S-shaped software reliability growth models derived from stochastic differential equations.: An article from: IIE Transactions
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ISBN / ASINB0009GO8C6
ISBN-13978B0009GO8C7
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This digital document is an article from IIE Transactions, published by Institute of Industrial Engineers, Inc. (IIE) on December 1, 2004. The length of the article is 4228 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.
From the author: This paper presents a software reliability growth model based on Ito type Stochastic Differential Equations (SDE). As the size of a software system becomes larger, the number of faults remaining in the system during the testing phase can be considered to be a continuous stochastic process. In practice, if the per-fault detection rate is subject to certain random effects, we may consider the use of a SDE to describe the average behavior of the software fault detection process during the testing phase. As a result, we derive several software reliability measures by utilizing the mean value function which is the expected value of the SDE. We also derive the maximum likelihood estimators of the unknown parameters for the model. Futhermore, we compare our model with other software reliability growth models in terms of several reliability measures and goodness-of-fit for the same data set.
Citation Details
Title: S-shaped software reliability growth models derived from stochastic differential equations.
Author: Chong Hyung Lee
Publication:IIE Transactions (Refereed)
Date: December 1, 2004
Publisher: Institute of Industrial Engineers, Inc. (IIE)
Volume: 36 Issue: 12 Page: 1193(7)
Distributed by Thomson Gale
From the author: This paper presents a software reliability growth model based on Ito type Stochastic Differential Equations (SDE). As the size of a software system becomes larger, the number of faults remaining in the system during the testing phase can be considered to be a continuous stochastic process. In practice, if the per-fault detection rate is subject to certain random effects, we may consider the use of a SDE to describe the average behavior of the software fault detection process during the testing phase. As a result, we derive several software reliability measures by utilizing the mean value function which is the expected value of the SDE. We also derive the maximum likelihood estimators of the unknown parameters for the model. Futhermore, we compare our model with other software reliability growth models in terms of several reliability measures and goodness-of-fit for the same data set.
Citation Details
Title: S-shaped software reliability growth models derived from stochastic differential equations.
Author: Chong Hyung Lee
Publication:IIE Transactions (Refereed)
Date: December 1, 2004
Publisher: Institute of Industrial Engineers, Inc. (IIE)
Volume: 36 Issue: 12 Page: 1193(7)
Distributed by Thomson Gale
