We study the experimental consequences of a recent theoretical result by Achlioptas et al. that shows that conventional models of random problems are trivially insoluble in the limit. We survey the literature to
identify experimental studies that lie within the scope of this result. We then estimate theoretically and measure experimentally
the size at which problems start to become trivially insoluble. Our results demonstrate that most (but not all) of these experimental
studies are luckily unaffected by this result. We also study an alternative model of random problems that does not suffer
from this asymptotic weakness. We show that, at a typical problem size used in experimental studies, this model looks similar
to conventional models. Finally, we generalize this model so that we can independently adjust the constraint tightness and
density
Supported by EPSRC awards GR/L/24014 and GR/K/65706. The authors wish to thank other members of the APES research group. We
are especially grateful to Ian Gent who derived the expected number of cliques in a random graph