  The notion of a part of phase space containing desired (or allowed) states of
a dynamical system is important in a wide range of complex systems research. It
has been called the safe operating space, the viability kernel or the sunny
region. In this paper we define the notion of survivability: Given a random
initial condition, what is the likelihood that the transient behaviour of a
deterministic system does not leave a region of desirable states. We
demonstrate the utility of this novel stability measure by considering models
from climate science, neuronal networks and power grids. We also show that a
semi-analytic lower bound for the survivability of linear systems allows a
numerically very efficient survivability analysis in realistic models of power
grids. Our numerical and semi-analytic work underlines that the type of
stability measured by survivability is not captured by common asymptotic
stability measures.
