  This paper addresses problems of second-order cone programming important in
optimization theory and applications. The main attention is paid to the
augmented Lagrangian method (ALM) for such problems considered in both exact
and inexact forms. Using generalized differential tools of second-order
variational analysis, we formulate the corresponding version of second-order
sufficiency and use it to establish, among other results, the uniform
second-order growth condition for the augmented Lagrangian. The latter allows
us to justify the solvability of subproblems in the ALM and to prove the linear
primal-dual convergence of this method.
