984 resultados para Problem oriented languages


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Abstract interpretation has been widely used for the analysis of object-oriented languages and, more precisely, Java source and bytecode. However, while most of the existing work deals with the problem of finding expressive abstract domains that track accurately the characteristics of a particular concrete property, the underlying fixpoint algorithms have received comparatively less attention. In fact, many existing (abstract interpretation based) fixpoint algorithms rely on relatively inefficient techniques to solve inter-procedural call graphs or are specific and tied to particular analyses. We argue that the design of an efficient fixpoint algorithm is pivotal to support the analysis of large programs. In this paper we introduce a novel algorithm for analysis of Java bytecode which includes a number of optimizations in order to reduce the number of iterations. Also, the algorithm is parametric in the sense that it is independent of the abstract domain used and it can be applied to different domains as "plug-ins". It is also incremental in the sense that, if desired, analysis data can be saved so that only a reduced amount of reanalysis is needed after a small program change, which can be instrumental for large programs. The algorithm is also multivariant and flowsensitive. Finally, another interesting characteristic of the algorithm is that it is based on a program transformation, prior to the analysis, that results in a highly uniform representation of all the features in the language and therefore simplifies analysis. Detailed descriptions of decompilation solutions are provided and discussed with an example.

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Modern object oriented languages like C# and JAVA enable developers to build complex application in less time. These languages are based on selecting heap allocated pass-by-reference objects for user defined data structures. This simplifies programming by automatically managing memory allocation and deallocation in conjunction with automated garbage collection. This simplification of programming comes at the cost of performance. Using pass-by-reference objects instead of lighter weight pass-by value structs can have memory impact in some cases. These costs can be critical when these application runs on limited resource environments such as mobile devices and cloud computing systems. We explore the problem by using the simple and uniform memory model to improve the performance. In this work we address this problem by providing an automated and sounds static conversion analysis which identifies if a by reference type can be safely converted to a by value type where the conversion may result in performance improvements. This works focus on C# programs. Our approach is based on a combination of syntactic and semantic checks to identify classes that are safe to convert. We evaluate the effectiveness of our work in identifying convertible types and impact of this transformation. The result shows that the transformation of reference type to value type can have substantial performance impact in practice. In our case studies we optimize the performance in Barnes-Hut program which shows total memory allocation decreased by 93% and execution time also reduced by 15%.

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With the advent of object-oriented languages and the portability of Java, the development and use of class libraries has become widespread. Effective class reuse depends on class reliability which in turn depends on thorough testing. This paper describes a class testing approach based on modeling each test case with a tuple and then generating large numbers of tuples to thoroughly cover an input space with many interesting combinations of values. The testing approach is supported by the Roast framework for the testing of Java classes. Roast provides automated tuple generation based on boundary values, unit operations that support driver standardization, and test case templates used for code generation. Roast produces thorough, compact test drivers with low development and maintenance cost. The framework and tool support are illustrated on a number of non-trivial classes, including a graphical user interface policy manager. Quantitative results are presented to substantiate the practicality and effectiveness of the approach. Copyright (C) 2002 John Wiley Sons, Ltd.

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Tese de Mestrado em Engenharia Informática

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Dissertação apresentada como requisito parcial para a obtenção do grau de Mestre em Estatística e Gestão de Informação

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El projecte consisteix en el desenvolupament d'una eina especialitzada per a la classificació i recerca de productes. L'aplicació pot ser fàcilment ampliable per a adaptar-la a qualsevol tipus de producte o necessitat futura. Per a la programació d'aquest projecte es va aprofitar la potència i senzillesa que proporciona l'entorn .NET i els seus llenguatges orientats a objecte, en aquest cas VB.

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In an earlier investigation (Burger et al., 2000) five sediment cores near the RodriguesTriple Junction in the Indian Ocean were studied applying classical statistical methods(fuzzy c-means clustering, linear mixing model, principal component analysis) for theextraction of endmembers and evaluating the spatial and temporal variation ofgeochemical signals. Three main factors of sedimentation were expected by the marinegeologists: a volcano-genetic, a hydro-hydrothermal and an ultra-basic factor. Thedisplay of fuzzy membership values and/or factor scores versus depth providedconsistent results for two factors only; the ultra-basic component could not beidentified. The reason for this may be that only traditional statistical methods wereapplied, i.e. the untransformed components were used and the cosine-theta coefficient assimilarity measure.During the last decade considerable progress in compositional data analysis was madeand many case studies were published using new tools for exploratory analysis of thesedata. Therefore it makes sense to check if the application of suitable data transformations,reduction of the D-part simplex to two or three factors and visualinterpretation of the factor scores would lead to a revision of earlier results and toanswers to open questions . In this paper we follow the lines of a paper of R. Tolosana-Delgado et al. (2005) starting with a problem-oriented interpretation of the biplotscattergram, extracting compositional factors, ilr-transformation of the components andvisualization of the factor scores in a spatial context: The compositional factors will beplotted versus depth (time) of the core samples in order to facilitate the identification ofthe expected sources of the sedimentary process.Kew words: compositional data analysis, biplot, deep sea sediments

