In the analysis of logic programs, abstract domains for detecting sharing and 
linearity information are widely used. Devising abstract unification algorithms
for such domains has proved to be rather hard. At the moment, the available
algorithms are correct but not optimal; i.e., they cannot fully exploit the 
information conveyed by the abstract domains. In this paper, we define a new
(infinite) domain ShLin^ω which can be thought of as a general framework from
which other domains can be easily derived by abstraction. ShLinω makes the 
interaction between sharing and linearity explicit. We provide a constructive
characterization of the optimal abstract unification operator on ShLin^ω, and
we lift it to two well-known abstractions of ShLin^ω, namely, to the classical
Sharing×Lin abstract domain and to the more precise ShLin^2 abstract domain
by Andy King. In the case of single-binding substitutions, we obtain optimal 
abstract unification algorithms for such domains.