We evaluate the state of the art of solvers for hard argumentation problems---the enumeration of preferred and stable extensions---to envisage future trends based on evidence collected as part of an extensive empirical evaluation.
In the last international competition on computational models of argumentation a general impression suggesting that reduction-based systems (either SAT-based or ASP-based) are the most efficient.
Our investigation shows that we show that this impression is not true in full generality and suggests the areas where the relatively under-developed non reduction-based systems should focus more to improve their performance. Moreover, it also highlights that the state-of-the-art solvers are very complementary and can be successfully combined in portfolios: our best per-instance portfolio is 51% (resp. 53%) faster than the best single solver for enumerating preferred (resp. stable) extensions.