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- Open source implementation of the proposed algorithm: https://github.com/jwalteros/dOmega - Related question: [stackexchange](https://cstheory.stackexchange.com/questions/47947/linear-time-algorithm-to-test-if-clique-number-equals-degeneracy-bound)
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Nice algorithms! Is there any open source implementation? I'm wondering how Quick_Cut performs on large real-world graphs.
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Page with a link to the code: http://www.biotec.tu-dresden.de/research/schroeder/powergraphs/
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Hello, are you aware of any open source implementation of this algorithm ?
Some nice presentations on the topic: - https://www.irif.fr/~habib/Documents/cours_4-2015.pdf - http://igm.univ-mlv.fr/AlgoB/algoperm2012/04Paul.pdf - http://www.lirmm.fr/~paul/Talks/talk-06-algo-sem-McGill.pdf
>See table 3 from https://arxiv.org/abs/1811.10705 This is with $n=50$ nodes. It seems that the behavior is not the same for $n$ large: - I think that in a large ER, if the proba of connection $p$ is not too large or too small, then it is rare to find a group of nodes with the same neighbors outside the group (i.e. find a module). Can you prove that? - I don't think that the code https://github.com/antonovvk/decmod is buggy.
[Almost all finite graphs are asymmetric](https://en.wikipedia.org/wiki/Asymmetric_graph#Random_graphs). There is no pair of vertices with common neighborhood.
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