3,261 research outputs found
Learning a Static Analyzer from Data
To be practically useful, modern static analyzers must precisely model the
effect of both, statements in the programming language as well as frameworks
used by the program under analysis. While important, manually addressing these
challenges is difficult for at least two reasons: (i) the effects on the
overall analysis can be non-trivial, and (ii) as the size and complexity of
modern libraries increase, so is the number of cases the analysis must handle.
In this paper we present a new, automated approach for creating static
analyzers: instead of manually providing the various inference rules of the
analyzer, the key idea is to learn these rules from a dataset of programs. Our
method consists of two ingredients: (i) a synthesis algorithm capable of
learning a candidate analyzer from a given dataset, and (ii) a counter-example
guided learning procedure which generates new programs beyond those in the
initial dataset, critical for discovering corner cases and ensuring the learned
analysis generalizes to unseen programs.
We implemented and instantiated our approach to the task of learning
JavaScript static analysis rules for a subset of points-to analysis and for
allocation sites analysis. These are challenging yet important problems that
have received significant research attention. We show that our approach is
effective: our system automatically discovered practical and useful inference
rules for many cases that are tricky to manually identify and are missed by
state-of-the-art, manually tuned analyzers
The Merging History of Massive Black Holes
We investigate a hierarchical structure formation scenario describing the
evolution of a Super Massive Black Holes (SMBHs) population. The seeds of the
local SMBHs are assumed to be 'pregalactic' black holes, remnants of the first
POPIII stars. As these pregalactic holes become incorporated through a series
of mergers into larger and larger halos, they sink to the center owing to
dynamical friction, accrete a fraction of the gas in the merger remnant to
become supermassive, form a binary system, and eventually coalesce. A simple
model in which the damage done to a stellar cusps by decaying BH pairs is
cumulative is able to reproduce the observed scaling relation between galaxy
luminosity and core size. An accretion model connecting quasar activity with
major mergers and the observed BH mass-velocity dispersion correlation
reproduces remarkably well the observed luminosity function of
optically-selected quasars in the redshift range 1<z<5. We finally asses the
potential observability of the gravitational wave background generated by the
cosmic evolution of SMBH binaries by the planned space-born interferometer
LISA.Comment: 4 pages, 2 figures, Contribute to "Multiwavelength Cosmology",
Mykonos, Greece, June 17-20, 200
Neutron scattering in a d_{x^2-y^2}-wave superconductor with strong impurity scattering and Coulomb correlations
We calculate the spin susceptibility at and below T_c for a d_{x^2-y^2}-wave
superconductor with resonant impurity scattering and Coulomb correlations. Both
the impurity scattering and the Coulomb correlations act to maintain peaks in
the spin susceptibility, as a function of momentum, at the Brillouin zone edge.
These peaks would otherwise be suppressed by the superconducting gap. The
predicted amount of suppression of the spin susceptibility in the
superconducting state compared to the normal state is in qualitative agreement
with results from recent magnetic neutron scattering experiments on
La_{1.86}Sr_{0.14}CuO_4 for momentum values at the zone edge and along the zone
diagonal. The predicted peak widths in the superconducting state, however, are
narrower than those in the normal state, a narrowing which has not been
observed experimentally.Comment: 24 pages (12 tarred-compressed-uuencoded Postscript figures), REVTeX
3.0 with epsf macros, UCSBTH-94-1
A Consistent Picture of Electronic Raman Scattering and Infrared Conductivity in the Cuprates
Calculations are presented for electronic Raman scattering and infrared
conductivity in a superconductor including the effects of
elastic scattering via anisotropic impurities and inelastic spin-fluctuation
scattering. A consistent description of experiments on optimally doped Bi-2212
is made possible by considering the effects of correlations on both inelastic
and elastic scattering.Comment: 4 pages Revtex, 5 embedded eps file
Inducing safer oblique trees without costs
Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the
distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification.
Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety.
This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming
Parallelization, Special Hardware and Post-Newtonian Dynamics in Direct N - Body Simulations
The formation and evolution of supermassive black hole (SMBH) binaries during and after galaxy mergers is an important ingredient for our understanding of galaxy formation and evolution in a cosmological context, e.g. for predictions of cosmic star formation histories or of SMBH demographics (to predict events that emit gravitational waves). If galaxies merge in the course of their evolution, there should be either many binary or even multiple black holes, or we have to find out what happens to black hole multiples in galactic nuclei, e.g. whether they come sufficiently close to merge resulting from emission of gravitational waves, or whether they eject each other in gravitational slingshot interactions
Effects of dilute Zn impurities on the uniform magnetic susceptibility of YBa2Cu3O{7-delta}
The effects of dilute Zn impurities on the uniform magnetic susceptibility
are calculated in the normal metallic state for a model of the spin
fluctuations of the layered cuprates. It is shown that scatterings from
extended impurity potentials can lead to a coupling of the q~(pi,pi) and the
q~0 components of the magnetic susceptibility chi(q). Within the presence of
antiferromagnetic correlations, this coupling can enhance the uniform
susceptibility. The implications of this result for the experimental data on Zn
substituted YBa2Cu3O{7-delta} are discussed.Comment: 4 pages, 4 figure
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