  Coalgebraic bisimilarity minimization generalizes classical automaton
minimization to a large class of automata whose transition structure is
specified by a functor, subsuming strong, weighted, and probabilistic
bisimilarity. This offers the enticing possibility of turning bisimilarity
minimization into an off-the-shelf technology, without having to develop a new
algorithm for each new type of automaton. Unfortunately, there is no existing
algorithm that is fully general, efficient, and able to handle large systems.
  We present a generic algorithm that minimizes coalgebras over an arbitrary
functor in the category of sets as long as the action on morphisms is
sufficiently computable. The functor makes at most $\mathcal{O}(m \log n)$
calls to the functor-specific action, where $n$ is the number of states and $m$
is the number of transitions in the coalgebra.
  While more specialized algorithms can be asymptotically faster than our
algorithm (usually by a factor of $\mathcal{O}(\frac{m}{n})$), our algorithm is
especially well suited to efficient implementation, and our tool Boa often uses
much less time and memory on existing benchmarks, and can handle larger
automata, despite being more generic.
