Lazy Set-Sharing Analysis

Sharing analysis is widely deployed in the optimisation, specialisation and parallelisation of logic programs. Each abstract unification operation over the classic Jacobs and Langen domain involves the calculation of a closure operation that has exponential worst-case complexity. This paper explores a new tactic for improving performance: laziness. The idea is to compute partial sharing information eagerly and recover full sharing information lazily. The net result is an analysis that runs in a fraction of the time of the classic analysis and yet has comparable precision.