Two Efficient Representations for Set-Sharing Analysis in Logic Programs

Set-Sharing analysis, the classic Jacobs and Langen’s domain, has been widely used to infer several interesting properties of programs at compile-time such as occurs-check reduction, automatic parallelization, finite-tree analysis, etc. However, performing abstract unification over this domain implies the use of a closure operation which makes the number of sharing groups grow exponentially. Much attention has been given in the literature to mitigate this key inefficiency in this otherwise very useful domain. In this paper we present two novel alternative representations for the traditional set-sharing domain, tSH and tNSH, which compress efficiently the number of elements into fewer elements enabling more efficient abstract operations, including abstract unification, without any loss of accuracy. Our experimental evaluation supports that both representations can reduce dramatically the number of sharing groups showing they can be more practical solutions towards scalable set-sharing.