Feature Model Synthesis

Variability provides the ability to adapt and customize a software system's artifacts for a particular context or circumstance. Variability enables code reuse, but its mechanisms are often tangled within a software artifact or scattered over multiple artifacts. This makes the system harder to maintain for developers, and harder to understand for users that configure the software. Feature models provide a centralized source for describing the variability in a software system. A feature model consists of a hierarchy of features—the common and variable system characteristics—with constraints between features. Constructing a feature model, however, is a arduous and time-consuming manual process. We developed two techniques for feature model synthesis. The first, Feature-Graph-Extraction, is an automated algorithm for extracting a feature graph from a propositional formula in either conjunctive normal form (CNF), or disjunctive normal form (DNF). A feature graph describes all feature diagrams that are complete with respect to the input. We evaluated our algorithms against related synthesis algorithms and found that our CNF variant was significantly faster than the previous comparable technique, and the DNF algorithm performed similarly to a comparable, but newer technique, with the exception of several models where our algorithm was faster. The second, Feature-Tree-Synthesis, is a semi-automated technique for building a feature model given a feature graph. This technique uses both logical constraints and text to address the most challenging part of feature model synthesis—constructing the feature hierarchy—by ranking potential parents of a feature with a textual similarity heuristic. We found that the procedure effectively reduced a modeler's choices from thousands, to five or less when synthesizing the Linux and eCos variability models. Our third contribution is the analysis of Kconfig—a language similar to feature modeling used to specify the variability model of the Linux kernel. While large feature models are reportedly used in industry, these models have not been available to the research community for benchmarking feature model analysis and synthesis techniques. We compare Kconfig to feature modeling, reverse engineer formal semantics, and translate 12 open-source Kconfig models—including the Linux model with over 6000 features—to propositional logic

Feature Model Mining

Software systems have grown larger and more complex in recent years. Generative software development strives to automate software development from a systems family by generating implementations using domain-specific languages. In current practice, specifying domain-specific languages is a manual task requiring expert analysis of multiple information sources. Furthermore, the concepts and relations represented in a language are grown through its usage. Keeping the language consistent with its usage is a time-consuming process requiring manual comparison between the language instances and its language specification. Feature model mining addresses these issues by synthesizing a representative model bottom-up from a sample set of instances called configurations. This thesis presents a mining algorithm that reverse-engineers a probabilistic feature model from a set of individual configurations. A configuration consists of a list of features that are defined as system properties that a stakeholder is interested in. Probabilistic expressions are retrieved from the sample configurations through the use of conjunctive and disjunctive association rule mining. These expressions are used to construct a probabilistic feature model. The mined feature model consists of a hierarchy of features, a set of additional hard constraints and soft constraints. The hierarchy describes the dependencies and alternative relations exhibited among the features. The additional hard constraints are a set of propositional formulas which must be satisfied in a legal configuration. Soft constraints describe likely defaults or common patterns. Systems families are often realized using object-oriented frameworks that provide reusable designs for constructing a family of applications. The mining algorithm is evaluated on a set of applications to retrieve a metamodel of the Java Applet framework. The feature model is then applied to the development of framework-specific modeling languages (FSMLs). FSMLs are domain-specific languages that model the framework-provided concepts and their rules for development. The work presented in this thesis provides the foundation for further research in feature model mining. The strengths and weaknesses of the algorithm are analyzed and the thesis concludes with a discussion of possible extensions.</p

Coordinated and Distinct Functions of Velvet Proteins in \u3ci\u3eFusarium verticillioides\u3c/i\u3e

Velvet-domain-containing proteins are broadly distributed within the fungal kingdom. In the corn pathogen Fusarium verticillioides, previous studies showed that the velvet protein F. verticillioides VE1 (FvVE1) is critical for morphological development, colony hydrophobicity, toxin production, and pathogenicity. In this study, tandem affinity purification of FvVE1 revealed that FvVE1 can form a complex with the velvet proteins F. verticillioides VelB (FvVelB) and FvVelC. Phenotypic characterization of gene knockout mutants showed that, as in the case of FvVE1, FvVelB regulated conidial size, hyphal hydrophobicity, fumonisin production, and oxidant resistance, while FvVelC was dispensable for these biological processes. Comparative transcriptional analysis of eight genes involved in the ROS (reactive oxygen species) removal system revealed that both FvVE1 and FvVelB positively regulated the transcription of a catalase-encoding gene, F. verticillioides CAT2 (FvCAT2). Deletion of FvCAT2 resulted in reduced oxidant resistance, providing further explanation of the regulation of oxidant resistance by velvet proteins in the fungal kingdom. Includes supplemental material

