I'm not too deep into CS theory so I'm not sure if this is an answer to your question but... SCC algorithms are useful when building routeable road networks from source data (like OSM) in order to filter out isolated sub-networks (like an airfield). We use dotnet but have something that looks possibly similar to what you wrote(?):

  StronglyConnectedVertices(Vertex source) => ReachableVertices(source).Intersect(ReverseReachableVertices(source))

The methods ReachableVertices and ReverseReachableVertices are effectively depth-first searches on the graph.

The challenge - in terms of performance - is actually not finding a single SCC but returning the full set of potentially thousands SCCs in large networks. I originally implemented an iterative (imperative) version of Gabow's "Path-Based" algorithm but it was too slow on continent-sized datasets. We did some experimentation with a parallel variant of Tarjan which didn't improve things much.

Eventually I settled for something "good enough" - randomly pick a vertex, calculate the SCC with the above code, return it if it's large enough (>1k vertices) otherwise filter it out, keep going until I've accounted for >90% of the graph. The remaining <10% gets filtered out. That's basically imperative (using a while loop) but could probably be functionalised.

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EDIT I've taken a better look at the linked paper and what I wrote is definitely not an answer to your question. But I'll leave it in case anyone's interested.