Dear all,
An update on the GLR extension for Happy:
Several improvements in speed and functionality have been made since the
August version. The full release as part of Happy will occur soon, but a
sneak preview plus useful information can be found on page:
http://www.dur.ac.uk/p.c.callaghan/happy-glr
This will be a permanent page for distributing information, tips,
interesting examples, experimental releases etc.
The currently contains a current linux build (as .tgz, compiled on
Fedora), and a current windows build (as a zip file)
These packages contain full documentation on the GLR extension and some
relevant examples. Executing "make in-place" in the distribution's root
directory will fix up paths to allow the examples to be compiled. (This
works on the linux version or Windows with Cygwin etc - there's no support
for other combinations yet.)
>From the earlier message:
> GLR parsing extends LR parsing to ambiguous grammars, producing a
> directed, acyclic and-or graph ("a packed forest") to compactly
> represent the multiple possible parses. There are many possible
> applications, not least natural language, bioinformatics, sequence
> alignment, code generation...
>
> It comprises an additional back-end and drivers for Happy. The code
> generated is 100% Haskell-98 or can be optimised for GHC. The latter is
> sufficiently efficient to parse a gene sequence of length 1200 to a graph
> of some 23400 nodes in about 4 seconds. It has two modes of recording
> semantic information, either calculating the list of all possible
> results or allowing detailed labelling of the forest's nodes. It is
> based on undergraduate work by Ben Medlock (Durham), with some use of
> ideas from Peter Ljungloef (Chalmers), and subsequently extended /
> improved by myself. Its unique feature is the production of an explicit
> graph, which is essential for applications involving heavy ambiguity -
> where simply processing lists of alternatives leads to explosion of
> possibilities.
Since August, the following change have been made:
* much faster
* better representation (ideal for local ambiguity packing)
* supports monadic semantic values in tree-decode mode (ie, Happy's
%monad directive and {%...} facility.)
* can parse grammars with hidden left recursion.
* full documentation added
* wider set of examples
Enjoy!
Paul Callaghan
--------------------------------------------------------------------------------
Dr Paul Callaghan (Lecturer) Email: [EMAIL PROTECTED]
Computer Assisted Reasoning Group, Department of Computer Science, Durham
http://www.dur.ac.uk/CARG
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