3,000 research outputs found
Really Natural Linear Indexed Type Checking
Recent works have shown the power of linear indexed type systems for
enforcing complex program properties. These systems combine linear types with a
language of type-level indices, allowing more fine-grained analyses. Such
systems have been fruitfully applied in diverse domains, including implicit
complexity and differential privacy. A natural way to enhance the
expressiveness of this approach is by allowing the indices to depend on runtime
information, in the spirit of dependent types. This approach is used in DFuzz,
a language for differential privacy. The DFuzz type system relies on an index
language supporting real and natural number arithmetic over constants and
variables. Moreover, DFuzz uses a subtyping mechanism to make types more
flexible. By themselves, linearity, dependency, and subtyping each require
delicate handling when performing type checking or type inference; their
combination increases this challenge substantially, as the features can
interact in non-trivial ways. In this paper, we study the type-checking problem
for DFuzz. We show how we can reduce type checking for (a simple extension of)
DFuzz to constraint solving over a first-order theory of naturals and real
numbers which, although undecidable, can often be handled in practice by
standard numeric solvers
Type-Based Termination, Inflationary Fixed-Points, and Mixed Inductive-Coinductive Types
Type systems certify program properties in a compositional way. From a bigger
program one can abstract out a part and certify the properties of the resulting
abstract program by just using the type of the part that was abstracted away.
Termination and productivity are non-trivial yet desired program properties,
and several type systems have been put forward that guarantee termination,
compositionally. These type systems are intimately connected to the definition
of least and greatest fixed-points by ordinal iteration. While most type
systems use conventional iteration, we consider inflationary iteration in this
article. We demonstrate how this leads to a more principled type system, with
recursion based on well-founded induction. The type system has a prototypical
implementation, MiniAgda, and we show in particular how it certifies
productivity of corecursive and mixed recursive-corecursive functions.Comment: In Proceedings FICS 2012, arXiv:1202.317
Practical Subtyping for System F with Sized (Co-)Induction
We present a rich type system with subtyping for an extension of System F.
Our type constructors include sum and product types, universal and existential
quantifiers, inductive and coinductive types. The latter two size annotations
allowing the preservation of size invariants. For example it is possible to
derive the termination of the quicksort by showing that partitioning a list
does not increase its size. The system deals with complex programs involving
mixed induction and coinduction, or even mixed (co-)induction and polymorphism
(as for Scott-encoded datatypes). One of the key ideas is to completely
separate the induction on sizes from the notion of recursive programs. We use
the size change principle to check that the proof is well-founded, not that the
program terminates. Termination is obtained by a strong normalization proof.
Another key idea is the use symbolic witnesses to handle quantifiers of all
sorts. To demonstrate the practicality of our system, we provide an
implementation that accepts all the examples discussed in the paper and much
more
Trust, but Verify: Two-Phase Typing for Dynamic Languages
A key challenge when statically typing so-called dynamic languages is the
ubiquity of value-based overloading, where a given function can dynamically
reflect upon and behave according to the types of its arguments. Thus, to
establish basic types, the analysis must reason precisely about values, but in
the presence of higher-order functions and polymorphism, this reasoning itself
can require basic types. In this paper we address this chicken-and-egg problem
by introducing the framework of two-phased typing. The first "trust" phase
performs classical, i.e. flow-, path- and value-insensitive type checking to
assign basic types to various program expressions. When the check inevitably
runs into "errors" due to value-insensitivity, it wraps problematic expressions
with DEAD-casts, which explicate the trust obligations that must be discharged
by the second phase. The second phase uses refinement typing, a flow- and
path-sensitive analysis, that decorates the first phase's types with logical
predicates to track value relationships and thereby verify the casts and
establish other correctness properties for dynamically typed languages
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