Dynamic networks (DNs) recently reported in the literature are based on cross-linked supramolecular chains or on covalent chains with reversible bonds. As originally pointed out by Lehn, these networks should be regarded as dynamic materials exhibiting adaptive features due to continuous scrambling of their bonds and sequences. Results in the recent literature reveal that these networks undergo reversible long-range deformation resembling that of rubber networks. The present analysis of this process in terms of the theory of composite networks is based on the expectation that the scrambling process should allow rupture of bonds in the undeformed state and their reformation in the stretched state. Accordingly, a permanent set of the resting length of DNs should generally be expected and set materials should retain long-range elasticity relative to the set state. However, only a limited set is shown by DNs, implying that a strong memory of the initial network topology assists elastic recovery of the original dimensions. The analysis of reported experimental data further reveals that the stress-strain dependence of dynamic networks accurately follows the classical rubber elasticity theory. In this respect, DNs show better rubber behavior than typical covalent networks. Consistently with theoretical predictions, this surprising finding suggests that bond scrambling relieves local strain constraints on the fluctuations of networks junctions and favors the recovery of the initial network topology. Scrambling therefore allows compliance under stress and enhanced recovery when stress is released. Unprecedented applications of these advanced materials thus become foreseeable.