Towards correct-by-construction product variants of a software product line: GFML, a formal language for feature modules

Software Product Line Engineering (SPLE) is a software engineering paradigm that focuses on reuse and variability. Although feature-oriented programming (FOP) can implement software product line efficiently, we still need a method to generate and prove correctness of all product variants more efficiently and automatically. In this context, we propose to manipulate feature modules which contain three kinds of artifacts: specification, code and correctness proof. We depict a methodology and a platform that help the user to automatically produce correct-by-construction product variants from the related feature modules. As a first step of this project, we begin by proposing a language, GFML, allowing the developer to write such feature modules. This language is designed so that the artifacts can be easily reused and composed. GFML files contain the different artifacts mentioned above.The idea is to compile them into FoCaLiZe, a language for specification, implementation and formal proof with some object-oriented flavor. In this paper, we define and illustrate this language. We also introduce a way to compose the feature modules on some examples.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301

Zakharov simulation study of spectral features of on-demand Langmuir turbulence in an inhomogeneous plasma

We have performed a simulation study of Langmuir turbulence in the Earth's ionosphere by means of a Zakharov model with parameters relevant for the F layer. The model includes dissipative terms to model collisions and Landau damping of the electrons and ions, and a linear density profile, which models the ionospheric plasma inhomogeneity whose length scale is of the order 10--100 km. The injection of energy into the system is modeled by a constant source term in the Zakharov equation. Langmuir turbulence is excited ``on-demand'' in controlled ionospheric modification experiments where the energy is provided by an HF radio beam injected into the overhead ionospheric plasma. The ensuing turbulence can be studied with radars and in the form of secondary radiation recorded by ground-based receivers. We have analyzed spectral signatures of the turbulence for different sets of parameters and different altitudes relative to the turning point of the linear Langmuir mode where the Langmuir frequency equals the local plasma frequency. By a parametric analysis, we have derived a simple scaling law, which links the spectral width of the turbulent frequency spectrum to the physical parameters in the ionosphere. The scaling law provides a quantitative relation between the physical parameters (temperatures, electron number density, ionospheric length scale, etc.) and the observed frequency spectrum. This law may be useful for interpreting experimental results.Comment: 7 pages, 8 figure

Testing the diffusion hypothesis as a mechanism of self-healing in Disperse orange 11 doped in PMMA

In this work, we show that reversible photodegradation of Disperse Orange 11 doped in PMMA is not due to dye diffusion - a common phenomenon observed in many dye-doped polymers. The change in linear absorbance due to photodegradation of the material shows an isobestic point, which is consistent with the formation of a quasi-stable damaged species. Spatially-resolved amplified spontaneous emission and fluorescence, both related to the population density, are measured by scanning the pump beam over a burn mark. A numerical model of the time evolution of the population density due to diffusion is inconsistent with the experimental data suggesting that diffusion is not responsible.Comment: 5 pages, 6 figure

Cracking in asphalt materials

This chapter provides a comprehensive review of both laboratory characterization and modelling of bulk material fracture in asphalt mixtures. For the purpose of organization, this chapter is divided into a section on laboratory tests and a section on models. The laboratory characterization section is further subdivided on the basis of predominant loading conditions (monotonic vs. cyclic). The section on constitutive models is subdivided into two sections, the first one containing fracture mechanics based models for crack initiation and propagation that do not include material degradation due to cyclic loading conditions. The second section discusses phenomenological models that have been developed for crack growth through the use of dissipated energy and damage accumulation concepts. These latter models have the capability to simulate degradation of material capacity upon exceeding a threshold number of loading cycles.Peer ReviewedPostprint (author's final draft

Learning Instance-Specific Augmentations by Capturing Local Invariances

We introduce InstaAug, a method for automatically learning input-specific augmentations from data. Previous methods for learning augmentations have typically assumed independence between the original input and the transformation applied to that input. This can be highly restrictive, as the invariances we hope our augmentation will capture are themselves often highly input dependent. InstaAug instead introduces a learnable invariance module that maps from inputs to tailored transformation parameters, allowing local invariances to be captured. This can be simultaneously trained alongside the downstream model in a fully end-to-end manner, or separately learned for a pre-trained model. We empirically demonstrate that InstaAug learns meaningful input-dependent augmentations for a wide range of transformation classes, which in turn provides better performance on both supervised and self-supervised tasks

Blowing cold flows away: the impact of early AGN activity on the formation of a brightest cluster galaxy progenitor

Supermassive black holes (BH) are powerful sources of energy that are already in place at very early epochs of the Universe (by z=6). Using hydrodynamical simulations of the formation of a massive M_vir=5 10^11 M_sun halo by z=6 (the most massive progenitor of a cluster of M_vir=2 10^15 M_sun at z=0), we evaluate the impact of Active Galactic Nuclei (AGN) on galaxy mass content, BH self-regulation, and gas distribution inside this massive halo. We find that SN feedback has a marginal influence on the stellar structure, and no influence on the mass distribution on large scales. In contrast, AGN feedback alone is able to significantly alter the stellar-bulge mass content by quenching star formation when the BH is self-regulating, and by depleting the cold gas reservoir in the centre of the galaxy. The growth of the BH proceeds first by a rapid Eddington-limited period fed by direct cold filamentary infall. When the energy delivered by the AGN is sufficiently large to unbind the cold gas of the bulge, the accretion of gas onto the BH is maintained both by smooth gas inflow and clump migration through the galactic disc triggered by merger-induced torques. The feedback from the AGN has also a severe consequence on the baryon mass content within the halo, producing large-scale hot superwinds, able to blow away some of the cold filamentary material from the centre and reduce the baryon fraction by more than 30 per cent within the halo's virial radius. Thus in the very young universe, AGN feedback is likely to be a key process, shaping the properties of the most massive galaxies.Comment: 18 pages, 16 figures, MNRAS accepte

Association of Human iPSC Gene Signatures and X Chromosome Dosage with Two Distinct Cardiac Differentiation Trajectories.

Despite the importance of understanding how variability across induced pluripotent stem cell (iPSC) lines due to non-genetic factors (clone and passage) influences their differentiation outcome, large-scale studies capable of addressing this question have not yet been conducted. Here, we differentiated 191 iPSC lines to generate iPSC-derived cardiovascular progenitor cells (iPSC-CVPCs). We observed cellular heterogeneity across the iPSC-CVPC samples due to varying fractions of two cell types: cardiomyocytes (CMs) and epicardium-derived cells (EPDCs). Comparing the transcriptomes of CM-fated and EPDC-fated iPSCs, we discovered that 91 signature genes and X chromosome dosage differences are associated with these two distinct cardiac developmental trajectories. In an independent set of 39 iPSCs differentiated into CMs, we confirmed that sex and transcriptional differences affect cardiac-fate outcome. Our study provides novel insights into how iPSC transcriptional and X chromosome gene dosage differences influence their response to differentiation stimuli and, hence, cardiac cell fate