Abstract (Jakob Rehof)
Program analyses based on partial order constraints
(e.g. subtype constraints, set constraints) suffer
from the problem that constraint sets extracted from large programs
become equally large. Constraint simplification aims at removing
redundant information from constraint sets in order to make them
more manageable in polymorphic inference systems, and the
simplification problem is now widely regarded as a key problem
for scalability of polymorphic subtype-based analysis. In this talk,
we give an overview of our recent results on algorithms and
complexity for constraint simplification and constraint satisfaction in
several subtyping systems, and we discuss applications to program
analysis based on such systems.
Some of the work discussed in the talk is joint
with Fritz Henglein, DIKU.
Last modified: April 20, 1998.
Kim Skak Larsen
(kslarsen@imada.sdu.dk)