IEICE TRANSACTIONS on Fundamentals
The Effective Smoothing Technique to Estimate the Optimal Software Release Schedule Based on Artificial Neural Network
Summary :
In this paper, we develop an effective smoothing technique to estimate the optimal software release schedule which minimizes the total software cost. The optimal software release problem is essentially reduced to a statistical estimation problem for the software failure rate, but the resulting estimator based on both the fault-detection time data observed in testing phase and its estimate in future is discontinuous and does not always function well for determining the optimal release schedule. We estimate the smoothed software failure rate using the usual quadratic programming approach and generate the optimal software release schedule with higher accuracy.
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- IEICE TRANSACTIONS on Fundamentals Vol.E83-A No.5 pp.796-803
- Publication Date
- 2000/05/25
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- Special Section PAPER (Special Section on Reliability Theory and Its Applications)
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Tadashi DOHI, Yoshifumi YATSUNAMI, Yasuhiko NISHIO, Shunji OSAKI, "The Effective Smoothing Technique to Estimate the Optimal Software Release Schedule Based on Artificial Neural Network" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 5, pp. 796-803, May 2000, doi: .
Abstract: In this paper, we develop an effective smoothing technique to estimate the optimal software release schedule which minimizes the total software cost. The optimal software release problem is essentially reduced to a statistical estimation problem for the software failure rate, but the resulting estimator based on both the fault-detection time data observed in testing phase and its estimate in future is discontinuous and does not always function well for determining the optimal release schedule. We estimate the smoothed software failure rate using the usual quadratic programming approach and generate the optimal software release schedule with higher accuracy.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_5_796/_p
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@ARTICLE{e83-a_5_796,
author={Tadashi DOHI, Yoshifumi YATSUNAMI, Yasuhiko NISHIO, Shunji OSAKI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={The Effective Smoothing Technique to Estimate the Optimal Software Release Schedule Based on Artificial Neural Network},
year={2000},
volume={E83-A},
number={5},
pages={796-803},
abstract={In this paper, we develop an effective smoothing technique to estimate the optimal software release schedule which minimizes the total software cost. The optimal software release problem is essentially reduced to a statistical estimation problem for the software failure rate, but the resulting estimator based on both the fault-detection time data observed in testing phase and its estimate in future is discontinuous and does not always function well for determining the optimal release schedule. We estimate the smoothed software failure rate using the usual quadratic programming approach and generate the optimal software release schedule with higher accuracy.},
keywords={},
doi={},
ISSN={},
month={May},}
Copy
TY - JOUR
TI - The Effective Smoothing Technique to Estimate the Optimal Software Release Schedule Based on Artificial Neural Network
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 796
EP - 803
AU - Tadashi DOHI
AU - Yoshifumi YATSUNAMI
AU - Yasuhiko NISHIO
AU - Shunji OSAKI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 2000
AB - In this paper, we develop an effective smoothing technique to estimate the optimal software release schedule which minimizes the total software cost. The optimal software release problem is essentially reduced to a statistical estimation problem for the software failure rate, but the resulting estimator based on both the fault-detection time data observed in testing phase and its estimate in future is discontinuous and does not always function well for determining the optimal release schedule. We estimate the smoothed software failure rate using the usual quadratic programming approach and generate the optimal software release schedule with higher accuracy.
ER -
English
