Selective CPS Transformation for Shift and Reset
This paper presents a selective CPS transformation for a program that
uses control operators, shift and reset, introduced by
Danvy and Filinski.
By selectively CPS-transforming a program, we can execute a program
with shift and reset in a standard functional language without
support for control operators.
We introduce a constraint-based type inference system that annotates
the parts that are captured by shift and thus require CPS
We show that the best annotation does not exist in general, and
present a constraint solving algorithm that is reasonably efficient.
The selective CPS transformation is defined over annotated terms
and its correctness is proven.
Finally, experimental results show that selective CPS transformation
does improve performance compared to the standard CPS