Your code seems very fast on Epinions.
 
I don't know which parameters you used to generate random graphs, but I 
assume that you have generated qui dense graphs. Such graphs have low 
diameter, and so are worse cases for iFUB and DiFUB.

You can of course open a ticket for DiFUB. 

Sincerely,

Le vendredi 27 mars 2020 08:12:32 UTC+1, Madhav Wagle a écrit :
>
> Hi,
> I have implemented the diFUB (directed iterative fringe bound) algorithm. 
> It is performing very well on all the real directed graphs which I tried:
>
> For Eg .
> Epinions social network graph 
> <https://snap.stanford.edu/data/soc-Epinions1.html> (32223 nodes in 
> largest SCC) 
> sage: %time m.diameter(algorithm="DiFUB")
> CPU times: user 304 ms, sys: 4.02 ms, total: 308 ms
> Wall time: 305 ms
> 16
>
> sage: %time m.diameter()
> CPU times: user 28min 55s, sys: 35.4 ms, total: 28min 55s
> Wall time: 28min 55s
> 16
>
>
> but* DIFUB isn't performing* well on random graphs( in the worst case may 
> take *twice* the number of BFS calls as the naive method)
>
> Even though my code is complete, I still plan on adding details to my 
> comments 
> Shall I open a ticket for this algorithm and open it for review?
>
>

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