178 research outputs found
A template-based approach for the generation of abstractable and reducible models of featured networks
We investigate the relationship between symmetry reduction and inductive reasoning when applied to model checking networks of featured components. Popular reduction techniques for combatting state space explosion in model checking, like abstraction and symmetry reduction, can only be applied effectively when the natural symmetry of a system is not destroyed during specification. We introduce a property which ensures this is preserved, open symmetry. We describe a template-based approach for the construction of open symmetric Promela specifications of featured systems. For certain systems (safely featured parameterised systems) our generated specifications are suitable for conversion to abstract specifications representing any size of network. This enables feature interaction analysis to be carried out, via model checking and induction, for systems of any number of featured components. In addition, we show how, for any balanced network of components, by using a graphical representation of the features and the process communication structure, a group of permutations of the underlying state space of the generated specification can be determined easily. Due to the open symmetry of our Promela specifications, this group of permutations can be used directly for symmetry reduced model checking.
The main contributions of this paper are an automatic method for developing open symmetric specifications which can be used for generic feature interaction analysis, and the novel application of symmetry detection and reduction in the context of model checking featured networks.
We apply our techniques to a well known example of a featured network – an email system
Automatic symmetry detection for model checking using computational group theory
We present an automatic technique for the detection of structural symmetry in a model directly from its Promela specification. Our approach involves finding the <i>static</i> <i>channel</i> <i>diagram</i> of the model, a graphical representation of channel-based system communication; computing the group of symmetries of this diagram; and computing the largest possible subgroup of these symmetries which induce automorphisms of the underlying model. We describe a tool, SymmExtractor, which, for a given model and <i>LTL</i> property, uses our approach to find a group of symmetries of the model which preserve the property. This group can then be used for symmetry reduction during model checking using existing quotient-based methods. Unlike previous approaches, our method can detect arbitrary structural symmetries arising from the communication structure of the model
State space c-reductions for concurrent systems in rewriting logic
We present c-reductions, a state space reduction technique.
The rough idea is to exploit some equivalence relation on states (possibly capturing system regularities) that preserves behavioral properties, and explore the induced quotient system. This is done by means of a canonizer
function, which maps each state into a (non necessarily unique) canonical representative of its equivalence class. The approach exploits the expressiveness of rewriting logic and its realization in Maude to enjoy several advantages over similar approaches: exibility and simplicity in
the definition of the reductions (supporting not only traditional symmetry reductions, but also name reuse and name abstraction); reasoning support for checking and proving correctness of the reductions; and automatization
of the reduction infrastructure via Maude's meta-programming
features. The approach has been validated over a set of representative case studies, exhibiting comparable results with respect to other tools
Engineering a static verification tool for GPU kernels
We report on practical experiences over the last 2.5 years related to the engineering of GPUVerify, a static verification tool for OpenCL and CUDA GPU kernels, plotting the progress of GPUVerify from a prototype to a fully functional and relatively efficient analysis tool. Our hope is that this experience report will serve the verification community by helping to inform future tooling efforts. © 2014 Springer International Publishing
Genetic and environmental variation in methane emissions of sheep at pasture
A total of 2,600 methane (CH4) and 1,847 CO2 measurements of sheep housed for 1 h in portable accumulation chambers (PAC) were recorded at 5 sites from the Australian Sheep CRC Information Nucleus, which was set up to test leading young industry sires for an extensive range of current and novel production traits. The final validated dataset had 2,455 methane records from 2,279 animals, which were the progeny of 187 sires and 1,653 dams with 7,690 animals in the pedigree file. The protocol involved rounding up animals from pasture into a holding paddock before the first measurement on each day and then measuring in groups of up to 16 sheep over the course of the day. Methane emissions declined linearly (with different slopes for each site) with time since the sheep were drafted into the holding area. After log transformation, estimated repeatability (rpt) and heritability (h(2)) of liveweight-adjusted CH4 emissions averaged 25% and 11.7%, respectively, for a single 1-h measurement. Sire Ă— site interactions were small and nonsignificant. Correlations between EBV for methane emissions and Sheep Genetics Australia EBV for production traits were used as approximations to genetic correlations. Apart from small positive correlations with weaning and yearling weights (r = 0.21-0.25, P < 0.05), there were no significant relationships between production trait and methane EBV (calculated from a model adjusting for liveweight by fitting separate slopes for each site). To improve accuracy, future protocols should use the mean of 2 (rpt = 39%, h(2) = 18.6%) or 3 (rpt = 48%, h(2) = 23.2%) PAC measurements. Repeat tests under different pasture conditions and time of year should also be considered, as well as protocols measuring animals directly off pasture instead of rounding them up in the morning. Reducing the time in the PAC from 1 h to 40 min would have a relatively small effect on overall accuracy and partly offset the additional time needed for more tests per animal. Field testing in PAC has the potential to provide accurate comparisons of animal and site methane emissions, with potentially lower cost/increased accuracy compared to alternatives such as SF6 tracers or open path lasers. If similar results are obtained from tests with different protocols/seasonal conditions, use of PAC measurements in a multitrait selection index with production traits could potentially reduce methane emissions from Australian sheep for the same production level
Systematics of Leading Particle Production
Using a QCD inspired model developed by our group for particle production,
the Interacting Gluon Model (IGM), we have made a systematic analysis of all
available data on leading particle spectra. These data include diffractive
collisions and photoproduction at HERA. With a small number of parameters
(essentially only the non-perturbative gluon-gluon cross section and the
fraction of diffractive events) good agreement with data is found. We show that
the difference between pion and proton leading spectra is due to their
different gluon distributions. We predict a universality in the diffractive
leading particle spectra in the large momentum region, which turns out to be
independent of the incident energy and of the projectile type.Comment: 13 pages, Latex, 4 ps figures. To appear in Phys. Rev.
Argentine Wheat Industry: Conference Report
Established and supported under the Australian Government’s Cooperative Research Centre Progra
Prevalencia y estacionalidad de la Pediculosis capitis en la poblaciĂłn infante-juvenil de la region sanitaria, Buenos Aires, Argentina
Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk
BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7Ă—10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4Ă—10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4Ă—10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat
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