The Estimation of Parameters of the Hypergeometric Distribution and Its Application to the Software Reliability Growth Model

IEEE Transactions on Software Engineering

Volumn 17, Issue 5, 1991, Pages 483-489

  Ohba, Yoshihiro ^a   Jacoby, Raymond ^a   Yamano, Hisashi ^a   Ohba, Morio ^a,b  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

^b TOYOTA MOTOR CORPORATION   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING - PROGRAM DEBUGGING; MATHEMATICAL TECHNIQUES - LEAST SQUARES APPROXIMATIONS; PROBABILITY;

HYPERGEOMETRIC DISTRIBUTION; SOFTWARE RELIABILITY GROWTH MODEL;

COMPUTER SOFTWARE;

EID: 0026157799     PISSN: 00985589     EISSN: None     Source Type: Journal    
DOI: 10.1109/32.90450     Document Type: Article

References (9)

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2. S. Yamada, M. Ohba, and S. Osaki, “S-shaped software reliability growth models and their applications,” IEEE Trans. Rel., Vol. R-33, pp. 289-292, Oct. 1984.
3. J. D. Musa and K. Okumoto, “A logarithmic poisson execution time model for software reliability measurement,” in Proc. 7th Int. Conf. Software Engineering, 1984, pp. 230-238.
4. G. J. Schick and R. W. Wolverton, “An analysis of competing software reliability models,” IEEE Trans. Software Eng., Vol. SE-4, pp. 104-120, Mar. 1978.
5. J. D. Musa, A. lanino, and K. Okumoto, Software Reliability—Measurement Prediction, Application. New York: McGraw-Hill, 1987.
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7. Y. Tohma, R. Jacoby, Y. Murata, and M. Yamamoto, “Hyper-geometric distribution model to estimate the number of residual software faults,” in Proc. COMPSAC-89, Orlando, FL, Sept. 1989, pp. 610-617.
8. J. S. Milton and J. C. Arnold, Probability and Statistics in the Electrical Engineering and Computer Sciences. New York: McGraw-Hill, 1986. pp. 64-65.
9. R. Jacoby and Y. Tohma, “The hyper-geometric distribution software reliability growth model (HGDM): Precise formulation and applicability,” in Proc. COMPSAC-90, Sept. 1990.