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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.

Lazy Set-Sharing Analysis