A common trait of complex systems is that they can be represented by means of a network of interacting parts. It is, in fact, the network (more than the parts) what largely conditions most higher-level properties, which are not reducible to the properties of the individual parts. Can the topological organisation of these webs provide some insight into their evolutionary origins? Both biological and artificial networks share some common architectural traits. They are often heterogeneous and sparse, and most exhibit the small-world property or the presence of modular or hierarchical patterns. These properties have often been attributed to the selection of functionally meaningful traits. However, the proper formulation of generative network models suggests that the origins of network complexity can be determined. Against the standard selection-optimisation argument, some networks reveal the inevitable generation of complex patterns resulting from reuse and can be modelled using duplication-rewiring rules. These give rise to the heterogeneous, scale-free and modular architectures observed in the real case studies. Tinkering is a universal mechanism that drives not only biological evolution but also the large-scale dynamics of some technological designs. Here we examine the evidence for tinkering in cellular, technological and ecological webs and its impact in shaping their architecture and deeply affecting their functional properties. Our analysis suggests to seriously reconsider the role played by selection forces or design principles as main drivers of network evolution.
