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Refined Type Inference for ML \Lambda Manuel F ahndrich y and Alexander Aiken y

Summary: Refined Type Inference for ML \Lambda
Manuel F˜ ahndrich y and Alexander Aiken y
University of California, Berkeley z
1 Introduction
Inclusion constraints over set­expressions [1, 4] provide
a general formalism to express a large class of program
analyses. Over the past two years, we have experimented
with inclusion constraints to model dataflow in type­based
analyses. One of our research goals is to determine how to
structure and implement precise constraint­based analyses
such that they scale to large programs. Program analyses
with O(n 3 ) complexity bounds often exhibit their worst­
case complexity in practice and consequently do not scale
beyond programs of a few thousand lines. As a result,
coarser but faster analyses are usually used [2, 10].
Scaling behavior and precision are intimately con­
nected and in an ideal formalism, one can be traded
for the other. Unfortunately, inclusion constraints over
set­expressions do not provide enough control over this


Source: Aiken, Alex - Department of Computer Science, Stanford University


Collections: Computer Technologies and Information Sciences