Uma contribuição ao teste baseado em modelo no contexto de aplicações móveis

• Ano de defesa: 2016
• Autor(a) principal: Farto, Guilherme de Cleva
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Cornelio Procopio; Brasil; Programa de Pós-Graduação em Informática; UTFPR
• Palavras-chave em Português: Software de aplicação; Software - Validação; Programas de computador - Testes; Application software; Computer software - Validation; Computer programs - Testing; CNPQ::CIENCIAS EXATAS E DA TERRA; Ciência da Computação
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/3097

Due to the increasing number and diversity of users, new testing approaches are necessary to reduce the presence of faults and ensure better quality in mobile applications. The particularities of this class of software require that traditional testing techniques are revisited and new approaches proposed. The event oriented nature and functionalities of mobile applications demand tests that can be performed automatically. Model-Based Testing (MBT) is a valid and promising approach that favors the use of a defined process, as well as mechanisms and formal techniques for the testing of mobile applications. This dissertation investigates the odoption of MBT along with the modeling technique Event Sequence Graph (ESG) to test Android applications. Initially, we evaluate TBM supported by ESG and the Robotium tool. Based on the results and challenges identified, we propose a specific approach underlying the reuse of test models to (i) reduce the manual effort to the concretization of test cases and to (ii) test different and inherited characteristics of the mobility context. A supporting tool was designed and implemented to automate the proposed approach. Finaly, we conducted an experimental study in an industrial environment to evaluate the proposed approach and tool regarding the effectiveness in reducing the concretization’s efforts, as well as the fault detection capability in Android mobile applications.