  We present Alias Refinement Types (ART), a new approach to the verification
of correctness properties of linked data structures. While there are many
techniques for checking that a heap-manipulating program adheres to its
specification, they often require that the programmer annotate the behavior of
each procedure, for example, in the form of loop invariants and pre- and
post-conditions. Predicate abstraction would be an attractive abstract domain
for performing invariant inference, existing techniques are not able to reason
about the heap with enough precision to verify functional properties of data
structure manipulating programs. In this paper, we propose a technique that
lifts predicate abstraction to the heap by factoring the analysis of data
structures into two orthogonal components: (1) Alias Types, which reason about
the physical shape of heap structures, and (2) Refinement Types, which use
simple predicates from an SMT decidable theory to capture the logical or
semantic properties of the structures. We prove ART sound by translating types
into separation logic assertions, thus translating typing derivations in ART
into separation logic proofs. We evaluate ART by implementing a tool that
performs type inference for an imperative language, and empirically show, using
a suite of data-structure benchmarks, that ART requires only 21% of the
annotations needed by other state-of-the-art verification techniques.
