Given a regular expression R and a string Q, the regular expression
parsing problem is to determine if Q matches R and if so, determine how it
matches, e.g., by a mapping of the characters of Q to the characters in R.
Regular expression parsing makes finding matches of a regular expression even
more useful by allowing us to directly extract subpatterns of the match, e.g.,
for extracting IP-addresses from internet traffic analysis or extracting
subparts of genomes from genetic data bases. We present a new general
techniques for efficiently converting a large class of algorithms that
determine if a string Q matches regular expression R into algorithms that
can construct a corresponding mapping. As a consequence, we obtain the first
efficient linear space solutions for regular expression parsing
