Submitted by Lucas Nunes Pellegrino (lucasnpellegrino@gmail.com) on 2018-06-29T22:12:52Z No. of bitstreams: 1 Reconhecimento e legitimação jurisprudencial do Goodwill no Brasil - uma interpretação a partir da teoria econômica de John R. Commons.pdf: 2302092 bytes, checksum: ed7addaefd4de0d7707280ee216db0f9 (MD5) / Approved for entry into archive by Aline Aparecida Matias null (alinematias@fclar.unesp.br) on 2018-07-03T11:34:40Z (GMT) No. of bitstreams: 1 pellegrino_ln_me_arafcl.pdf: 2302092 bytes, checksum: ed7addaefd4de0d7707280ee216db0f9 (MD5) / Made available in DSpace on 2018-07-03T11:34:40Z (GMT). No. of bitstreams: 1 pellegrino_ln_me_arafcl.pdf: 2302092 bytes, checksum: ed7addaefd4de0d7707280ee216db0f9 (MD5) Previous issue date: 2018-04-23 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / O texto objetivou analisar – de uma perspectiva do institucionalismo original – o processo de emergência, reconhecimento e legitimação jurídica/legal das formas de riqueza capitalistas intangíveis e incorpóreas em um país de capitalismo periférico, o Brasil. Claramente inspirado nas reflexões do economista institucionalista norte americano John R. Commons sobre a riqueza incorpórea e intangível, em especial o goodwill, e no papel do sistema legal na sua institucionalização, o texto toma a presença dessas formas de riqueza como sendo a expressão de maturidade do capitalismo monopolista, dada a imensa possibilidade que oferecem para a valorização do capital. O texto mostrou que no Brasil, à diferença dos EUA e outros países de capitalismo central, a presença de tais formas de riqueza foi inicialmente tardia (posterior aos anos 1920), e de certo modo limitada (circunscrita majoritariamente às atividades imobiliárias). Com a própria evolução e consolidação do capitalismo brasileiro, quando as novas formas de riqueza capitalistas foram ganhando peso e destaque, o sistema jurídico progressivamente foi se estruturando e se especializando para analisar e decidir sobre os conflitos originados da própria evolução do capitalismo brasileiro, em especial aqueles que envolveram o goodwill. Deste modo, buscamos compreender como tem sido o processo de regulamentação do goodwill pelo Estado na evolução do capitalismo e das instituições no Brasil, de modo a identificar e analisar casos jurídicos que possivelmente fundamentaram a lei, assim como as possíveis mudanças de entendimentos dos Tribunais de Cúpula (Supremo Tribunal Federal e Superior Tribunal de Justiça) daquilo que é considerado como prática “razoável” no que diz respeito ao goodwill, buscando delimitar os limites de ação dos indivíduos envolvidos e identificar as variáveis responsáveis por tais mudanças, sob a ótica da teoria de Commons. Vemos que parece haver consolidação incremental de jurisprudências acerca do goodwill ao longo das décadas (legitimando-o cada vez mais), principalmente em função do pequeno número de casos que subiram à terceira instância para decisão/delimitação das regras operacionais das transações que possam envolver esse ativo. / The text aimed to analyze - from a perspective of the original institutionalism - the process of emergence, recognition and law / legal legitimation of intangible and incorporeal capitalist wealth forms in a country of peripheral capitalism, Brazil. Clearly inspired by the reflections of North American institutional economist John R. Commons on incoporeal and intangible wealth, especially goodwill, and on the role of the legal system in its institutionalization, the text takes the presence of these forms of wealth as the expression of maturity of monopoly capitalism, given the immense possibility they offer for the valorization of capital. The text showed that in Brazil, unlike the USA and other countries of central capitalism, the presence of such forms of wealth was initially late (after the 1920s), and to a certain extent limited (mostly limited to real estate activities). With the evolution and consolidation of Brazilian capitalism itself, when the new forms of capitalist wealth gained weight and prominence, the legal system gradually became structured and specialized to analyze and decide on the conflicts originated from the very evolution of Brazilian capitalism, in particular those that involved goodwill. In this way, we seek to understand how the process of regulation of goodwill by the State in the evolution of capitalism and institutions in Brazil has been, in order to identify and analyze legal cases that possibly based the law, as well as the possible changes of understandings of the Courts of (Supreme Court and Superior Court of Justice) of what is considered a "reasonable" practice with respect to goodwill, seeking to delimit the limits of action of the individuals involved and to identify the variables responsible for such changes, from the point of view of the theory of Commons. We see that there seems to be an incremental consolidation of jurisprudence over goodwill over the decades (legitimating it more and more), mainly due to the small number of cases that have risen to the third instance for decision / delimitation of the operational rules of the transactions that may involve this active. / 148129/2016-1.

