Detalhes bibliográficos
| Ano de defesa: |
2016 |
| Autor(a) principal: |
Machado, Bruno Nunes
 |
| Orientador(a): |
Rodrigues, Cássio Leonardo
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| Banca de defesa: |
Rodrigues, Cássio Leonardo,
Camilo Junior, Celso Gonçalves,
Leitão Junior, Plínio de Sá,
Freitas, Eduardo Noronha de Andrade |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Programa de Pós-graduação em Ciência da Computação (INF)
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| Departamento: |
Instituto de Informática - INF (RG)
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| País: |
Brasil
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| 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/6345
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Resumo: |
The software testing is an important component of software development life cycle, that directly affects quality of software products. Some problems in software testing phase can not be optimized only with traditional Software Engineering techniques. It is possible to do the mathematical modelling of those problems in an attempt to optimize them through the search techniques. However, the use of optimization approaches tend to incorporate more and more activities decisions to the tester, making more complex test activity. So, in order that optimization techniques are in fact employed at the Software Test solutions, the ability to abstract the details of optimization are required. Thus, the objective of this research is to propose a framework for search-based software testing (SBST). The proposed framework works as a top-level layer over generic optimization frameworks and testing software tools, it's target is supporting software testers that are not able to use optimization frameworks during a testing activity due to short deadlines and limited resources or skills, also supporting expert or beginners users from optimization area that need or want to compare their metaheuristics with ones from literature and offered by the proposed framework. The framework was evaluated in a case study of software testing scenario. This scenario was modeled as test case selection problem in which experiments were executed with different metaheuristics and benchmarks offered by framework. The results indicate it's capability to support the SBST area with emphasis on the test cases selection. The framework was evaluated and compared with other SBST frameworks in terms of quality metrics, that indicated its extensibility and flexibility as framework. |
