8,959 research outputs found
Soft Contract Verification
Behavioral software contracts are a widely used mechanism for governing the
flow of values between components. However, run-time monitoring and enforcement
of contracts imposes significant overhead and delays discovery of faulty
components to run-time.
To overcome these issues, we present soft contract verification, which aims
to statically prove either complete or partial contract correctness of
components, written in an untyped, higher-order language with first-class
contracts. Our approach uses higher-order symbolic execution, leveraging
contracts as a source of symbolic values including unknown behavioral values,
and employs an updatable heap of contract invariants to reason about
flow-sensitive facts. We prove the symbolic execution soundly approximates the
dynamic semantics and that verified programs can't be blamed.
The approach is able to analyze first-class contracts, recursive data
structures, unknown functions, and control-flow-sensitive refinements of
values, which are all idiomatic in dynamic languages. It makes effective use of
an off-the-shelf solver to decide problems without heavy encodings. The
approach is competitive with a wide range of existing tools---including type
systems, flow analyzers, and model checkers---on their own benchmarks.Comment: ICFP '14, September 1-6, 2014, Gothenburg, Swede
Information, Coordination, and the Industrialization of Countries
The industrialization process of a country is often plagued by a failure to coordinate investment decisions. Using the Global Games approach we can solve this coordination problem and eliminate the problem of multiple equilibria. We show how appropriate information provision enhances efficiency. We discuss extensions of the model and argue that subsidies may be a property of a signalling equilibrium to overcome credibility problems in information provision. In addition we point out possible problems with overreaction to public information. Furthermore, we suggest a new focus for development policy
Real time clustering of time series using triangular potentials
Motivated by the problem of computing investment portfolio weightings we
investigate various methods of clustering as alternatives to traditional
mean-variance approaches. Such methods can have significant benefits from a
practical point of view since they remove the need to invert a sample
covariance matrix, which can suffer from estimation error and will almost
certainly be non-stationary. The general idea is to find groups of assets which
share similar return characteristics over time and treat each group as a single
composite asset. We then apply inverse volatility weightings to these new
composite assets. In the course of our investigation we devise a method of
clustering based on triangular potentials and we present associated theoretical
results as well as various examples based on synthetic data.Comment: AIFU1
Analytic cell decomposition and analytic motivic integration
The main results of this paper are a Cell Decomposition Theorem for Henselian
valued fields with analytic structure in an analytic Denef-Pas language, and
its application to analytic motivic integrals and analytic integrals over
\FF_q((t)) of big enough characteristic. To accomplish this, we introduce a
general framework for Henselian valued fields with analytic structure, and
we investigate the structure of analytic functions in one variable, defined on
annuli over . We also prove that, after parameterization, definable analytic
functions are given by terms. The results in this paper pave the way for a
theory of \emph{analytic} motivic integration and \emph{analytic} motivic
constructible functions in the line of R. Cluckers and F. Loeser
[\emph{Fonctions constructible et int\'egration motivic I}, Comptes rendus de
l'Acad\'emie des Sciences, {\bf 339} (2004) 411 - 416]
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