Towards Practical Typechecking for Macro Tree Transducers

Computer Science – Programming Languages

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

Macro tree transducers (mtt) are an important model that both covers many useful XML transformations and allows decidable exact typechecking. This paper reports our first step toward an implementation of mtt typechecker that has a practical efficiency. Our approach is to represent an input type obtained from a backward inference as an alternating tree automaton, in a style similar to Tozawa's XSLT0 typechecking. In this approach, typechecking reduces to checking emptiness of an alternating tree automaton. We propose several optimizations (Cartesian factorization, state partitioning) on the backward inference process in order to produce much smaller alternating tree automata than the naive algorithm, and we present our efficient algorithm for checking emptiness of alternating tree automata, where we exploit the explicit representation of alternation for local optimizations. Our preliminary experiments confirm that our algorithm has a practical performance that can typecheck simple transformations with respect to the full XHTML in a reasonable time.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Towards Practical Typechecking for Macro Tree Transducers does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Towards Practical Typechecking for Macro Tree Transducers, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Towards Practical Typechecking for Macro Tree Transducers will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-568238

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.