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This thesis contains three parts. The first one offers the theoretical basement, where the history of the police from their beginning in the early 19th century to this day is shown. The emphasis however is laid on the last 40 years, which gave birth to a multitude of innovations, such as community, problem-oriented, hot-spots or zero-tolerance policing. Those innovations are described in detail and are critically commented. At the end of this section, I present a scheme, where all the approaches are classified as strategic or methodic innovations, but united under a model called "modern policing". The fact that the innovations are not competitive but rather complementary is the most important finding of this examination. The second part of this work deals with a unique survey about the implementation of four innovations and eight problem- and community-oriented activities in 85 Swiss police forces. This explorative study shows that in the last 15 years the Swiss police forces have increasingly adopted innovative approaches. The most frequent innovation is community policing, which has been implemented all over the country. Due to the results, we can also assume that the implementation of the innovations is mostly substantial and profound. However, particularly in the area of problem-solving there is still a need for improvements. The third section consists of a scientific evaluation of a temporary special unit of the municipal police Zurich, which, during nine months, fought against public drug dealing and illegal prostitution in a particular neighborhood called Langstrasse. The effects of this hot-spot project were measured with police data, observations and several population surveys. In general, the special unit achieved a positive outcome and helped to defuse the hot-spot. Additionally, a survey conducted within the police department showed that the personal attitude towards the special unit differed widely between the policemen. We found significant differences between both police regions East and West, rank-and-file and higher ranking officers, different ages and the personal connection to the special unit. In fact, the higher the rank, the lower the age, and the closer the relationship, the more positive the officers were towards the unit.

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The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

