Analysis of Software Binaries for Reengineering-Driven Product Line Architecture\^aAn Industrial Case Study

This paper describes a method for the recovering of software architectures from a set of similar (but unrelated) software products in binary form. One intention is to drive refactoring into software product lines and combine architecture recovery with run time binary analysis and existing clustering methods. Using our runtime binary analysis, we create graphs that capture the dependencies between different software parts. These are clustered into smaller component graphs, that group software parts with high interactions into larger entities. The component graphs serve as a basis for further software product line work. In this paper, we concentrate on the analysis part of the method and the graph clustering. We apply the graph clustering method to a real application in the context of automation / robot configuration software tools.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301

BOSS-LDG: A Novel Computational Framework that Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery

We present a novel computational framework that connects Blue Waters, the NSF-supported, leadership-class supercomputer operated by NCSA, to the Laser Interferometer Gravitational-Wave Observatory (LIGO) Data Grid via Open Science Grid technology. To enable this computational infrastructure, we configured, for the first time, a LIGO Data Grid Tier-1 Center that can submit heterogeneous LIGO workflows using Open Science Grid facilities. In order to enable a seamless connection between the LIGO Data Grid and Blue Waters via Open Science Grid, we utilize Shifter to containerize LIGO's workflow software. This work represents the first time Open Science Grid, Shifter, and Blue Waters are unified to tackle a scientific problem and, in particular, it is the first time a framework of this nature is used in the context of large scale gravitational wave data analysis. This new framework has been used in the last several weeks of LIGO's second discovery campaign to run the most computationally demanding gravitational wave search workflows on Blue Waters, and accelerate discovery in the emergent field of gravitational wave astrophysics. We discuss the implications of this novel framework for a wider ecosystem of Higher Performance Computing users.Comment: 10 pages, 10 figures. Accepted as a Full Research Paper to the 13th IEEE International Conference on eScienc

Exploring hybridity in food supply chains

In recent years, a number of dynamic aspects of food supply chains have attracted great interest among social scientists investigating rural restructuring and change. These include: the expansion of organic agriculture; the development of new value added enterprises at farm level and the revitalisation of traditional and new-old artisanal production practices; the expansion from a low base of the market share of alternative short supply chains, such as farmers markets; and the so-called quality turn, riding on the heels of another turn in rural social research - the consumption turn. All of these changes come together in a vision of alternative agro food networks (AAFNs) that has been built around empirical and theoretical work from a number of predominantly European social researchers, centred on Wageningen, but conducted in a number of countries in Europe. These and other associated changes in the composition of farm-based economic activity are seen to be constitutive of a new paradigm of rural development comprising an alternative network of producers, consumers and other actors in relation to the mainstream agro-food system (Van der Ploeg et al. 2000; Van der Ploeg and Renting 2004; Renting et al. 2003). The theorisation surrounding this work on AAFNs has been sharply criticised by Goodman (2004). He challenges the vision of certain European social scientists of an alternative food sector rising like a phoenix from the ashes of the commodity-based food system to constitute a new paradigm of rural development. He notes their view of AAFNs as: innovative precursors of paradigm change, of a more endogenous, territorialized and ecologically embedded successor to the allegedly crisis-ridden modernisation model of conventional industrialised agriculture. (Goodman 2004:6) In particular, he challenges the binary categorisation into alternative and mainstream and is deeply sceptical as to the existence of a new paradigm while, at the same time, highly cognisant of dynamic changes within the agro-food sector. This paper is motivated by a desire to explore the extent to which different theories can help interpret and explain some of the most dynamic areas of agro-food systems that belong neither in the mainstream food supply chains and networks, nor in the alternative food supply networks. We review two areas where we argue that hybridity is evident in food supply chains and networks, and draw conclusions as to the research needs in a field where too often dualistic interpretations have prevailed.Agribusiness,

On ab initio-based, free and closed-form expressions for gravitational waves

We introduce a new approach for fnding high accuracy, free and closed-form expressions for the gravitational waves emitted by binary black hole collisions from ab initio models. More precisely, our expressions are built from numerical surrogate models based on supercomputer simulations of the Einstein equations, which have been shown to be essentially indistinguishable from each other. Distinct aspects of our approach are that: (i) representations of the gravitational waves can be explicitly written in a few lines, (ii) these representations are free-form yet still fast to search for and validate and (iii) there are no underlying physical approximations in the underlying model. The key strategy is combining techniques from Artifcial Intelligence and Reduced Order Modeling for parameterized systems. Namely, symbolic regression through genetic programming combined with sparse representations in parameter space and the time domain using Reduced Basis and the Empirical Interpolation Method enabling fast free-form symbolic searches and large-scale a posteriori validations. As a proof of concept we present our results for the collision of two black holes, initially without spin, and with an initial separation corresponding to 25–31 gravitational wave cycles before merger. The minimum overlap, compared to ground truth solutions, is 99%. That is, 1% diference between our closed-form expressions and supercomputer simulations; this is considered for gravitational (GW) science more than the minimum required due to experimental numerical errors which otherwise dominate. This paper aims to contribute to the feld of GWs in particular and Artifcial Intelligence in general.Fil: Tiglio, Manuel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física. Sección Ciencias de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Villanueva, Uziel Aarón. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física. Sección Ciencias de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentin

Moving in, out, through, and beyond the tensions between experience and social construction in somatic theory

This article is a reflexive analysis of the author’s movement through the positions of different somatic theories. While some somatic theorists and practitioners focus on ideas of self and experiential knowledge, others are moving into a more postmodern realm by looking at bodies and somatic experience as social constructions. The author traces her movement through these theories and towards a non-binary postmodern view of somatics that does not dismiss the role of experience. Two narratives serve as a vehicle whereby the author wrestles with the issues

Reduced Order and Surrogate Models for Gravitational Waves

We present an introduction to some of the state of the art in reduced order and surrogate modeling in gravitational wave (GW) science. Approaches that we cover include Principal Component Analysis, Proper Orthogonal Decomposition, the Reduced Basis approach, the Empirical Interpolation Method, Reduced Order Quadratures, and Compressed Likelihood evaluations. We divide the review into three parts: representation/compression of known data, predictive models, and data analysis. The targeted audience is that one of practitioners in GW science, a field in which building predictive models and data analysis tools that are both accurate and fast to evaluate, especially when dealing with large amounts of data and intensive computations, are necessary yet can be challenging. As such, practical presentations and, sometimes, heuristic approaches are here preferred over rigor when the latter is not available. This review aims to be self-contained, within reasonable page limits, with little previous knowledge (at the undergraduate level) requirements in mathematics, scientific computing, and other disciplines. Emphasis is placed on optimality, as well as the curse of dimensionality and approaches that might have the promise of beating it. We also review most of the state of the art of GW surrogates. Some numerical algorithms, conditioning details, scalability, parallelization and other practical points are discussed. The approaches presented are to large extent non-intrusive and data-driven and can therefore be applicable to other disciplines. We close with open challenges in high dimension surrogates, which are not unique to GW science.Comment: Invited article for Living Reviews in Relativity. 93 page