L'Ingénierie Dirigée par les Modèles (IDM) est un domaine de recherche en pleine émergence qui considère les modèles comme des éléments de base. Chaque modèle est conforme à un autre modèle, appelé son méta-modèle, qui définit sa syntaxe abstraite et ses concepts. Dans un processus IDM, différents types de modèles sont manipulés par des transformations de modèles. Une transformation génère un modèle dans un langage cible à partir d'un modèle dans un langage source. Pour concevoir une transformation, les développeurs doivent avoir une bonne connaissance des méta-modèles concernés ainsi que des langages de transformation, ce qui rend cette tâche difficile. Dans cette thèse, nous proposons d'assister l'écriture des transformations et plus généralement de comprendre comment une transformation opère. Nous adhérons à l'approche de transformation de modèles par l'exemple qui propose de créer une transformation de modèles à partir d'exemples de transformation. Cela permet d'utiliser la syntaxe concrète définie pour les méta-modèles, et cela évite donc de requérir que les développeurs aient une bonne maîtrise des méta-modèles utilisés. Dans ce contexte, nous proposons deux contributions. La première consiste à définir une méthode pour générer des règles de transformation opérationnelles à partir d'exemples. Nous nous basons sur une approche qui utilise l'Analyse Relationnelle de Concepts (ARC) comme technique d'apprentissage pour obtenir des patrons de transformation à partir d'un appariement de type 1-1 entre les modèles. Nous développons une technique pour extraire des règles de transformation opérationnelles à partir de ces patrons. Ensuite, nous utilisons le langage et le moteur de règles JESS pour exécuter ces règles. Nous étudions aussi comment mieux apprendre des règles de transformations à partir d'exemples, en utilisant séparément chaque exemple ou en réunissant tous les exemples. La deuxième contribution consiste à récupérer les traces de transformation à partir d'exemples de transformation. Ces traces peuvent être utilisées par exemple pour localiser des erreurs durant l'exécution des programmes de transformation ou vérifier la couverture de tous les modèles d'entrée par une transformation. Dans notre contexte, nous supposons que ces traces vont servir pour un futur apprentissage des règles de transformation. Nous traitons tout d'abord le problème de récupération des traces avec des exemples provenant d'un programme de transformation. Nous proposons une approche basée sur une méta-heuristique multi-objectifs pour générer des traces sous forme d'appariement de type n-m entre des éléments de modèles. La fonction objectif s'appuie sur une similarité lexicale et structurelle entre ces éléments. Une extension de cette méthode est proposée pour traiter le problème plus général de l'appariement entre modèles. / Model Driven Engineering (MDE) considers models as first class artifacts. Each model conforms to another model, called its metamodel which defines its abstract syntax and its semantics.Various kinds of models are handled successively in an MDE development cycle. They are manipulated using, among others, programs called model transformations. A transformation takes as input a model in a source language and produces a model in a target language. The developers of a transformation must have a strong knowledge about the source and target metamodels which are involved and about the model transformation language. This makes the writing of the model transformation difficult.In this thesis, we address the problem of assisting the writing of a model transformation and more generally of understanding how a transformation operates.We adhere to the Model Transformation By example (MTBE) approach, which proposes to create a model transformation using examples of transformation. MTBE allows us to use the concrete syntaxes defined for the metamodels. Hence, the developers do not need in-depth knowledge about the metamodels. In this context, our thesis proposes two contributions.As a first contribution, we define a method to generate operational transformation rules from transformation examples. We extend a previous approach which uses Relational Concept Analysis as a learning technique for obtaining transformation patterns from 1-1 mapping between models. We develop a technique for extracting relevant transformation rules from these transformation patterns and we use JESS language and engine to make the rules executable. We also study how we better learn transformation rules from examples, using transformation examples separately or by gathering all the examples.The second contribution consists in recovering transformation traces from transformation examples. This trace recovery is useful for several purposes as locating bugs during the execution of transformation programs, or checking the coverage of all input models by a transformation. In our context, we expect also that this trace will provide data for a future model transformation learning technique. We first address the trace recovery problem with examples coming from a transformation program. We propose an approach, based on a multi-objective meta-heuristic, to generate the textit{many-to-many} mapping between model constructs which correspond to a trace. The fitness functions rely on the lexical and structure similarity between the constructs. We also refine the approach to apply it to the more general problem of model matching.