We study the sequences of numbers corresponding to lambda terms of given sizes, where the size is this of lambda terms with de Bruijn indices in a very natural model where all the operators have size 1.Expand

We advance Boltzmann samplers to term sizes interesting not only for correctness but also for scalability tests, by deriving Boltzmillers returning in a few seconds simply-typed random lambda terms of size 120 and above.Expand

In this paper, we propose an efficient polynomial-time, with respect to the number of tuned parameters, tuning algorithm based on convex optimisation techniques for Boltzmann samplers.Expand

We present an algorithm which, for given $n$, generates an unambiguous regular tree grammar defining the set of combinatory logic terms, over the set $\{S,K\}$ of primitive combinators, requiring exactly $n$ normal-order reduction steps to normalize.Expand

We combine the framework of Boltzmann samplers, a powerful technique of random combinatorial structure generation, with today’s Prolog systems offering a synergy between logic variables, unification with occurs check and efficient backtracking.Expand