  We present a new algorithm for determining the satisfiability of conjunctions
of non-linear polynomial constraints over the reals, which can be used as a
theory solver for satisfiability modulo theory (SMT) solving for non-linear
real arithmetic. The algorithm is a variant of Cylindrical Algebraic
Decomposition (CAD) adapted for satisfiability, where solution candidates
(sample points) are constructed incrementally, either until a satisfying sample
is found or sufficient samples have been sampled to conclude unsatisfiability.
The choice of samples is guided by the input constraints and previous
conflicts.
  The key idea behind our new approach is to start with a partial sample;
demonstrate that it cannot be extended to a full sample; and from the reasons
for that rule out a larger space around the partial sample, which build up
incrementally into a cylindrical algebraic covering of the space. There are
similarities with the incremental variant of CAD, the NLSAT method of Jovanovic
and de Moura, and the NuCAD algorithm of Brown; but we present worked examples
and experimental results on a preliminary implementation to demonstrate the
differences to these, and the benefits of the new approach.
