Made available in DSpace on 2014-06-12T15:50:47Z (GMT). No. of bitstreams: 2 arquivo1988_1.pdf: 1433897 bytes, checksum: 2bd67eddaeadba13aa380ec5c913b7e0 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2008 / Uma das propostas da Web Semântica é fornecer uma grande diversidade de serviços de diferentes domínios na Web. Estes serviços são, em sua maioria, colaborativos, cujas tarefas se baseiam em processos de tomada de decisão. Estas decisões, por sua vez, serão mais bem embasadas se considerarem a maior quantidade possível de informação relacionada às tarefas em execução. Neste sentido, este cenário encoraja o desenvolvimento de técnicas e ferramentas orientadas para a integração de informação, procurando soluções para a heterogeneidade das fontes de dados. A arquitetura baseada em mediação, utilizada no desenvolvimento de sistemas de integração de informações tem como objetivo isolar o usuário das fontes de dados distribuídas utilizando uma camada intermediária de software chamada de mediador. O mediador, em um sistema de integração de informações, utiliza um esquema global para a execução das consultas do usuário que são reformuladas em sub-consultas de acordo com os esquemas locais das fontes de dados. Neste caso, um processo de integração de esquemas gera o esquema global (esquema de mediação) como resultado da integração dos esquemas individuais das fontes de dados. O problema maior em integração de esquemas é a heterogeneidade das fontes de dados locais. Neste sentido, a resolução semântica é primordial. A utilização de métodos puramente estruturais e sintáticos na integração de esquemas é pouco eficaz se antes não houver a identificação do real significado dos elementos dos esquemas. Um processo de integração de esquemas tem como resultado um esquema global integrado e um conjunto de mapeamentos inter-esquema e usualmente, compreende algumas etapas básicas como: pré-integração, comparação, mapeamento e unificação de esquemas e geração do esquema de mediação. Em integração de esquemas, resolução de nomes é o processo que determina a qual entidade do mundo real um dado elemento de esquema se refere, levando em consideração um conjunto de informações semânticas disponíveis. A informação semântica necessária para resolução de nomes, em geral, é obtida de vocabulários genéricos e/ou específicos de um determinado domínio de conhecimento. Nomes de elementos podem apresentar significados diferentes dependendo do contexto semântico ao qual eles estão relacionados. Assim, o uso de informação contextual, além da de domínio, pode trazer uma maior precisão na interpretação dos elementos permitindo modificar o seu significado de acordo com um dado contexto. Este trabalho propõe uma abordagem de resolução de nomes baseada em contexto para integração de esquemas. Um de seus pontos fortes é a utilização e modelagem da informação contextual necessária à resolução de nomes em diferentes etapas do processo de integração de esquemas. A informação contextual está modelada utilizando uma ontologia, o que favorece a utilização de mecanismos de inferência, compartilhamento e reuso da informação. Além disto, este trabalho propõe um processo de integração de esquemas simples e extensível de forma que seu desenvolvimento se concentrasse principalmente nos requisitos relacionados à resolução de nomes. Este processo foi desenvolvido para um sistema de integração de informações baseado em mediação, que adota a abordagem GAV e XML como modelo comum para intercâmbio de dados e integração de fontes de dados na Web

