This increases the chance of hitting the correct letter when typing a word
that exists in the dictionary, rather than only correct it after the fact.
It is most effective after 2 or 3 letters of a word have been typed and gets
more accurate with more typed letters in the word.
If 2 adjacent letters have similar probabilities of occuring, then there is no
hit correction applied.
Native code was not returning the correct count for found matches. Fixed the
incorrect assumption that words usually get inserted in descending order of
frequency.
If the number of keys picked from proximity is too large, prune out
the subtree. Otherwise you get vastly unrelated suggestions.
Fix a bug introduced with the missing_chars checkin.
Changed the tree structure to have variable length nodes to save an average of 21% on the dictionary size.
Created a shortened English dictionary for Dream - 50K words.
Added a shortened Spanish dictionary for Dream - 32K words.
Original author: yamasani
Merged from: //branches/cupcake/...
Automated import of CL 143659