  In Software Product Line Engineering (SPLE) families of systems are designed,
rather than developing the individual systems independently. Combinatorial
Interaction Testing has proven to be effective for testing in the context of
SPLE, where a representative subset of products is chosen for testing in place
of the complete family. Such a subset of products can be determined by
computing a so called t-wise Covering Array (tCA), whose computation is
NP-complete. Recently, reduction rules that exploit basic feature model
analysis have been proposed that reduce the number of elements that need to be
considered during the computation of tCAs for Software Product Lines (SPLs). We
applied these rules to CASA, a simulated annealing algorithm for tCA generation
for SPLs. We evaluated the adapted version of CASA using 133 publicly available
feature models and could record on average a speedup of $61.8\%$ of median
execution time, while at the same time preserving the coverage of the generated
array.
