Constraints ReReVisited

My wonderful and glorious, and long_windedly_titled Finite-Domain-Constraint-Satisfaction-Library, now solves Sudoku and sundry other Finite-Domain-Constraint-Satisfaction-Problems. Special thanks to Peter Norvig and the wonderful "AI: A Modern Approach" book. Also special thanks to the Cream constraint library (which was the original inspiration) and the Oz/Mozart language/library.
For those of you who haven't been following the progress of my library, it's written in Scala, and clocks in at just over 2000 loc; thats 1000 of library code plus 1000 lines of testing code -- which was essential because I refactored this thing so many times... if I hadn't had the tests I would have never gotten it working.
The future of the library is bright. There are more things to add and some improvements to make; however, its core parts seem to be feature complete. It uses the AC-3 algorithm to do the constraint propagation, and a simple backtracking search to solve the problems (if constraint propagation by itself doesn't do the trick). It maintains arc-consistency as it searches, and the next-variable-picker-algorithm, the constraint-propogation-algorithm, and the search-algorithm are all swappable. I'll be implementing more algorithms as time goes on, so the user may select the best strategy for solving their particular problem. Right now next-variables are selected using the Most-Restricted-Variable strategy, but for completeness I definitely need to add more options.
Oh, and special thanks to the Eular Project, which got me off on this constraints tangent in the first place.