Coordinated and Distinct Functions of Velvet Proteins in \u3ci\u3eFusarium verticillioides\u3c/i\u3e

Velvet-domain-containing proteins are broadly distributed within the fungal kingdom. In the corn pathogen Fusarium verticillioides, previous studies showed that the velvet protein F. verticillioides VE1 (FvVE1) is critical for morphological development, colony hydrophobicity, toxin production, and pathogenicity. In this study, tandem affinity purification of FvVE1 revealed that FvVE1 can form a complex with the velvet proteins F. verticillioides VelB (FvVelB) and FvVelC. Phenotypic characterization of gene knockout mutants showed that, as in the case of FvVE1, FvVelB regulated conidial size, hyphal hydrophobicity, fumonisin production, and oxidant resistance, while FvVelC was dispensable for these biological processes. Comparative transcriptional analysis of eight genes involved in the ROS (reactive oxygen species) removal system revealed that both FvVE1 and FvVelB positively regulated the transcription of a catalase-encoding gene, F. verticillioides CAT2 (FvCAT2). Deletion of FvCAT2 resulted in reduced oxidant resistance, providing further explanation of the regulation of oxidant resistance by velvet proteins in the fungal kingdom. Includes supplemental material

Coordinated and Distinct Functions of Velvet Proteins in \u3ci\u3eFusarium verticillioides\u3c/i\u3e

Velvet-domain-containing proteins are broadly distributed within the fungal kingdom. In the corn pathogen Fusarium verticillioides, previous studies showed that the velvet protein F. verticillioides VE1 (FvVE1) is critical for morphological development, colony hydrophobicity, toxin production, and pathogenicity. In this study, tandem affinity purification of FvVE1 revealed that FvVE1 can form a complex with the velvet proteins F. verticillioides VelB (FvVelB) and FvVelC. Phenotypic characterization of gene knockout mutants showed that, as in the case of FvVE1, FvVelB regulated conidial size, hyphal hydrophobicity, fumonisin production, and oxidant resistance, while FvVelC was dispensable for these biological processes. Comparative transcriptional analysis of eight genes involved in the ROS (reactive oxygen species) removal system revealed that both FvVE1 and FvVelB positively regulated the transcription of a catalase-encoding gene, F. verticillioides CAT2 (FvCAT2). Deletion of FvCAT2 resulted in reduced oxidant resistance, providing further explanation of the regulation of oxidant resistance by velvet proteins in the fungal kingdom. Includes supplemental material

Seasonal variations of semidiurnal tidalperturbations in mesopause region temperature and zonal and meridional winds above Fort Collins, Colorado(40.6°N, 105.1°W)

On the basis of Colorado State University (CSU) Na lidar observations over full diurnal cycles from May 2002 to April 2006, a harmonic analysis was performed to extract semidiurnal perturbations in mesopause region temperature and zonal and meridional winds over Fort Collins, Colorado (40.6°N, 105.1°W). The observed monthly results are in good agreement with MF radar tidal climatology for Urbana, Illinois, and with predictions of the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), sampled at the CSU Na lidar coordinates. The observed semidiurnal tidal period perturbation within the mesopause region is found to be dominated by propagating modes in winter and equinoctial months with a combined vertical wavelength varying from 50 km to almost 90 km and by a mode with evanescent behavior and longer vertical wavelength (100–150 km) in summer months, most likely due to dominance of (2, 2) and (2, 3) tidal (Hough) modes. The observed semidiurnal tidal amplitude shows strong seasonal variation, with a large amplitude during the winter months, with a higher growth rate above ∼85–90 km, and minimal amplitudes during the summer months. Maximum tidal amplitudes over 50 m/s for wind and 12 K for temperature occur during fall equinox. A detailed comparison with HAMMONIA predictions shows excellent agreement in semidiurnal phases. HAMMONIA-predicted semidiurnal amplitudes generally agree well with observations; however, HOMMONIA underestimates temperature amplitudes in some of the nonsummer months as well as zonal wind and meridional wind amplitudes in April and September but overestimates them in February. To reveal the effects of the atmospheric background on vertical propagation of tidal modes and their relative importance in the composite semidiurnal tide during different seasons, we use the lidar-observed monthly mean temperature and zonal wind from the same data set as well as HAMMONIA output to calculate the vertical wave number seasonal variations of the major tidal modes of the migrating semidiurnal tide. This leads to a qualitative understanding of the lidar-observed and HAMMONIA-predicted seasonal variation of the semidiurnal tidal perturbation

