  The majority of existing probabilistic model checking case studies are based
on well understood theoretical models and distributions. However, real-life
probabilistic systems usually involve distribution parameters whose values are
obtained by empirical measurements and thus are subject to small perturbations.
In this paper, we consider perturbation analysis of reachability in the
parametric models of these systems (i.e., parametric Markov chains) equipped
with the norm of absolute distance. Our main contribution is a method to
compute the asymptotic bounds in the form of condition numbers for constrained
reachability probabilities against perturbations of the distribution parameters
of the system. The adequacy of the method is demonstrated through experiments
with the Zeroconf protocol and the hopping frog problem.
