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Dependent ML

Experimental programming language From Wikipedia, the free encyclopedia

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Dependent ML (DML) is an experimental, multi-paradigm, general-purpose, high-level, functional programming language proposed by Hongwei Xi (Xi 2007) and Frank Pfenning. It is a dialect of the programming language ML. Dependent ML extends ML by a restricted notion of 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 phase distinction between compilation and execution of the program.[1] By restricting the generality of full dependent types type checking remains decidable, but type inference becomes undecidable.

Dependent ML has been superseded by ATS and is no longer under active development.

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