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La fabrication, la distribution et l'usage de fausses pièces d'identité constituent une menace pour la sécurité autant publique que privée. Ces faux documents représentent en effet un catalyseur pour une multitude de formes de criminalité, des plus anodines aux formes les plus graves et organisées. La dimension, la complexité, la faible visibilité, ainsi que les caractères répétitif et évolutif de la fraude aux documents d'identité appellent des réponses nouvelles qui vont au-delà d'une approche traditionnelle au cas par cas ou de la stratégie du tout technologique dont la perspective historique révèle l'échec. Ces nouvelles réponses passent par un renforcement de la capacité de comprendre les problèmes criminels que posent la fraude aux documents d'identité et les phénomènes qui l'animent. Cette compréhension est tout bonnement nécessaire pour permettre d'imaginer, d'évaluer et de décider les solutions et mesures les plus appropriées. Elle requière de développer les capacités d'analyse et la fonction de renseignement criminel qui fondent en particulier les modèles d'action de sécurité les plus récents, tels que l'intelligence-led policing ou le problem-oriented policing par exemple. Dans ce contexte, le travail doctoral adopte une position originale en postulant que les fausses pièces d'identité se conçoivent utilement comme la trace matérielle ou le vestige résultant de l'activité de fabrication ou d'altération d'un document d'identité menée par les faussaires. Sur la base de ce postulat fondamental, il est avancé que l'exploitation scientifique, méthodique et systématique de ces traces au travers d'un processus de renseignement forensique permet de générer des connaissances phénoménologiques sur les formes de criminalité qui fabriquent, diffusent ou utilisent les fausses pièces d'identité, connaissances qui s'intègrent et se mettent avantageusement au service du renseignement criminel. A l'appui de l'épreuve de cette thèse de départ et de l'étude plus générale du renseignement forensique, le travail doctoral propose des définitions et des modèles. Il décrit des nouvelles méthodes de profilage et initie la constitution d'un catalogue de formes d'analyses. Il recourt également à des expérimentations et des études de cas. Les résultats obtenus démontrent que le traitement systématique de la donnée forensique apporte une contribution utile et pertinente pour le renseignement criminel stratégique, opérationnel et tactique, ou encore la criminologie. Combiné aux informations disponibles par ailleurs, le renseignement forensique produit est susceptible de soutenir l'action de sécurité dans ses dimensions répressive, proactive, préventive et de contrôle. En particulier, les méthodes de profilage des fausses pièces d'identité proposées permettent de révéler des tendances au travers de jeux de données étendus, d'analyser des modus operandi ou d'inférer une communauté ou différence de source. Ces méthodes appuient des moyens de détection et de suivi des séries, des problèmes et des phénomènes criminels qui s'intègrent dans le cadre de la veille opérationnelle. Ils permettent de regrouper par problèmes les cas isolés, de mettre en évidence les formes organisées de criminalité qui méritent le plus d'attention, ou de produire des connaissances robustes et inédites qui offrent une perception plus profonde de la criminalité. Le travail discute également les difficultés associées à la gestion de données et d'informations propres à différents niveaux de généralité, ou les difficultés relatives à l'implémentation du processus de renseignement forensique dans la pratique. Ce travail doctoral porte en premier lieu sur les fausses pièces d'identité et leur traitement par les protagonistes de l'action de sécurité. Au travers d'une démarche inductive, il procède également à une généralisation qui souligne que les observations ci-dessus ne valent pas uniquement pour le traitement systématique des fausses pièces d'identité, mais pour celui de tout type de trace dès lors qu'un profil en est extrait. Il ressort de ces travaux une définition et une compréhension plus transversales de la notion et de la fonction de renseignement forensique. The production, distribution and use of false identity documents constitute a threat to both public and private security. Fraudulent documents are a catalyser for a multitude of crimes, from the most trivial to the most serious and organised forms. The dimension, complexity, low visibility as well as the repetitive and evolving character of the production and use of false identity documents call for new solutions that go beyond the traditional case-by-case approach, or the technology-focused strategy whose failure is revealed by the historic perspective. These new solutions require to strengthen the ability to understand crime phenomena and crime problems posed by false identity documents. Such an understanding is pivotal in order to be able to imagine, evaluate and decide on the most appropriate measures and responses. Therefore, analysis capacities and crime intelligence functions, which found the most recent policing models such as intelligence-led policing or problem-oriented policing for instance, have to be developed. In this context, the doctoral research work adopts an original position by postulating that false identity documents can be usefully perceived as the material remnant resulting from the criminal activity undertook by forgers, namely the manufacture or the modification of identity documents. Based on this fundamental postulate, it is proposed that a scientific, methodical and systematic processing of these traces through a forensic intelligence approach can generate phenomenological knowledge on the forms of crime that produce, distribute and use false identity documents. Such knowledge should integrate and serve advantageously crime intelligence efforts. In support of this original thesis and of a more general study of forensic intelligence, the doctoral work proposes definitions and models. It describes new profiling methods and initiates the construction of a catalogue of analysis forms. It also leverages experimentations and case studies. Results demonstrate that the systematic processing of forensic data usefully and relevantly contributes to strategic, tactical and operational crime intelligence, and also to criminology. Combined with alternative information available, forensic intelligence may support policing in its repressive, proactive, preventive and control activities. In particular, the proposed profiling methods enable to reveal trends among extended datasets, to analyse modus operandi, or to infer that false identity documents have a common or different source. These methods support the detection and follow-up of crime series, crime problems and phenomena and therefore contribute to crime monitoring efforts. They enable to link and regroup by problems cases that were previously viewed as isolated, to highlight organised forms of crime which deserve greatest attention, and to elicit robust and novel knowledge offering a deeper perception of crime. The doctoral research work discusses also difficulties associated with the management of data and information relating to different levels of generality, or difficulties associated with the implementation in practice of the forensic intelligence process. The doctoral work focuses primarily on false identity documents and their treatment by policing stakeholders. However, through an inductive process, it makes a generalisation which underlines that observations do not only apply to false identity documents but to any kind of trace as soon as a profile is extracted. A more transversal definition and understanding of the concept and function of forensic intelligence therefore derives from the doctoral work.

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L'analyse quantitative a été réalisée en cotutelle avec Rémi Boivin et Pierre Tremblay et publiée dans la Revue de Criminologie: Boivin, R., Lamige, C,. Tremblay, P. (2009) La police devrait-elle cibler les taudis malfamés? Criminologie, (42)1, 225-266.

