Sonia Cafieri, Jon Lee, et al.
Journal of Global Optimization
Set constraints are relations between sets of terms. They have been used extensively in various applications in program analysis and type inference. Recently, several algorithms for solving general systems of positive set constraints have appeared. In this paper we consider systems of mixed positive and negative constraints, which are considerably more expressive than positive constraints alone. We show that it is decidable whether a given such system has a solution. The proof involves a reduction to a number-theoretic decision problem that may be of independent interest. © 1995 Academic Press, Inc.
Sonia Cafieri, Jon Lee, et al.
Journal of Global Optimization
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ACM/IEEE SC 2006
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ICCAD 2009