fully lazy lambda lifting

   John Hughes's optimisation of lambda lifting to give full
   laziness.  Maximal free expressions are shared to minimise
   the amount of recalculation.  Each inner sub-expression is
   replaced by a function of its maximal free expressions
   (expressions not containing any bound variable) applied to
   those expressions.  E.g.

   	f = \ x . (\ y . (+) (sqrt x) y)

   ((+) (sqrt x)) is a maximal free expression in
   (\ y . (+) (sqrt x) y) so this inner abstraction is replaced
   with

   	(\ g . \ y . g y) ((+) (sqrt x))

   Now, if a partial application of f is shared, the result of
   evaluating (sqrt x) will also be shared rather than
   re-evaluated on each application of f.  As Chin notes, the
   same benefit could be achieved without introducing the new
   higher-order function, g, if we just extracted out (sqrt x).

   This is similar to the code motion optimisation in
   procedural languages where constant expressions are moved
   outside a loop or procedure.

   (1994-12-01)