  We study decompositions of the global NVALUE constraint. Our main
contribution is theoretical: we show that there are propagators for global
constraints like NVALUE which decomposition can simulate with the same time
complexity but with a much greater space complexity. This suggests that the
benefit of a global propagator may often not be in saving time but in saving
space. Our other theoretical contribution is to show for the first time that
range consistency can be enforced on NVALUE with the same worst-case time
complexity as bound consistency. Finally, the decompositions we study are
readily encoded as linear inequalities. We are therefore able to use them in
integer linear programs.
