A logic for networks

Abstract

Networks are pervasive in the real world. Nature, society, economy, and technology are supported by ostensibly different networks that in fact share an amazing number of interesting structural properties. Network thinking exploded in the last decade, boosted by the availability of large databases on the topology of various real networks, mainly the Web and biological networks, and converged to the new discipline of network analysis - the holistic analysis of complex systems through the study of the network that wires their components. Physicists mainly drove the investigation, studying the structure and function of networks using methods and tools of statistical mechanics. Here, we give an alternative perspective on network analysis, proposing a logic for specifying general properties of networks and a modular algorithm for checking these properties. The logic borrows from two intertwined computing fields: XML databases and model checking.

References in corpus (9)

• Emergence of scaling in random networks
• Statistical mechanics of complex networks
• The structure and function of complex networks
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• Lethality and centrality in protein networks
• Classes of behavior of small-world networks
• Mean-field theory for scale-free random networks
• Assessing the relevance of node features for network structure
• PageRank: Standing on the shoulders of giants