Detection and correction process modeling considering the time dependency

Y. P. Wu; Q. P. Hu; M. Xie; S. H. Ng

doi:10.1109/PRDC.2006.27

Detection and correction process modeling considering the time dependency

Y. P. Wu, Q. P. Hu, M. Xie, S. H. Ng

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

Most of the models for software reliability analysis are based on reliability growth models which deal with the fault detection process only. In this paper, some useful approaches to the modeling of both software fault detection and fault correction processes are discussed. Since the estimation of model parameters in software testing is essential to give accurate prediction and help make the right decision about software release, the problem of estimating the parameters is addressed here. Taking into account the dependency between the fault correction process and the fault detection process, a new explicit formula for the likelihood function is derived and the maximum likelihood estimates are obtained under various time delay assumptions. An actual set of data from a software development project is used as an illustrative example. A Monte Carlo simulation is carried out to compare the predictive capability between the LSE method and the MLE method. © 2006 IEEE.

Original language	English
Title of host publication	Proceedings - 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006
Pages	19-25
DOIs	https://doi.org/10.1109/PRDC.2006.27
Publication status	Published - 2006
Externally published	Yes
Event	12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006 - Riverside, CA, United States Duration: 18 Dec 2006 → 20 Dec 2006

Conference

Conference	12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006
Place	United States
City	Riverside, CA
Period	18/12/06 → 20/12/06

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@inproceedings{a744e6ea20a343fa82811c80a89c46d1,

title = "Detection and correction process modeling considering the time dependency",

abstract = "Most of the models for software reliability analysis are based on reliability growth models which deal with the fault detection process only. In this paper, some useful approaches to the modeling of both software fault detection and fault correction processes are discussed. Since the estimation of model parameters in software testing is essential to give accurate prediction and help make the right decision about software release, the problem of estimating the parameters is addressed here. Taking into account the dependency between the fault correction process and the fault detection process, a new explicit formula for the likelihood function is derived and the maximum likelihood estimates are obtained under various time delay assumptions. An actual set of data from a software development project is used as an illustrative example. A Monte Carlo simulation is carried out to compare the predictive capability between the LSE method and the MLE method. {\textcopyright} 2006 IEEE.",

author = "Wu, {Y. P.} and Hu, {Q. P.} and M. Xie and Ng, {S. H.}",

year = "2006",

doi = "10.1109/PRDC.2006.27",

language = "English",

isbn = "0769527248",

pages = "19--25",

booktitle = "Proceedings - 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006",

note = "12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006 ; Conference date: 18-12-2006 Through 20-12-2006",

}

Wu, YP, Hu, QP, Xie, M & Ng, SH 2006, Detection and correction process modeling considering the time dependency. in Proceedings - 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006., 4041884, pp. 19-25, 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006, Riverside, CA, United States, 18/12/06. https://doi.org/10.1109/PRDC.2006.27

Detection and correction process modeling considering the time dependency. / Wu, Y. P.; Hu, Q. P.; Xie, M. et al.
Proceedings - 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006. 2006. p. 19-25 4041884.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Detection and correction process modeling considering the time dependency

AU - Wu, Y. P.

AU - Hu, Q. P.

AU - Xie, M.

AU - Ng, S. H.

PY - 2006

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N2 - Most of the models for software reliability analysis are based on reliability growth models which deal with the fault detection process only. In this paper, some useful approaches to the modeling of both software fault detection and fault correction processes are discussed. Since the estimation of model parameters in software testing is essential to give accurate prediction and help make the right decision about software release, the problem of estimating the parameters is addressed here. Taking into account the dependency between the fault correction process and the fault detection process, a new explicit formula for the likelihood function is derived and the maximum likelihood estimates are obtained under various time delay assumptions. An actual set of data from a software development project is used as an illustrative example. A Monte Carlo simulation is carried out to compare the predictive capability between the LSE method and the MLE method. © 2006 IEEE.

AB - Most of the models for software reliability analysis are based on reliability growth models which deal with the fault detection process only. In this paper, some useful approaches to the modeling of both software fault detection and fault correction processes are discussed. Since the estimation of model parameters in software testing is essential to give accurate prediction and help make the right decision about software release, the problem of estimating the parameters is addressed here. Taking into account the dependency between the fault correction process and the fault detection process, a new explicit formula for the likelihood function is derived and the maximum likelihood estimates are obtained under various time delay assumptions. An actual set of data from a software development project is used as an illustrative example. A Monte Carlo simulation is carried out to compare the predictive capability between the LSE method and the MLE method. © 2006 IEEE.

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DO - 10.1109/PRDC.2006.27

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0769527248

SN - 9780769527246

SP - 19

EP - 25

BT - Proceedings - 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006

T2 - 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006

Y2 - 18 December 2006 through 20 December 2006

ER -

Detection and correction process modeling considering the time dependency

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