Semantic subtyping for objects and classes

In this paper we propose an integration of structural subtyping with boolean connectives and semantic subtyping to define a Java-like programming language that exploits the benefits of both techniques. Semantic subtyping is an approach for defining subtyping relation based on set-theoretic models, rather than syntactic rules. On the one hand, this approach involves some non trivial mathematical machinery in the background. On the other hand, final users of the language need not know this machinery and the resulting subtyping relation is very powerful and intuitive. While semantic subtyping is naturally linked to the structural one, we show how our framework can also accommodate the nominal subtyping. Several examples show the expressivity and the practical advantages of our proposal

Type systems for distributed programs: session communication

Distributed systems are everywhere around us and guaranteeing their correctness is of paramount importance. It is natural to expect that these systems interact and communicate among them to achieve a common task. In this work, we develop techniques based on types and type systems for the verification of correctness, consistency and safety properties related to communication in complex distributed systems. We study advanced safety properties related to communication, like deadlock or lock freedom and progress. We study session types in the pi-calculus describing distributed systems and communication-centric computation. Most importantly, we de- fine an encoding of the session pi-calculus into the standard typed pi-calculus in order to understand the expressive power of these concurrent calculi. We show how to derive in the session pi-calculus basic properties, like type safety or complex ones, like progress, by exploiting this encoding

Predicate Abstraction for Linked Data Structures

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

A Step-indexed Semantics of Imperative Objects

Step-indexed semantic interpretations of types were proposed as an alternative to purely syntactic proofs of type safety using subject reduction. The types are interpreted as sets of values indexed by the number of computation steps for which these values are guaranteed to behave like proper elements of the type. Building on work by Ahmed, Appel and others, we introduce a step-indexed semantics for the imperative object calculus of Abadi and Cardelli. Providing a semantic account of this calculus using more `traditional', domain-theoretic approaches has proved challenging due to the combination of dynamically allocated objects, higher-order store, and an expressive type system. Here we show that, using step-indexing, one can interpret a rich type discipline with object types, subtyping, recursive and bounded quantified types in the presence of state

Type Abstraction for Relaxed Noninterference

Information-flow security typing statically prevents confidential information to leak to public channels. The fundamental information flow property, known as noninterference, states that a public observer cannot learn anything from private data. As attractive as it is from a theoretical viewpoint, noninterference is impractical: real systems need to intentionally declassify some information, selectively. Among the different information flow approaches to declassification, a particularly expressive approach was proposed by Li and Zdancewic, enforcing a notion of relaxed noninterference by allowing programmers to specify declassification policies that capture the intended manner in which public information can be computed from private data. This paper shows how we can exploit the familiar notion of type abstraction to support expressive declassification policies in a simpler, yet more expressive manner. In particular, the type-based approach to declassification---which we develop in an object-oriented setting---addresses several issues and challenges with respect to prior work, including a simple notion of label ordering based on subtyping, support for recursive declassification policies, and a local, modular reasoning principle for relaxed noninterference. This work paves the way for integrating declassification policies in practical security-typed languages