The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 전체 소프트웨어 비용을 최소화하는 최적의 소프트웨어 출시 일정을 추정하기 위한 효과적인 평활화 기법을 개발합니다. 최적 소프트웨어 출시 문제는 본질적으로 소프트웨어 실패율에 대한 통계적 추정 문제로 축소되지만, 테스트 단계에서 관찰된 결함 검출 시간 데이터와 향후 추정치를 기반으로 한 결과 추정기는 불연속적이고 항상 제대로 작동하지 않습니다. 최적의 출시 일정을 결정합니다. 우리는 일반적인 2차 계획법 접근 방식을 사용하여 평활화된 소프트웨어 실패율을 추정하고 더 높은 정확도로 최적의 소프트웨어 출시 일정을 생성합니다.
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부
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
부
@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},}
부
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 -