CatchML: uma linguagem de domínio específico para modelagem do tratamento de exceção sensível ao contexto

• Ano de defesa: 2013
• Autor(a) principal: Lima, Rafael de
• Orientador(a): Andrade, Rossana Maria de Castro
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Ciência da computação; Tratamento de exceções; Sensibilidade ao contexto; Linguagens de domínio específico; Exception handling; Context awareness
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/18515

In ubiquitous systems, due to the complexity added by the use of contextual information, the application of context aware exception handling (CAEH) techniques has many challenges and in the literature several approaches have been found to define concepts and abstractions useful for modeling CAEH. However, only one of these approaches proposes a method for specification and verification of models in the field of ubiquitous systems, which provides a tool for specifying the CAEH model using a Java API, and also generates an error report to a text file. The disadvantage of this approach is that the designer should strive to understand programming details that are irrelevant to the analysis process of the exceptional behavior of the system. Then, this work aims to propose a domain specific language for modeling CAEH, which provides abstractions and constructors that allow to express relevant concepts and make the task of designing CAEH models simpler and more intuitive. In addition, the language is integrated with the tool mentioned before that allows automatic model verification. The errors generated by the verifier are now shown directly in the source code making their identification and correction easier for the designer. In order to evaluate the language, a case study is conducted to provide evidence of its viability as an alternative to modeling CAEH.