A discrete-time software reliability-growth model and its application for predicting the number of errors encountered during program testing

• Autorzy: Worwa K.
• Języki publikacji: EN

Abstrakty

EN

An approach to evaluate the number of errors encountered during the program testing process is proposed in the paper. Considerations are based on some program reliability-growth model, constructed for an assumed scheme of the program testing process. In this model the program under testing is characterized by means of the so-called characteristic matrix and the program testing process is determined by means of so-called testing strategy. The formula for determining the mean value of the predicted number of errors encountered during the program testing is obtained. This formula can be used if the characteristic matrix and the testing strategy are known. Formulae for evaluating this value when the program characteristic matrix is not known are also proposed.

Słowa kluczowe

EN

software testing; software reliability; software reliability-growth model

PL

testowanie oprogramowania; niezawodność oprogramowania

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2005
• Tom: Vol. 34, no 2
• Strony: 589--606
• Opis fizyczny: Bibliogr. 26 poz.

Twórcy

autor

Worwa K.

• Faculty of Cybernetics, Military Technical University, 00-908 Warszawa, Kaliskiego 2, Poland,

Bibliografia

• Basu, S. and Ebrahimi, N. (2003) Bayesian software reliability models based on martingale processes. Technometrics 2, 150–158.
• Cai, K.Y. (2000) Towards a conceptual framework of software run reliability modeling. Information Science 126, 137–163.
• Chen, M., Mathur, A.P. and Rego, V. (1995) Effect of testing techniques on software reliability estimates obtained using a time-domain model. IEEE Transactions on Reliability 44 (1), 97–103.
• Chen, T.Y. and Yu, Y.T. (1994) On the relationship between partition and random testing. IEEE Transactions on Software Engineering 20 (12), 977–980.
• Chen, T.Y. and Yu, Y.T. (1996) On the expected number of failures detected by subdomain testing and random testing. IEEE Transactions on Software Engineering 22 (2), 109–119.
• Cobb, R.H. and Mills, H.D. (1990) Engineering software under statistical quality control. IEEE Software 16, 44–54.
• Csenki, A. (1990) Bayes predictive analysis of a fundamental software reliability model. IEEE Transactions on Software Engineering 39 (2), 177–183.
• Gaudoin, O. (1999) Software reliability models with two debugging rates. International Journal of Reliability 1, 31–42.
• Hayakawa, Y. and Telfar, G. (2000) Mixed poisson-type processes with application in software reliability. Mathematical and Computer Modelling 31, 151–156.
• Jelinski, Z. and Moranda, P.B. (1972) Software Reliability Research. Statistical Computer Performance Evaluation. Academic Press, New York.
• Jeske, D.R. and Pham, H. (2001) On the maximum likelihood estimates for the Goel-Okumoto software reliability model. The American Statistician 3, 219–222.
• Kit, E. (1995) Software testing in the real world. ACM Press Books.
• Musa, J.D., Iannino, A. and Okumoto, K. (1987) Software Reliability. Measurement, Prediction, Application. McGraw-Hill, Inc.
• Sawada, K. and Sandoh, H. (2000) Continuous model for software reliability demonstration testing considering damage size of software failures. Mathematical and Computer Modelling 31, 321–326.
• Schick, G.J. and Wolverton, R.W. (1978) An Analysis of Competing Software Reliability Models. IEEE Transactions on Software Engineering SE-4 (2), 104–120.
• Shooman, M.L. (1972) Probabilistic Models for Software Reliability Prediction. Statistical Computer Performance Evaluation. Academic Press, New York.
• Thayer, T.A., Lipov, M. and Nelson, E.C. (1978) Software Reliability. North-Holland Publishing Company. Amsterdam.
• Tokuno, K. and Yamada, S. (2000) An imperfect debugging model with two types of hazard rates for software reliability measurement and assessment. Mathematical and Computer Modelling 31, 343–352.
• Trachtenberg, M. (1990) A general theory of software reliability modeling. IEEE Transactions on Software Engineering 39 (1), 92–96.
• Whittaker, J.A., Rekab, K. and Thomason, M.G (2000) AMarkov chain model for predicting the reliability of multi-build software. Information and Software Technology 42, 889–894.
• Worwa, K. (1995a) Estimation of the programtesting strategy. Part 1—The same errors can be encountered. Cybernetics Research and Development 3-4, 155–173.
• Worwa, K. (1995b) Estimation of the program testing strategy. Part 2 — The same errors can not be encountered. Cybernetics Research and Development 3-4, 175–188.
• Worwa, K. (2000) Modelling and estimation of software reliability growth during the testing process. Publishers of Warsaw Technical University, Warsaw (in Polish).
• Yamada, S. and Fujiwara, T. (2001) Testing-domain dependent software reliability growth models and their comparisons of goodness-of-fit. International Journal of Reliability 3, 205–218.
• Yang, M.C. and Chao, A. (1995) Reliability-estimation & stopping-rules for software testing, based on repeated appearances of bugs. IEEE Transactions on Reliability 44 (2), 315–321.
• Zhang, X. and Pham, H. (2000) Comparisons of nonhomogeneous Poisson process software reliability models and its applications. International Journal of Systems Science 9, 1115–1123.