Superstabilization is a concept of fault-tolerance in distributed computing. Superstabilizing distributed algorithms combine the features of self-stabilizing algorithms and dynamic algorithms. A superstabilizing algorithm – just like any other self-stabilizing algorithm – can be started in an arbitrary state, and it will eventually converge to a legitimate state. Additionally, a superstabilizing algorithm will recover rapidly from a single change in the network topology (adding or removing one edge or node in the network).
Any self-stabilizing algorithm recovers from a change in the network topology – the system configuration after a topology change can be treated just like any other arbitrary starting configuration. However, in a self-stabilizing algorithm, the convergence after a single change in the network topology may be as slow as the convergence from an arbitrary starting state. In the study of superstabilizing algorithms, special attention is paid to the time it takes to recover from a single change in the network topology.