This thesis deals with fact extraction, which analyzes source code (and sometimes related artifacts) to produce extracted facts about the code. These facts may, for example, record where in the code variables are declared and where they are used, as well as related information. These extracted facts are typically used in software reverse engineering to reconstruct the design of the program. This thesis has two main parts, each of which deals with a formal approach to fact extraction. Part 1 of the thesis deals with the question: How can we demonstrate that a fact extractor actually does its job? That is, does the extractor produce the facts that it is supposed to produce? This thesis builds on the concept of semantic completeness of a fact extractor, as defined by Tom Dean et al, and further defines source, syntax and compiler completeness. One of the contributions of this thesis is to show that in particular important cases (when the extractor is deterministic and its front end is idempotent), there is an efficient algorithm to determine if the extractor is compiler complete. This result is surprising, considering that in general it is undecidable if two programs are semantically equivalent, and it would seem that source code and its corresponding extracted facts are each essentially programs that are to be proved to be equivalent or at least sufficiently similar. The larger part of the thesis, Part 2, presents Algebraic Refers-to Analysis (ARA), a new approach to fact extraction with emphasis on the Refers-to relation. ARA provides a framework for specifying fact extraction, based on a three-step pipeline: (1) basic (lexical and syntactic) extraction, (2) a normalization step and (3) a binding step. For practical programming languages, these three steps are repeated, in stages and phases, until the Refers-to relation is computed. During the writing of this thesis, ARA pipelines for C, Java, C++, Fortran, Pascal and Ada have been designed. A prototype fact extractor for the C language has been created. Validating ARA means to demonstrate that ARA pipelines satisfy the programming language standards such as ISO C++ standard. In other words, we show that ARA phases (stages and formulas) are correctly transcribed from the rules in the language standard. Comparing with the existing approaches such as Attribute Grammar, ARA has the following advantages. First, ARA formulas are concise, elegant and more importantly, insightful. As a result, we have some interesting discovery about the programming languages. Second, ARA is validated based on set theory and relational algebra, which is more reliable than exhaustive testing. Finally, ARA formulas are supported by existing software tools such as database management systems and relational calculators. Overall, the contributions of this thesis include 1) the invention of the concept of hierarchy of completeness and the automatic testing of completeness, 2) the use of the relational data model in fact extraction, 3) the invention of Algebraic Refers-to Relation Analysis (ARA) and 4) the discovery of some interesting facts of programming languages.

This thesis deals with fact extraction, which analyzes source code (and sometimes related artifacts) to produce extracted facts about the code. These facts may, for example, record where in the code variables are declared and where they are used, as well as related information. These extracted facts are typically used in software reverse engineering to reconstruct the design of the program. This thesis has two main parts, each of which deals with a formal approach to fact extraction. Part 1 of the thesis deals with the question: How can we demonstrate that a fact extractor actually does its job? That is, does the extractor produce the facts that it is supposed to produce? This thesis builds on the concept of semantic completeness of a fact extractor, as defined by Tom Dean et al, and further defines source, syntax and compiler completeness. One of the contributions of this thesis is to show that in particular important cases (when the extractor is deterministic and its front end is idempotent), there is an efficient algorithm to determine if the extractor is compiler complete. This result is surprising, considering that in general it is undecidable if two programs are semantically equivalent, and it would seem that source code and its corresponding extracted facts are each essentially programs that are to be proved to be equivalent or at least sufficiently similar. The larger part of the thesis, Part 2, presents Algebraic Refers-to Analysis (ARA), a new approach to fact extraction with emphasis on the Refers-to relation. ARA provides a framework for specifying fact extraction, based on a three-step pipeline: (1) basic (lexical and syntactic) extraction, (2) a normalization step and (3) a binding step. For practical programming languages, these three steps are repeated, in stages and phases, until the Refers-to relation is computed. During the writing of this thesis, ARA pipelines for C, Java, C++, Fortran, Pascal and Ada have been designed. A prototype fact extractor for the C language has been created. Validating ARA means to demonstrate that ARA pipelines satisfy the programming language standards such as ISO C++ standard. In other words, we show that ARA phases (stages and formulas) are correctly transcribed from the rules in the language standard. Comparing with the existing approaches such as Attribute Grammar, ARA has the following advantages. First, ARA formulas are concise, elegant and more importantly, insightful. As a result, we have some interesting discovery about the programming languages. Second, ARA is validated based on set theory and relational algebra, which is more reliable than exhaustive testing. Finally, ARA formulas are supported by existing software tools such as database management systems and relational calculators. Overall, the contributions of this thesis include 1) the invention of the concept of hierarchy of completeness and the automatic testing of completeness, 2) the use of the relational data model in fact extraction, 3) the invention of Algebraic Refers-to Relation Analysis (ARA) and 4) the discovery of some interesting facts of programming languages.

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The goal of the Master thesis on the topic of the Client application of DNS protocol with graphical interface for teaching purposes is to create a program with the features of sending, receiving DNS, MDNS and LLMNR protocols with optional parameters. Additionally, compare the created application with available tools such as Nslookup, Dig and create examples of application for teaching.