Generic random generators

Define sized random generators for almost any type.

    {-# LANGUAGE DeriveDataTypeable #-}
    import Data.Data
    import Test.QuickCheck
    import Data.Random.Generics

    data Term = Lambda Int Term | App Term Term | Var Int
      deriving (Show, Data)

    instance Arbitrary Term where
      arbitrary = sized (generator asGen)

    main = sample (arbitrary :: Gen Term)

• Objects of the same size (number of constructors) occur with the same probability (see Duchon et al., references below).
• Implements rejection sampling and pointing.
• Works with QuickCheck and MonadRandom.
• Can be extended or modified with user defined generators.

References

• The core theory of Boltzmann samplers is described in Boltzmann Samplers for the Random Generation of Combinatorial Structures, P. Duchon, P. Flajolet, G. Louchard, G. Schaeffer.

• The numerical evaluation of recursively defined generating functions is taken from Boltzmann Oracle for Combinatorial Systems, C. Pivoteau, B. Salvy, M. Soria.