Numerical Invariants through Convex Relaxation and Max-Strategy   Iteration
  In this article we develop a max-strategy improvement algorithm for computing least fixpoints of operators on on the reals that are point-wise maxima of finitely many monotone and order-concave operators. Computing the uniquely determined least fixpoint of such operators is a problem that occurs frequently in the context of numerical program/systems verification/analysis. As an example for an application we discuss how our algorithm can be applied to compute numerical invariants of programs by abstract interpretation based on quadratic templates. 
Thomas Martin Gawlitza and Helmut Seidl
cs.PL