On-the-fly self-subsuming resolution

I have recently been trying a new method of shortening learnt clauses. There is a learnt clause minimisation paper by Sörensson and Biere, and I have recently been trying to do more. The trick I use, is that many literals can be removed from learnt clauses, if self-subsuming resolution (see my older post) is applied to them.

During self-subsuming resolution, under normal circumstances, the clauses used to remove literals with are the short clauses: binary and tertiary clauses. The trick I have discovered, is that since CryptoMiniSat keeps binary and tertiary clauses natively inside the watchlists (see my previous post), so doing self-subsuming resolution can be done extremely fast. We simply need to put the literals of the newly learnt clause into a fast-addressable memory, then go through the watchlists of every literal in the clause, and remove the literals that match.

The code used to achieve this is the following:

Essentially, we set the seen vector (which is initially all 0), to 1 where the original clause contained a literal. Then, we go through the watchlists, and check if any binary clause could strengthen the clause. If so, we unset the corresponding bit in seen. Finally, we clean the clause from the literals where seen is 0 (and then set all parts of seen back to 0).

The actual implementation only differs from the one above by also using tertiary clauses (which are also natively inside the watchlists) to do self-subsuming resolution. The results are very promising: CryptoMiniSat can now solve 2 more problems from the 2009 SAT Competition instances within the original time limit, and seems to scale better in the longer run, too. An example statistics output of CryptoMiniSat (from the UTI-20-10p1 problem):

which means that in 64% of the cases, on-the-fly self-subsuming resolution was useful, and on average, it removed 6.3 literals from each clause where it was useful.