34,669 research outputs found
TyCO + Linear channels
We present an extension to the TyCO type system that is able to identify linear channels. We prove some technical results (e.g. type preservation w.r.t. reduction) and present an algorithm for inferring channels usage from process expressions. Our major contribution is the inference of linear information in a calculus with recursive equations rather than replicatio
Type Inference for Bimorphic Recursion
This paper proposes bimorphic recursion, which is restricted polymorphic
recursion such that every recursive call in the body of a function definition
has the same type. Bimorphic recursion allows us to assign two different types
to a recursively defined function: one is for its recursive calls and the other
is for its calls outside its definition. Bimorphic recursion in this paper can
be nested. This paper shows bimorphic recursion has principal types and
decidable type inference. Hence bimorphic recursion gives us flexible typing
for recursion with decidable type inference. This paper also shows that its
typability becomes undecidable because of nesting of recursions when one
removes the instantiation property from the bimorphic recursion.Comment: In Proceedings GandALF 2011, arXiv:1106.081
Aspect-Oriented Programming with Type Classes
We consider the problem of adding aspects to a strongly typed language which supports type classes. We show that type classes as supported by the Glasgow Haskell Compiler can model an AOP style of programming via a simple syntax-directed transformation scheme where AOP programming idioms are mapped to type classes. The drawback of this approach is that we cannot easily advise functions in programs which carry type annotations. We sketch a more principled approach which is free of such problems by combining ideas from intentional type analysis with advanced overloading resolution strategies. Our results show that type-directed static weaving is closely related to type class resolution -- the process of typing and translating type class programs
Polynomial Size Analysis of First-Order Shapely Functions
We present a size-aware type system for first-order shapely function
definitions. Here, a function definition is called shapely when the size of the
result is determined exactly by a polynomial in the sizes of the arguments.
Examples of shapely function definitions may be implementations of matrix
multiplication and the Cartesian product of two lists. The type system is
proved to be sound w.r.t. the operational semantics of the language. The type
checking problem is shown to be undecidable in general. We define a natural
syntactic restriction such that the type checking becomes decidable, even
though size polynomials are not necessarily linear or monotonic. Furthermore,
we have shown that the type-inference problem is at least semi-decidable (under
this restriction). We have implemented a procedure that combines run-time
testing and type-checking to automatically obtain size dependencies. It
terminates on total typable function definitions.Comment: 35 pages, 1 figur
Discrete chain graph models
The statistical literature discusses different types of Markov properties for
chain graphs that lead to four possible classes of chain graph Markov models.
The different models are rather well understood when the observations are
continuous and multivariate normal, and it is also known that one model class,
referred to as models of LWF (Lauritzen--Wermuth--Frydenberg) or block
concentration type, yields discrete models for categorical data that are
smooth. This paper considers the structural properties of the discrete models
based on the three alternative Markov properties. It is shown by example that
two of the alternative Markov properties can lead to non-smooth models. The
remaining model class, which can be viewed as a discrete version of
multivariate regressions, is proven to comprise only smooth models. The proof
employs a simple change of coordinates that also reveals that the model's
likelihood function is unimodal if the chain components of the graph are
complete sets.Comment: Published in at http://dx.doi.org/10.3150/08-BEJ172 the Bernoulli
(http://isi.cbs.nl/bernoulli/) by the International Statistical
Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm
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