456,609 research outputs found
Static Analysis of Functional Programs
In this paper, the static analysis of programs in the functional programming language Miranda* is described based on two graph models. A new control-flow graph model of Miranda definitions is presented, and a model with four classes of callgraphs. Standard software metrics are applicable to these models. A Miranda front end for Prometrix, ¿, a tool for the automated analysis of flowgraphs and callgraphs, has been developed. This front end produces the flowgraph and callgraph representations of Miranda programs. Some features of the metric analyser are illustrated with an example program. The tool provides a promising access to standard metrics on functional programs
Type Classes for Lightweight Substructural Types
Linear and substructural types are powerful tools, but adding them to
standard functional programming languages often means introducing extra
annotations and typing machinery. We propose a lightweight substructural type
system design that recasts the structural rules of weakening and contraction as
type classes; we demonstrate this design in a prototype language, Clamp.
Clamp supports polymorphic substructural types as well as an expressive
system of mutable references. At the same time, it adds little additional
overhead to a standard Damas-Hindley-Milner type system enriched with type
classes. We have established type safety for the core model and implemented a
type checker with type inference in Haskell.Comment: In Proceedings LINEARITY 2014, arXiv:1502.0441
Logic programming in the context of multiparadigm programming: the Oz experience
Oz is a multiparadigm language that supports logic programming as one of its
major paradigms. A multiparadigm language is designed to support different
programming paradigms (logic, functional, constraint, object-oriented,
sequential, concurrent, etc.) with equal ease. This article has two goals: to
give a tutorial of logic programming in Oz and to show how logic programming
fits naturally into the wider context of multiparadigm programming. Our
experience shows that there are two classes of problems, which we call
algorithmic and search problems, for which logic programming can help formulate
practical solutions. Algorithmic problems have known efficient algorithms.
Search problems do not have known efficient algorithms but can be solved with
search. The Oz support for logic programming targets these two problem classes
specifically, using the concepts needed for each. This is in contrast to the
Prolog approach, which targets both classes with one set of concepts, which
results in less than optimal support for each class. To explain the essential
difference between algorithmic and search programs, we define the Oz execution
model. This model subsumes both concurrent logic programming
(committed-choice-style) and search-based logic programming (Prolog-style).
Instead of Horn clause syntax, Oz has a simple, fully compositional,
higher-order syntax that accommodates the abilities of the language. We
conclude with lessons learned from this work, a brief history of Oz, and many
entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic
Programming
Software Extension and Integration with Type Classes
The abilities to extend a software module and to integrate a software module into an existing software system without changing existing source code are fundamental challenges in software engineering and programming-language design. We reconsider these challenges at the level of language expressiveness, by using the language concept of type classes, as it is available in the functional programming language Haskell. A detailed comparison with related work shows that type classes provide a powerful framework in which solutions to known software extension and integration problems can be provided. We also pinpoint several limitations of type classes in this context
Deformation quantization of Poisson manifolds, I
I prove that every finite-dimensional Poisson manifold X admits a canonical
deformation quantization. Informally, it means that the set of equivalence
classes of associative algebras close to the algebra of functions on X is in
one-to-one correspondence with the set of equivalence classes of Poisson
structures on X modulo diffeomorphisms. In fact, a more general statement is
proven ("Formality conjecture"), relating the Lie superalgebra of polyvector
fields on X and the Hochschild complex of the algebra of functions on X.
Coefficients in explicit formulas for the deformed product can be interpreted
as correlators in a topological open string theory, although I do not use
explicitly the language of functional integrals. One of corollaries is a
justification of the orbit method in the representation theory.Comment: plain TeX and epsf.tex, 46 pages, 24 figure
Weakly-supervised appraisal analysis
This article is concerned with the computational treatment of Appraisal, a Systemic Functional Linguistic theory of the types of language employed to communicate opinion in English. The theory considers aspects such as Attitude (how writers communicate their point of view), Engagement (how writers align themselves with respect to the opinions of others) and Graduation (how writers amplify or diminish their attitudes and engagements). To analyse text according to the theory we employ a weakly-supervised approach to text classification, which involves comparing the similarity of words with prototypical examples of classes. We evaluate the method's performance using a collection of book reviews annotated according to the Appraisal theory
The Glasgow Parallel Reduction Machine: Programming Shared-memory Many-core Systems using Parallel Task Composition
We present the Glasgow Parallel Reduction Machine (GPRM), a novel, flexible
framework for parallel task-composition based many-core programming. We allow
the programmer to structure programs into task code, written as C++ classes,
and communication code, written in a restricted subset of C++ with functional
semantics and parallel evaluation. In this paper we discuss the GPRM, the
virtual machine framework that enables the parallel task composition approach.
We focus the discussion on GPIR, the functional language used as the
intermediate representation of the bytecode running on the GPRM. Using examples
in this language we show the flexibility and power of our task composition
framework. We demonstrate the potential using an implementation of a merge sort
algorithm on a 64-core Tilera processor, as well as on a conventional Intel
quad-core processor and an AMD 48-core processor system. We also compare our
framework with OpenMP tasks in a parallel pointer chasing algorithm running on
the Tilera processor. Our results show that the GPRM programs outperform the
corresponding OpenMP codes on all test platforms, and can greatly facilitate
writing of parallel programs, in particular non-data parallel algorithms such
as reductions.Comment: In Proceedings PLACES 2013, arXiv:1312.221
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