Sistema de recomendação de frameworks para desenvolvimento multiplataforma em dispositivos móveis

• Ano de defesa: 2018
• Autor(a) principal: Santos, Denisson Santana dos
• Orientador(a): Costa Neto, Alberto
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Programa de Pós-Graduação: Pós-Graduação em Ciência da Computação
• Palavras-chave em Português: Framework; Recomendação; Multiplataforma; Dispositivos móveis
• Palavras-chave em Inglês: Recommendation; Cross-platform; Mobile devices
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://ri.ufs.br/jspui/handle/riufs/10685

The number and variety of mobile devices have increased so much nowadays, as well as the number of platforms on the market, from different manufacturers, operating systems and programming languages. To keep up with this increase, developers, aimming to make their applications available to the largest number of platforms, are increasingly seeking to optimize how to develop mobile applications. Create the same specific application for each platform demands greater financial, time and labor investment. In order to reduce these problems, mobile development frameworks for multiplatforms have emerged, making possible to create multiplatform applications from the same source code. However, a new issue arises for the developer - the plurality and diversity of these frameworks, each one with objectives and characteristics that sometimes make them closer and in other cases farther. In addition, there is a demand for multi-purpose applications and work teams with different training profiles. For these reasons, choosing a framework is not trivial. In order to help developers and companies of mobile software development, this paper presents a research proposal that consists of developing an approach that indicates which multi-platform application development framework is most suitable for a given project. In addition, the above mentioned approach was implemented through a knowledge-based recommendation system that considered the critical factors of a given project informed by the developer.