Classifying metrics for assessing object-oriented software maintainability: a family of metrics’ catalogs

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: SARAIVA, Juliana de Albuquerque Gonçalves
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade Federal de Pernambuco
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufpe.br/handle/123456789/12152
Resumo: Currently, Object-Oriented Programming (OOP) is one of the most used paradigms. Complementarily, the software maintainability is considered a software attribute that plays an important role in quality level. In this context, the Object-Oriented Software Maintainability (OOSM) has been studied through years, and many researchers have proposed a large number of metrics to measure it. As a consequence of the number and diversity of metrics, beyond the no standardization in metrics definition and naming, the decision-making process about which metrics can be adopted in experiments on OOSM, or even their using in software companies is a difficult task. Therefore, a systematic mapping study was conducted in order to find which metrics are used as indicators in OOSM assessments. There was an initial selection of 5175 primary studies and 138 were selected, resulting in 568 metrics found. Analyzing the 568 metrics, inconsistencies in metrics’ naming were found because there were metrics with the same names but different meanings (8 cases involving 17 metrics) and also, there were metrics with different names, however with similar meanings (32 cases involving 214 metrics). Moreover, a metrics’ categorization has been proposed to facilitate decision-making process about which ones have to be adopted, and 7 categories and 17 subcategories were identified. These categories represent the evaluation scenarios where OOSM metrics should be used. Additionally, a metrics’ web portal was developed to provide information about the metrics collected in this research, and to generate metrics’ catalogs according to the context of their adoption. This portal can also be systematically fed by other researchers that work with OOSM metrics, making the results of this work the first steps towards metrics’ standardization, and the improvement of the metrics’ validation. Finally, a quasi-experiment was conducted to check the coverage index of the catalogs generated using our approach over the catalogs suggested by experts. 90% of coverage was obtained and this result was confirmed with 99% of confidential level using the Wilcoxon Test. Complementarily, a survey was conducted to check the experts’ opinion about the catalog generated by the portal when they were compared by the catalogs suggested by the experts. Thus, the coverage evaluation can be the first evidences of the usefulness of the proposed approach for metrics’ choice in OOSM evaluation.