• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.273-273
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• 2002

In this paper, we investigate a software release policy with software reliability growth factor during the warranty period by assuming that the software reliability growth is assumed to occur after the testing phase with probability p and the software reliability growth is not assumed to occur after the testing phase with probability 1-p. The optimal release policy to minimize the expected total software cost is discussed. Numerical examples are shown to illustrate the results of the optimal policy. And we consider a Bayesian decision theoretic approach to determine an optimal software release policy. This approach enables us to update our uncertainty when determining optimal software release time, When the failure time is Weibull distribution with uncertain parameters, a bayesian approach is established. Finally, numerical examples are presented for illustrative propose.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.27-35
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• 1989

Software developers often allocate a significant amount of effort to software testing. But for most business-related software system it is natural to expect the continued discovery of defects after the software system is released into field. Such defects are usually very expensive to fix and have the potential to cause great damages to the users. It is important to stop testing the software and release it to the users at the correct time. In this paper, we propose the determination of the optimal number of software test oy minimizing a total expected software cost. A numerical example is used when the criterion is the expected profit. The result indicates that the proposed software release policy based on the number of software test can be a good alternative to the existing policy.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1225-1233
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• 1998

An important issue for software developers is to determine when to stop testing the software system and release it to users. Generally the release time is specified by the number of detected faults or the testing time needed to meet the reliability requirement. Software reliability directly depends on the number of remaining or corrected faults. All the detected faults are not always corrected under imperfect debugging environment. We therefore need a new approach to software release policy for imperfect debugging. This paper suggests a software release policy, which guarantees that the reliability requirement has been achieved. The suggested policy is then implemented and illustrated for specific SRGMs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.1-6
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• 1990

This paper deals with software Release policy having a Fixed Operational period after a Software System is released. The underlying Software Reliability Growth is described by J-M Model Optimal of Software Release Time minimizing Total Expected Cost is Obtained.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.673-682
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• 2005

In this paper, we generalize the software reliability growth model by assuming that the testing cost and maintenance cost are random and adopt the Bayesian approach to determine the optimal software release time. Numerical examples are provided to illustrate the Bayesian method for certain parametric models.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.891-898
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• 2010

In real software development fields, software is unified by several modules that are developed before the software testing period. For the evaluation of software task processing performance, this paper considers the software imperfect debugging model that is proposed by Lee and Park (2003) and presents the measures of a unified software, such as the completion probability of a task which is completed in a time interval and the expected number of the completed tasks. In addition, we suggest a software release policy that satisfies the required level of the expected perfect debugging, completion probability, and availability.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.49-54
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• 2012

In this paper, a software policy considering testing time and the number of errors corrected is presented. The software is tested until a specified testing time or the time to a specified number of errors are corrected, whichever comes first. The model includes the cost of error correction and software testing during the testing time, and the cost of error correction during operation. It is assumed that the length of software life cycle has no bounds, and the error correction follows an non-homogeneous Poisson process. An expression for the total cost under the policy is derived. It is shown that the model includes the previous models as special cases.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.159-166
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• 2013

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, finite failure non-homogeneous Poisson process model, presented and propose release policies of the life distribution, half-logistic property model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameters estimation using maximum likelihood estimation of failure time data, make out estimating software optimal release time. Software release time is used as prior information, potential security damages should be reduced.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.335-342
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• 2013

In this study, reliability software cost model considering logarithmic fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software cost model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. In this research, Software developers to identify the best time to release some extent be able to help is considered.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.219-226
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• 2014

In this study, reliability software cost model considering shape parameter based on life distribution from the process of software product testing was studied. The shape parameter using the Erlang and Log-logistic model that is widely used in the field of reliability problems presented. The software failure model was used finite failure non-homogeneous Poisson process model, the parameters estimation using maximum likelihood estimation was conducted. In comparison result of software cost model based on the Erlang distribution and the log-logistic distribution software cost model, because Erlang model is to predict the optimal release time can be software, but the log-logistic model to predict to optimal release time can not be, Erlang distribution than the log-logistic distribution appears to be effective. In this research, software developers to identify software development cost some extent be able to help is considered.