891 resultados para Computer aided software engineering
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Un plan para organizar las enseñanzas de la ingeniería del software en las titulaciones de informática de la URJC. Nowadays both industry and academic environments are showing a lot of interest in the Software Engineering discipline. Therefore, it is a challenge for universities to provide students with appropriate training in this area, preparing them for their future professional practice. There are many difficulties to provide that training. The outstanding ones are: the Software Engineering area is too broad and class hours are scarce; the discipline requires a high level of abstraction; it is difficult to reproduce real world situations in the classroom to provide a practical learning environment; the number of students per professor is very high (at least in Spain); companies develop software with a maturity level rarely over level 2 of the CMM for Software (again, at least in Spain) as opposed to what is taught at the University. Besides, there are different levels and study plans, making more difficult to structure the contents to teach in each term and degree. In this paper we present a plan for teaching Software Engineering trying to overcome some of the difficulties above.
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Nowadays, organizations have plenty of data stored in DB databases, which contain invaluable information. Decision Support Systems DSS provide the support needed to manage this information and planning médium and long-term ?the modus operandi? of these organizations. Despite the growing importance of these systems, most proposals do not include its total evelopment, mostly limiting itself on the development of isolated parts, which often have serious integration problems. Hence, methodologies that include models and processes that consider every factor are necessary. This paper will try to fill this void as it proposes an approach for developing spatial DSS driven by the development of their associated Data Warehouse DW, without forgetting its other components. To the end of framing the proposal different Engineering Software focus (The Software Engineering Process and Model Driven Architecture) are used, and coupling with the DB development methodology, (and both of them adapted to DW peculiarities). Finally, an example illustrates the proposal.
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There are many open issues that must be addressed before the replication process can be successfully formalized in empirical software engineering research. We define replication as the deliberate repetition of the same empirical study for the purpose of determining whether the results of the first experiment can be reproduced. This definition would appear at first glance to be good. However, it needs several clarifications that have not yet been forthcoming in software engineering: – What is the exact meaning of the same empirical study? Namely how similar should an experiment be to the baseline study for it to be considered a replication? What is the exact meaning of a result being reproduced? Namely how similar does a result have to be to the result of the baseline study for it to be considered reproduced? These and other methodological questions need to be researched and tailored for empirical software engineering.
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Context: Replication plays an important role in experimental disciplines. There are still many uncertain- ties about how to proceed with replications of SE experiments. Should replicators reuse the baseline experiment materials? How much liaison should there be among the original and replicating experiment- ers, if any? What elements of the experimental configuration can be changed for the experiment to be considered a replication rather than a new experiment? Objective: To improve our understanding of SE experiment replication, in this work we propose a classi- fication which is intend to provide experimenters with guidance about what types of replication they can perform. Method: The research approach followed is structured according to the following activities: (1) a litera- ture review of experiment replication in SE and in other disciplines, (2) identification of typical elements that compose an experimental configuration, (3) identification of different replications purposes and (4) development of a classification of experiment replications for SE. Results: We propose a classification of replications which provides experimenters in SE with guidance about what changes can they make in a replication and, based on these, what verification purposes such a replication can serve. The proposed classification helped to accommodate opposing views within a broader framework, it is capable of accounting for less similar replications to more similar ones regarding the baseline experiment. Conclusion: The aim of replication is to verify results, but different types of replication serve special ver- ification purposes and afford different degrees of change. Each replication type helps to discover partic- ular experimental conditions that might influence the results. The proposed classification can be used to identify changes in a replication and, based on these, understand the level of verification.
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"UILU-ENG 77 1726."
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Thesis (M.S.)--University of Illinois.
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Shipping list no.: 88-100-P.
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Software Configuration Management is the discipline of managing large collections of software development artefacts from which software products are built. Software configuration management tools typically deal with artefacts at fine levels of granularity - such as individual source code files - and assist with coordination of changes to such artefacts. This paper describes a lightweight tool, designed to be used on top of a traditional file-based configuration management system. The add-on tool support enables users to flexibly define new hierarchical views of product structure, independent of the underlying artefact-repository structure. The tool extracts configuration and change data with respect to the user-defined hierarchy, leading to improved visibility of how individual subsystems have changed. The approach yields a range of new capabilities for build managers, and verification and validation teams. The paper includes a description of our experience using the tool in an organization that builds large embedded software systems.
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The XSophe computer simulation software suite consisting of a daemon, the XSophe interface and the computational program Sophe is a state of the art package for the simulation of electron paramagnetic resonance spectra. The Sophe program performs the computer simulation and includes a number of new technologies including; the SOPHE partition and interpolation schemes, a field segmentation algorithm, homotopy, parallelisation and spectral optimisation. The SOPHE partition and interpolation scheme along with a field segmentation algorithm greatly increases the speed of simulations for most systems. Multidimensional homotopy provides an efficient method for accurately tracing energy levels and hence tracing transitions in the presence of energy level anticrossings and looping transitions and allowing computer simulations in frequency space. Recent enhancements to Sophe include the generalised treatment of distributions of orientational parameters, termed the mosaic misorientation linewidth model and a faster more efficient algorithm for the calculation of resonant field positions and transition probabilities. For complex systems the parallelisation enables the simulation of these systems on a parallel computer and the optimisation algorithms in the suite provide the experimentalist with the possibility of finding the spin Hamiltonian parameters in a systematic manner rather than a trial-and-error process. The XSophe software suite has been used to simulate multifrequency EPR spectra (200 MHz to 6 00 GHz) from isolated spin systems (S > ~½) and coupled centres (Si, Sj _> I/2). Griffin, M.; Muys, A.; Noble, C.; Wang, D.; Eldershaw, C.; Gates, K.E.; Burrage, K.; Hanson, G.R."XSophe, a Computer Simulation Software Suite for the Analysis of Electron Paramagnetic Resonance Spectra", 1999, Mol. Phys. Rep., 26, 60-84.
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Proceedings of the 44th Rocky Mountain conference on analytical chemistry
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Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.