Abstract : Besides the complexity in time or in number of messages, a common approach for analyzing distributed algorithms is to look at their assumptions on the underlying network. This paper focuses on the study of such assumptions in dynamic networks, where the connectivity is expected to change, predictably or not, during the execution. Our main contribution is a theoretical framework dedicated to such analysis. By combining several existing components (local computations, graph relabellings, and evolving graphs), this framework allows to express detailed properties on the network dynamics and to prove that a given property is necessary, or sufficient, for the success of an algorithm. Consequences of this work include (i)~the possibility to compare distributed algorithms on the basis of their topological requirements, (ii)~the elaboration of a formal classification of dynamic networks with respect to these properties, and (iii)~the possibility to check automatically whether a network trace belongs to one of the classes, and consequently to know which algorithm should run on it.