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Leiden Computational Network Science Lab

Network science research lab at Leiden University

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Using network analysis to understand the role of software components

September 15, 2018 network science

Software typically consists of a large number of components (in software design terms called ‘classes’). Master student Xavyr Rademaker worked on new ways of automatically determining the role of such a software component using a combination of machine learning and complex network analysis. This can be usefil, as it may allow poorly documented software projects to be understood more efficiently by software developers working on the project. Xavyr will present his findings at the Complex Networks conference in Cambridge in December 2018. The work is summarized in the following paper:

  • X. Rademaker, M.R.V. Chaudron and F.W. Takes, Automatic identification of component roles in software design networks, in Proceedings of the 7th International Conference on Complex Networks, Studies in Computational Intelligence 813: 145-157, Springer, 2018.

New CNS Lab website

Counting temporal motifs in multilayer networks

About the CNS Lab

The Leiden Computational Network Science Lab (CNS Lab) is a research group working on methods for knowledge discovery from real-world network data. We develop algorithms to unveil patterns in dynamic complex networks from a range of application domains, including (online) soclal networks, scientific collaboration networks and economic networks. The CNS Lab is lead by Frank Takes and hosted at LIACS, the Department of AI and Computer Science of Leiden University.

 

 

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