IEEE Transactions on Reliability, VOL. 50, NO. 2, June 2001. Summary and Conclusions—Existing software reliability-growth models often over-estimate the reliability of a given program. Empirical studies suggest that the over-estimations exist because the models do not account for the nature of the testing. Every testing technique has a limit to its ability to reveal faults in a...
Paper - 12 p
This paper reviews recent developments in Bayesian software reliability
modeling. In so doing, emphasis is given to two models which can incorporate the
case of reliability deterioration due to potential introduction of new bugs to the software
during the development phase. Since the introduction of bugs is an unobservable
process, latent variables are introduced...
Article Software reliability models are very useful to estimate the probability of the software fail along the time. Several different models have been proposed to predict the software reliability growth (SRGM); however, none of them has proven to perform well considering different project characteristics. The ability to predict the number of faults in the software during...
Paper. — PWASET. — 2007. — Volume 26. — p. 720-725. The Moranda’s Geometric de-Eutrophication model alleviates some of the objections to the Jelinski Moranda model for software failures. In Moranda Geometric de-Eutrophication model, N(t) is defined as the number of faults detected in the time interval (0, t]. In this paper, N(t) is studied as a pure birth stochastic process,...
Paper, Florida Institute of Technology, 2000 IEEE, 7 p.
The notions of time and the operational profile incorporated into software reliability are incomplete.
Reliability should be redefined as a function of application complexity, test effectiveness, and
operating environment.
Journal of Software. — 2012. — Vol. 7. — No. 6. — P. 1296–1306. Software reliability deals with the probability that software will not cause the failure of a system for a specified time under a specified condition. The probability is a function of the inputs to and use of the system as well as a function of the existing faults in the software. The inputs to the system determine...
Paper, Duke University, 8 p.
Finite failure NHPP models proposed in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault, and are inadequate to describe the failure process underlying certain failure data sets. In this paper, we propose the loglogistic
reliability growth model, which can capture the...
Article. — Dept. of Electrical and Computer Engg, Center for Advanced Comp. & Comm. — NC.: Duke University, 2024. — 21 p. Prevalent black-box based approaches to software reliability modeling are inappropriate for the reliability assessment of modern component-based systems. The existing Markovian and semi-Markovian methods to predict the reliability and performance of such...
Комментарии