That is, the time bound of BFD improves upon that of Bellman–Ford in the in-between cases when negative edges exist, but are sparsely dispersed in the graph. A motivation of such input graphs comes naturally from classic, seemingly purely non-negative problem settings, where there are a few special edges in the network. For example, consider the navigation problem of finding a shortest route in a road map. Suppose that a driver chooses a few objects of interest, such as a beautiful view or a good restaurant, and assigns a route cost reduction to visiting each of them. Then, the updated road map can acquire a few negative edges.