  Graph parameters such as the clique number, the chromatic number, and the
independence number are central in many areas, ranging from computer networks
to linguistics to computational neuroscience to social networks. In particular,
the chromatic number of a graph (i.e., the smallest number of colors needed to
color all vertices such that no two adjacent vertices are of the same color)
can be applied in solving practical tasks as diverse as pattern matching,
scheduling jobs to machines, allocating registers in compiler optimization, and
even solving Sudoku puzzles. Typically, however, the underlying graphs are
subject to (often minor) changes. To make these applications of graph
parameters robust, it is important to know which graphs are stable for them in
the sense that adding or deleting single edges or vertices does not change
them. We initiate the study of stability of graphs for such parameters in terms
of their computational complexity. We show that, for various central graph
parameters, the problem of determining whether or not a given graph is stable
is complete for \Theta_2^p, a well-known complexity class in the second level
of the polynomial hierarchy, which is also known as "parallel access to NP."
