85,634 research outputs found

    Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines

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    In Software Product Lines (SPLs) it is not possible, in general, to test all products of the family. The number of products denoted by a SPL is very high due to the combinatorial explosion of features. For this reason, some coverage criteria have been proposed which try to test at least all feature interactions without the necessity to test all products, e.g., all pairs of features (pairwise coverage). In addition, it is desirable to first test products composed by a set of priority features. This problem is known as the Prioritized Pairwise Test Data Generation Problem. In this work we propose two hybrid algorithms using Integer Programming (IP) to generate a prioritized test suite. The first one is based on an integer linear formulation and the second one is based on a integer quadratic (nonlinear) formulation. We compare these techniques with two state-of-the-art algorithms, the Parallel Prioritized Genetic Solver (PPGS) and a greedy algorithm called prioritized-ICPL. Our study reveals that our hybrid nonlinear approach is clearly the best in both, solution quality and computation time. Moreover, the nonlinear variant (the fastest one) is 27 and 42 times faster than PPGS in the two groups of instances analyzed in this work.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Partially funded by the Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2014-57341-R, the University of Málaga, Andalucía Tech and the Spanish Network TIN2015-71841-REDT (SEBASENet)

    A Systematic Approach to Constructing Families of Incremental Topology Control Algorithms Using Graph Transformation

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    In the communication systems domain, constructing and maintaining network topologies via topology control (TC) algorithms is an important cross-cutting research area. Network topologies are usually modeled using attributed graphs whose nodes and edges represent the network nodes and their interconnecting links. A key requirement of TC algorithms is to fulfill certain consistency and optimization properties to ensure a high quality of service. Still, few attempts have been made to constructively integrate these properties into the development process of TC algorithms. Furthermore, even though many TC algorithms share substantial parts (such as structural patterns or tie-breaking strategies), few works constructively leverage these commonalities and differences of TC algorithms systematically. In previous work, we addressed the constructive integration of consistency properties into the development process. We outlined a constructive, model-driven methodology for designing individual TC algorithms. Valid and high-quality topologies are characterized using declarative graph constraints; TC algorithms are specified using programmed graph transformation. We applied a well-known static analysis technique to refine a given TC algorithm in a way that the resulting algorithm preserves the specified graph constraints. In this paper, we extend our constructive methodology by generalizing it to support the specification of families of TC algorithms. To show the feasibility of our approach, we reneging six existing TC algorithms and develop e-kTC, a novel energy-efficient variant of the TC algorithm kTC. Finally, we evaluate a subset of the specified TC algorithms using a new tool integration of the graph transformation tool eMoflon and the Simonstrator network simulation framework.Comment: Corresponds to the accepted manuscrip

    Evolution of Ada technology in the flight dynamics area: Implementation/testing phase analysis

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    An analysis is presented of the software engineering issues related to the use of Ada for the implementation and system testing phases of four Ada projects developed in the flight dynamics area. These projects reflect an evolving understanding of more effective use of Ada features. In addition, the testing methodology used on these projects has changed substantially from that used on previous FORTRAN projects

    Innovation search fields with Lead Users

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    Close orientation with the market is essential for innovation success! Although both academics and market research practitioners would generally agree with this statement, alignment with the needs of the customer often results in conservative innovation strategies. Due to their focus on what is currently on offer in the marketplace, customers primarily demand small, step-wise developments - so-called incremental innovations. This dilemma can be overcome through with the help of particularly advanced customers (Lead Users). The Lead User method aids companies in capitalizing on the innovative potential of these highly qualified customers. A case study with the German firm, Johnson & Johnson Medical GmbH, demonstrated that Breakthrough Innovations are achievable this way. -- Kundenorientierung ist entscheidend für den Innovationserfolg! Obwohl dem Wissenschaftler und Praktiker in der Marktforschung grundsätzlich zustimmen dürften, ist mit der konsequenten Ausrichtung auf die Kundenbedürfnisse gleichzeitig der Nachteil einer konservativen Innovationspolitik verbunden. Kunden fördern durch ihre Fixierung auf aktuelle Marktangebot primär kleine Weiterentwicklungen, d.h. inkrementale Innovationen. Dieses Dilemma kann mit Hilfe besonders fortschrittlicher Kunden (Lead User) überwunden werden. Die Lead User Methode hilft Unternehmen dabei, das innovative Potential dieser hochqualifizierten Kunden zu nutzen. Eine Fallanwendung mit der Johnson&Johnson Medical GmbH demonstriert, wie auf diese Weise Ansätze für radikale Innovationen erarbeitet werden können.Produktentwicklung,Produktinnovation,Marktforschung,Lead User

    Deriving Models for Software Project Effort Estimation By Means of Genetic Programming

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    Software engineering, effort estimation, genetic programming, symbolic regression. This paper presents the application of a computational intelligence methodology in effort estimation for software projects. Namely, we apply a genetic programming model for symbolic regression; aiming to produce mathematical expressions that (1) are highly accurate and (2) can be used for estimating the development effort by revealing relationships between the project’s features and the required work. We selected to investigate the effectiveness of this methodology into two software engineering domains. The system was proved able to generate models in the form of handy mathematical expressions that are more accurate than those found in literature.
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