  Recently, two new parallel algorithms for on-the-fly model checking of LTL
properties were presented at the same conference: Automated Technology for
Verification and Analysis, 2011. Both approaches extend Swarmed NDFS, which
runs several sequential NDFS instances in parallel. While parallel random
search already speeds up detection of bugs, the workers must share some global
information in order to speed up full verification of correct models. The two
algorithms differ considerably in the global information shared between
workers, and in the way they synchronize.
  Here, we provide a thorough experimental comparison between the two
algorithms, by measuring the runtime of their implementations on a multi-core
machine. Both algorithms were implemented in the same framework of the model
checker LTSmin, using similar optimizations, and have been subjected to the
full BEEM model database.
  Because both algorithms have complementary advantages, we constructed an
algorithm that combines both ideas. This combination clearly has an improved
speedup. We also compare the results with the alternative parallel algorithm
for accepting cycle detection OWCTY-MAP. Finally, we study a simple statistical
model for input models that do contain accepting cycles. The goal is to
distinguish the speedup due to parallel random search from the speedup that can
be attributed to clever work sharing schemes.
