Self-avoiding walks have also been studied in the context of network theory. In this context, it is customary to treat the SAW as a dynamical process, such that in every time-step a walker randomly hops between neighboring nodes of the network. The walk ends when the walker reaches a dead-end state, such that it can no longer progress to newly un-visited nodes. It was recently found that on Erdős–Rényi networks, the distribution of path lengths of such dynamically grown SAWs can be calculated analytically, and follows the Gompertz distribution. For arbitrary networks, the distribution of path lengths of the walk, the degree distribution of the non-visited network and the first-hitting-time distribution to a node can be obtained by solving a set of coupled recurrence equations.