Detalhes bibliográficos
| Ano de defesa: |
2014 |
| Autor(a) principal: |
Mendonça, Vinícius Rafael Lobo de
 |
| Orientador(a): |
Vincenzi, Auri Marcelo Rizzo
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| Banca de defesa: |
Vincenzi, Auri Marcelo Rizzo,
Rodrigues, Cássio Leonardo,
Delamaro, Márcio Eduardo |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
|
| Programa de Pós-Graduação: |
Programa de Pós-graduação em Ciência da Computação (INF)
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| Departamento: |
Instituto de Informática - INF (RG)
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/4338
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Resumo: |
Recommendation systems try to guide the user carrying out a task providing him with useful information about it. Considering the context of software development, programs are ever increasing, making it difficult to carry out a detailed verification of warnings generated by automatic static analyzers. In this work, we propose a recommendation system, called WarningsFIX, which aims at helping developers on handling the high number of warnings reported by automatic static analyzers. The back end of this system is composed of seven open-source static analysis tools collecting data, which subsequently are used for visualizing information through TreeMaps. The intention is to combine the outcomes of different static analyzers such that WarningsFIX recommends the analysis of warnings with highest chance to be a true positive. Therefore, the information related to warnings are displayed in four levels of detail: program, package, class, and line. The nodes may be classified in the first three levels: amount of warnings, number of tools and suspicions rate. An exploratory study was carried out and the limitations, advantages and disadvantages of the proposed approach were discussed. |
