be dependent on static indices of type Nat (natural numbers
). Dependent ML employs a constraint theorem prover to decide a strong equational theory over the index expressions.

DML's types are not dependent on runtime values - there is still a

becomes undecidable.

Dependent ML has been superseded by ATS and is no longer under active development.

References

  1. ^ Aspinall & Hofmann 2005. p. 75.

Further reading

  • Xi, Hongwei (March 2007). "Dependent ML: An Approach to Practical Programming with Dependent Types".
    S2CID 45996427
    .
  • David Aspinall and Martin Hofmann [de] (2005). "Dependent Types". In Pierce, Benjamin C. (ed.) Advanced Topics in Types and Programming Languages. MIT Press.

External links