MDAONTO: um processo MDA de desenvolvimento de software com foco em ontologias

• Ano de defesa: 2009
• Autor(a) principal: Rego, Elisangela Simões
• Orientador(a): Salvador, Laís do Nascimento
• Banca de defesa: Falbo, Ricardo de Almeida, Chavez, Christina Von Flach Garcia
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso embargado
• Idioma: por
• Instituição de defesa: Universidade Salvador
• Programa de Pós-Graduação: Programa de Pós-Graduação em Sistemas e Computação
• Departamento: Sistemas e Computação
• País: BR
• Palavras-chave em Português: Processo de desenvolvimento de software; Ontologia; Padrão MDA.
• Palavras-chave em Inglês: Software development process; Ontology; MDA standard
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://teste.tede.unifacs.br:8080/tede/handle/tede/266

Model Driven Architecture (MDA) software development standard follows a set of guidelines, which can promote substantial benefits in design of a new system. In this sense, using tools of this paradigm and the automated generation code, in several programming languages, it is possible to augment productivity, lower cost and increase quality. Despite these benefits, the use of these concepts is little explored, and the lack of an appropriate and concise process makes it more difficult. This brings to industry and academy the idea of defining models for software artifacts, defining transformations between them and providing tools to automate these transformations.Allied to MDA standard, this work proposes the use of ontologies aiming to acquire knowledge in a particular domain, serving as the basis for upholding the proposed process, which was called MDAONTO. Thus, several models of software are developed under a particular point of view using ontologies and this process is up to the code generation.Some advantages offered by the proposed process include the specification of well designed models in all levels of process development, repetitive and susceptible to errors tasks automation, knowledge acquisition in a more productive way, consensual knowledge sharing, spread of knowledge among stakeholders, support for traceability between artifacts, risks reduction, among others.