  Regular expressions (res), because of their succinctness and clear syntax,
are the common choice to represent regular languages. However, efficient
pattern matching or word recognition depend on the size of the equivalent
nondeterministic finite automata (NFA). We present the implementation of
several algorithms for constructing small epsilon-free NFAss from res within
the FAdo system, and a comparison of regular expression measures and NFA sizes
based on experimental results obtained from uniform random generated res. For
this analysis, nonredundant res and reduced res in star normal form were
considered.
