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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