  We present a method for solving the general mixed constrained convex
quadratic programming problem using an active set method on the dual problem.
The approach is similar to existing active set methods, but we present a new
way of solving the linear systems arising in the algorithm. There are two main
contributions; we present a new way of factorizing the linear systems, and show
how iterative refinement can be used to achieve good accuracy and to solve both
types of sub-problems that arise from semi-definite problems.
