So sánh phương pháp

	Mô hình độ tin cậy phần mềm	Mô hình dự đoán lỗi
Lĩnh vực	Kỹ thuật phần mềm	Kỹ thuật phần mềm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1979	2005
Người khởi xướng	Alok Goel and Kazuhira Okumoto	Thomas Ostrand, Elaine Weyuker, Robert Bell
Loại	stochastic model	machine learning model
Công trình gốc	Goel, A. L., & Okumoto, K. (1979). Time-dependent error-detection rate model for software reliability and other performance measures. IEEE Transactions on Reliability, 28(3), 206–211.	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.
Tên gọi khác	reliability growth model, failure rate prediction, SRGM	fault prediction, bug prediction, defect classification
Liên quan	4	4
Tóm tắt	Software reliability models predict the behavior of failure rates during testing and operation, estimating when software achieves required reliability targets. Introduced by Goel and Okumoto (1979), these stochastic models capture how defect discovery declines as testing progresses. Organizations use reliability models to forecast release readiness, estimate testing duration, and validate quality achievement.	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.