Сравнение методов

	Тестирование методом разбиения на эквивалентные классы	Модель прогнозирования дефектов
Область	Программная инженерия	Программная инженерия
Семейство	Process / pipeline	Process / pipeline
Год появления	1979	2005
Автор метода	Glenford Myers	Thomas Ostrand, Elaine Weyuker, Robert Bell
Тип	partitioning strategy	machine learning model
Основополагающий источник	Myers, G. J. (1979). The Art of Software Testing. John Wiley & Sons.	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.
Другие названия	equivalence partitioning, BVA, boundary value analysis	fault prediction, bug prediction, defect classification
Связанные	4	4
Сводка	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.