180,442 research outputs found

    Synthesis of Attributed Feature Models From Product Descriptions: Foundations

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    Feature modeling is a widely used formalism to characterize a set of products (also called configurations). As a manual elaboration is a long and arduous task, numerous techniques have been proposed to reverse engineer feature models from various kinds of artefacts. But none of them synthesize feature attributes (or constraints over attributes) despite the practical relevance of attributes for documenting the different values across a range of products. In this report, we develop an algorithm for synthesizing attributed feature models given a set of product descriptions. We present sound, complete, and parametrizable techniques for computing all possible hierarchies, feature groups, placements of feature attributes, domain values, and constraints. We perform a complexity analysis w.r.t. number of features, attributes, configurations, and domain size. We also evaluate the scalability of our synthesis procedure using randomized configuration matrices. This report is a first step that aims to describe the foundations for synthesizing attributed feature models

    Hierarchical Coding for Distributed Computing

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    Coding for distributed computing supports low-latency computation by relieving the burden of straggling workers. While most existing works assume a simple master-worker model, we consider a hierarchical computational structure consisting of groups of workers, motivated by the need to reflect the architectures of real-world distributed computing systems. In this work, we propose a hierarchical coding scheme for this model, as well as analyze its decoding cost and expected computation time. Specifically, we first provide upper and lower bounds on the expected computing time of the proposed scheme. We also show that our scheme enables efficient parallel decoding, thus reducing decoding costs by orders of magnitude over non-hierarchical schemes. When considering both decoding cost and computing time, the proposed hierarchical coding is shown to outperform existing schemes in many practical scenarios.Comment: 7 pages, part of the paper is submitted to ISIT201

    Improvements to NESTLE: Cross Section Interpolation and \u3ci\u3eN\u3c/i\u3e-Group Extension

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    The NESTLE program is a few-group neutron diffusion reactor core simulator code utilizing the nodal expansion method (NEM). This thesis presents two improvements made to NESTLE regarding cross-section interpolation and multigroup capability. To quickly and accurately obtain cross sections from lattice physics input data, a new cross section interpolation routine was developed utilizing multidimensional radial basis function interpolation, also known as thin plate spline interpolation. Testing showed that, for existing NESTLE lattice physics input, accuracy was retained but not improved and processing time was longer. However, the new interpolation routine was shown allow much greater exibility in the case matrix of the the lattice physics input file. This allows for much more detailed modeling of cross section variation at the expense of computation time. The existing capability of NESTLE to use two or four neutron energy groups in the NEM calculation was supplemented with a new routine to allow the use of an arbitrary number of neutron energy groups by calling existing, widely used linear algebra libraries. This represents a significant expansion of NESTLE\u27s capability to model a broader ranger of reactor types beyond typical light water reactors (LWRs). Testing revealed that the new NEM routines retained the accuracy and speed of the existing routines for two and four energy groups, while calculations with other numbers of energy groups had adequate accuracy and speed for practical use

    Black Box White Arrow

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    The present paper proposes a new and systematic approach to the so-called black box group methods in computational group theory. Instead of a single black box, we consider categories of black boxes and their morphisms. This makes new classes of black box problems accessible. For example, we can enrich black box groups by actions of outer automorphisms. As an example of application of this technique, we construct Frobenius maps on black box groups of untwisted Lie type in odd characteristic (Section 6) and inverse-transpose automorphisms on black box groups encrypting (P)SLn(Fq){\rm (P)SL}_n(\mathbb{F}_q). One of the advantages of our approach is that it allows us to work in black box groups over finite fields of big characteristic. Another advantage is explanatory power of our methods; as an example, we explain Kantor's and Kassabov's construction of an involution in black box groups encrypting SL2(2n){\rm SL}_2(2^n). Due to the nature of our work we also have to discuss a few methodological issues of the black box group theory. The paper is further development of our text "Fifty shades of black" [arXiv:1308.2487], and repeats parts of it, but under a weaker axioms for black box groups.Comment: arXiv admin note: substantial text overlap with arXiv:1308.248
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