Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Particionamento por Equivalência em Testes× | Modelo de Previsão de Defeitos× | |
|---|---|---|
| Área | Engenharia de software | Engenharia de software |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1979 | 2005 |
| Autor original≠ | Glenford Myers | Thomas Ostrand, Elaine Weyuker, Robert Bell |
| Tipo≠ | partitioning strategy | machine learning model |
| Fonte seminal≠ | Myers, G. J. (1979). The Art of Software Testing. John Wiley & Sons. link ↗ | Ostrand, T. J., Weyuker, E. J., & Bell, R. M. (2005). Predicting the location and number of faults in large software systems. IEEE Transactions on Software Engineering, 31(4), 340–355. DOI ↗ |
| Outros nomes | equivalence partitioning, BVA, boundary value analysis | fault prediction, bug prediction, defect classification |
| Relacionados | 4 | 4 |
| Resumo≠ | Equivalence partitioning divides input domains into equivalence classes—sets of inputs expected to behave identically—then selects test cases from each class. Introduced by Myers (1979), this technique reduces test cases while maintaining effectiveness. Boundary value analysis (BVA) complements partitioning by testing values at partition boundaries where failures often occur. | Defect prediction models forecast the likelihood of software faults in code modules using statistical or machine learning approaches. Pioneered by Ostrand, Weyuker, and Bell (2005), these models correlate code metrics (complexity, churn, coupling) with historical defect data to identify high-risk components. Organizations use predictions to allocate testing resources, guide code review, and prioritize refactoring. |
| ScholarGateConjunto de dados ↗ |
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