A Statistical Estimation Method of Optimal Software Release Timing Applying Auto-Regressive Models

スポンサーリンク

概要

• 論文の詳細を見る

• This paper proposes a statistical method to estimate the optimal software release time which minimizes the expected total software cost incurred in both testing and operation phases. It is shown that the underlying cost minimization problem can be reduced to a graphical one. This implies that the software release problem under consideration is essentially equivalent to a time series forecasting for the software fault-occurrence time data. In order to predict the future fault-occurrence time, we apply three extraordinary auto-regressive models by Singpurwalla and soyer (1985) as the prediction devices as well as the well-known AR and ARIMA models. Numerical example sare devoted to illustrate the predictive performance for the proposed method. We compare it with the classical exponential software reliability growth model based on the non-homegeneous Poisson process, using actual software fault-occurrence time data.

• 社団法人電子情報通信学会の論文
• 2001-01-01

著者

• Osaki Shunji

  The Authors Are With The Department Of Industrial And Systems Engineering Hiroshima University Facul

• Dohi Tadashi

  The Authors Are With The Department Of Industrial And Systems Engineering Hiroshima University Facul

• MORISHITA Hiromichi

  The authors are with the Department of Industrial and Systems Engineering, Hiroshima University, Fac

• Morishita Hiromichi

  The Authors Are With The Department Of Industrial And Systems Engineering Hiroshima University Facul

関連論文

• A Statistical Estimation Method of Optimal Software Release Timing Applying Auto-Regressive Models

スポンサーリンク