The Effective Smoothing Technique to Estimate the Optimal Software Release Schedule Based on Artificial Neural Network(Special Section on Reliability Theory and Its Applications)
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概要
- 論文の詳細を見る
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.
- 社団法人電子情報通信学会の論文
- 2000-05-25
著者
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Osaki Shunji
The Department Of Industrial And Systems Engineering Faculty Of Engineering Hiroshima University
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Dohi Tadashi
The Department Of Industrial And Systems Engineering Faculty Of Engineering Hiroshima University
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YATSUNAMI Yoshifumi
the Department of Industrial and Systems Engineering, Faculty of Engineering, Hiroshima University
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NISHIO Yasuhiko
the Department of Industrial and Systems Engineering, Faculty of Engineering, Hiroshima University
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Yatsunami Yoshifumi
The Department Of Industrial And Systems Engineering Faculty Of Engineering Hiroshima University
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Nishio Yasuhiko
The Department Of Industrial And Systems Engineering Faculty Of Engineering Hiroshima University
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- The Effective Smoothing Technique to Estimate the Optimal Software Release Schedule Based on Artificial Neural Network(Special Section on Reliability Theory and Its Applications)
- Application of Markov Chain Monte Carlo Random Testing to Test Case Prioritization in Regression Testing
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