This paper proposes a dynamic capture-recapture (DCR) model to estimate not only the total number of software faults but also quantitative software reliability from observed data. Compared to conventional static capture-recapture (SCR) model and usual software reliability models (SRMs) in the past literature, the DCR model can handle dynamic behavior of software fault-detection processes and can evaluate quantitative software reliability based on capture-recapture sampling of software fault data. This is regarded as a unified modeling framework of SCR and SRM with the Bayesian estimation. Simulation experiments under some plausible testing scenarios show that our models are superior to SCR and SRMs in terms of estimation accuracy.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
Hiroyuki OKAMURA, Tadashi DOHI, "Software Reliability Modeling Based on Capture-Recapture Sampling" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 7, pp. 1615-1622, July 2009, doi: 10.1587/transfun.E92.A.1615.
Abstract: This paper proposes a dynamic capture-recapture (DCR) model to estimate not only the total number of software faults but also quantitative software reliability from observed data. Compared to conventional static capture-recapture (SCR) model and usual software reliability models (SRMs) in the past literature, the DCR model can handle dynamic behavior of software fault-detection processes and can evaluate quantitative software reliability based on capture-recapture sampling of software fault data. This is regarded as a unified modeling framework of SCR and SRM with the Bayesian estimation. Simulation experiments under some plausible testing scenarios show that our models are superior to SCR and SRMs in terms of estimation accuracy.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1615/_p
Copy
@ARTICLE{e92-a_7_1615,
author={Hiroyuki OKAMURA, Tadashi DOHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Software Reliability Modeling Based on Capture-Recapture Sampling},
year={2009},
volume={E92-A},
number={7},
pages={1615-1622},
abstract={This paper proposes a dynamic capture-recapture (DCR) model to estimate not only the total number of software faults but also quantitative software reliability from observed data. Compared to conventional static capture-recapture (SCR) model and usual software reliability models (SRMs) in the past literature, the DCR model can handle dynamic behavior of software fault-detection processes and can evaluate quantitative software reliability based on capture-recapture sampling of software fault data. This is regarded as a unified modeling framework of SCR and SRM with the Bayesian estimation. Simulation experiments under some plausible testing scenarios show that our models are superior to SCR and SRMs in terms of estimation accuracy.},
keywords={},
doi={10.1587/transfun.E92.A.1615},
ISSN={1745-1337},
month={July},}
Copy
TY - JOUR
TI - Software Reliability Modeling Based on Capture-Recapture Sampling
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1615
EP - 1622
AU - Hiroyuki OKAMURA
AU - Tadashi DOHI
PY - 2009
DO - 10.1587/transfun.E92.A.1615
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2009
AB - This paper proposes a dynamic capture-recapture (DCR) model to estimate not only the total number of software faults but also quantitative software reliability from observed data. Compared to conventional static capture-recapture (SCR) model and usual software reliability models (SRMs) in the past literature, the DCR model can handle dynamic behavior of software fault-detection processes and can evaluate quantitative software reliability based on capture-recapture sampling of software fault data. This is regarded as a unified modeling framework of SCR and SRM with the Bayesian estimation. Simulation experiments under some plausible testing scenarios show that our models are superior to SCR and SRMs in terms of estimation accuracy.
ER -