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This thesis describes Optimist, an optimizing compiler for the Concurrent Smalltalk language developed by the Concurrent VLSI Architecture Group. Optimist compiles Concurrent Smalltalk to the assembly language of the Message-Driven Processor (MDP). The compiler includes numerous optimization techniques such as dead code elimination, dataflow analysis, constant folding, move elimination, concurrency analysis, duplicate code merging, tail forwarding, use of register variables, as well as various MDP-specific optimizations in the code generator. The MDP presents some unique challenges and opportunities for compilation. Due to the MDP's small memory size, it is critical that the size of the generated code be as small as possible. The MDP is an inherently concurrent processor with efficient mechanisms for sending and receiving messages; the compiler takes advantage of these mechanisms. The MDP's tagged architecture allows very efficient support of object-oriented languages such as Concurrent Smalltalk. The initial goals for the MDP were to have the MDP execute about twenty instructions per method and contain 4096 words of memory. This compiler shows that these goals are too optimistic -- most methods are longer, both in terms of code size and running time. Thus, the memory size of the MDP should be increased.

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In an earlier investigation (Burger et al., 2000) five sediment cores near the Rodrigues Triple Junction in the Indian Ocean were studied applying classical statistical methods (fuzzy c-means clustering, linear mixing model, principal component analysis) for the extraction of endmembers and evaluating the spatial and temporal variation of geochemical signals. Three main factors of sedimentation were expected by the marine geologists: a volcano-genetic, a hydro-hydrothermal and an ultra-basic factor. The display of fuzzy membership values and/or factor scores versus depth provided consistent results for two factors only; the ultra-basic component could not be identified. The reason for this may be that only traditional statistical methods were applied, i.e. the untransformed components were used and the cosine-theta coefficient as similarity measure. During the last decade considerable progress in compositional data analysis was made and many case studies were published using new tools for exploratory analysis of these data. Therefore it makes sense to check if the application of suitable data transformations, reduction of the D-part simplex to two or three factors and visual interpretation of the factor scores would lead to a revision of earlier results and to answers to open questions . In this paper we follow the lines of a paper of R. Tolosana- Delgado et al. (2005) starting with a problem-oriented interpretation of the biplot scattergram, extracting compositional factors, ilr-transformation of the components and visualization of the factor scores in a spatial context: The compositional factors will be plotted versus depth (time) of the core samples in order to facilitate the identification of the expected sources of the sedimentary process. Kew words: compositional data analysis, biplot, deep sea sediments

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Uma linguagem orientada ao problema de projeto estrutural de edifícios e a correspondente estrutura de armazenamento de dados são apresentados, como núcleo principal do sistema PROADE. Objetiva-se assim permitir ao engenheiro estrutural descrever o problema em termos correntes de Engenharia, organizandose os dados recebidos para posterior análise e dimensionamento da estrutura. São discutidos o problema PROADE e os dados correspondentes, seguidos pela descrição das estruturas de armazenamento de dados do sistema. A seguir, define-se a linguagem PROADE e finalmente apresenta-se a organização do sistema PROADE.

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There is a growing interest of the Computer Science education community for including testing concepts on introductory programming courses. Aiming at contributing to this issue, we introduce POPT, a Problem-Oriented Programming and Testing approach for Introductory Programming Courses. POPT main goal is to improve the traditional method of teaching introductory programming that concentrates mainly on implementation and neglects testing. POPT extends POP (Problem Oriented Programing) methodology proposed on the PhD Thesis of Andrea Mendonça (UFCG). In both methodologies POPT and POP, students skills in dealing with ill-defined problems must be developed since the first programming courses. In POPT however, students are stimulated to clarify ill-defined problem specifications, guided by de definition of test cases (in a table-like manner). This paper presents POPT, and TestBoot a tool developed to support the methodology. In order to evaluate the approach a case study and a controlled experiment (which adopted the Latin Square design) were performed. In an Introductory Programming course of Computer Science and Software Engineering Graduation Programs at the Federal University of Rio Grande do Norte, Brazil. The study results have shown that, when compared to a Blind Testing approach, POPT stimulates the implementation of programs of better external quality the first program version submitted by POPT students passed in twice the number of test cases (professor-defined ones) when compared to non-POPT students. Moreover, POPT students submitted fewer program versions and spent more time to submit the first version to the automatic evaluation system, which lead us to think that POPT students are stimulated to think better about the solution they are implementing. The controlled experiment confirmed the influence of the proposed methodology on the quality of the code developed by POPT students