Kurt Eisner: Ein unvollendetes Leben

Abstract. Understanding the challenges faced by real projects in evolving variability models, is a prerequisite for providing adequate support for such undertakings. We study the evolution of a model describing features and configurations in a large product line—the Linux kernel variability model. We analyze this evolution quantitatively and qualitatively. Our primary finding is that the Linux kernel model appears to evolve surprisingly smoothly. In the analyzed period, the number of features had doubled, and still the structural complexity of the model remained roughly the same. Furthermore, we provide an in-depth look at the effect of the kernel’s development methodologies on the evolution of its model. We also include evidence about edit operations applied in practice, evidence of challenges in maintaining large models, and a range of recommendations (and open problems) for builders of modeling tools.

2008), Seasonal variations of semidiurnal tidal perturbations in mesopause region temperature and zonal and meridional winds above Fort

[1] On the basis of Colorado State University (CSU) Na lidar observations over full diurnal cycles from May 2002 to April 2006, a harmonic analysis was performed to extract semidiurnal perturbations in mesopause region temperature and zonal and meridional winds over Fort Collins, Colorado (40.6°N, 105.1°W). The observed monthly results are in good agreement with MF radar tidal climatology for Urbana, Illinois, and with predictions of the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), sampled at the CSU Na lidar coordinates. The observed semidiurnal tidal period perturbation within the mesopause region is found to be dominated by propagating modes in winter and equinoctial months with a combined vertical wavelength varying from 50 km to almost 90 km and by a mode with evanescent behavior and longer vertical wavelength (100-150 km) in summer months, most likely due to dominance of (2, 2) and (2, 3) tidal (Hough) modes. The observed semidiurnal tidal amplitude shows strong seasonal variation, with a large amplitude during the winter months, with a higher growth rate above $85-90 km, and minimal amplitudes during the summer months. Maximum tidal amplitudes over 50 m/s for wind and 12 K for temperature occur during fall equinox. A detailed comparison with HAMMONIA predictions shows excellent agreement in semidiurnal phases. HAMMONIA-predicted semidiurnal amplitudes generally agree well with observations; however, HOMMONIA underestimates temperature amplitudes in some of the nonsummer months as well as zonal wind and meridional wind amplitudes in April and September but overestimates them in February. To reveal the effects of the atmospheric background on vertical propagation of tidal modes and their relative importance in the composite semidiurnal tide during different seasons, we use the lidarobserved monthly mean temperature and zonal wind from the same data set as well as HAMMONIA output to calculate the vertical wave number seasonal variations of the major tidal modes of the migrating semidiurnal tide. This leads to a qualitative understanding of the lidar-observed and HAMMONIA-predicted seasonal variation of the semidiurnal tidal perturbation

Structure Determination, Functional Characterization, and Biosynthetic Implications of Nybomycin Metabolites from a Mining Reclamation Site-Associated \u3cem\u3eStreptomyces\u3c/em\u3e

We report the isolation and characterization of three new nybomycins (nybomycins B–D, 1–3) and six known compounds (nybomycin, 4; deoxynyboquinone, 5; α-rubromycin, 6; β-rubromycin, 7; γ-rubromycin, 8; and [2α(1E,3E),4β]-2-(1,3-pentadienyl)-4-piperidinol, 9) from the Rock Creek (McCreary County, KY) underground coal mine acid reclamation site isolate Streptomyces sp. AD-3-6. Nybomycin D (3) and deoxynyboquinone (5) displayed moderate (3) to potent (5) cancer cell line cytotoxicity and displayed weak to moderate anti-Gram-(+) bacterial activity, whereas rubromycins 6–8 displayed little to no cancer cell line cytotoxicity but moderate to potent anti-Gram-(+) bacterial and antifungal activity. Assessment of the impact of 3 or 5 cancer cell line treatment on 4E-BP1 phosphorylation, a predictive marker of ROS-mediated control of cap-dependent translation, also revealed deoxynyboquinone (5)-mediated downstream inhibition of 4E-BP1p. Evaluation of 1–9 in a recently established axolotl embryo tail regeneration assay also highlighted the prototypical telomerase inhibitor γ-rubromycin (8) as a new inhibitor of tail regeneration. Cumulatively, this work highlights an alternative nybomycin production strain, a small set of new nybomycin metabolites, and previously unknown functions of rubromycins (antifungal activity and inhibition of tail regeneration) and also provides a basis for revision of the previously proposed nybomycin biosynthetic pathway