Optimum number of errors corrected before releasing a software system

Bai, Do Sun; Yun, Woo-Seop

doi:10.1109/24.3710

Cited by 18 publications

(12 citation statements)

References 9 publications

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“…The policy proposes not to release the software system until n* failures are observed (i.e., n* faults are corrected) and to release it immediately thereafter. Similar results are obtained by Bai and Yun [1988]. Note that although c 1 > 0, the optimal release rule has a simple control-limit structure described by the single critical number n* as in Corollary 1.…”

Section: Numerical Illustrationssupporting

confidence: 85%

“…The main idea is to stop testing whenever the total failure rate of the software system goes below an acceptable failure rate. Bai and Yun (1988) consider a cost model where the release decision is based on the number of faults corrected during the testing time. Although the underlying reliability model is the de-eutrophication model of Jelinski and Moranda (1972), the proposed procedure for the determination of the optimal release time is also applicable to any decreasing failure rate model.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A dynamic software release model

Özekıcı

Catkan

1993

Comput Econ

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Abstract. The determination of optimal software release times constitutes an interesting decision making problem which involves the stochastic structure of the underlying software reliability model, as well as various cost parameters. There is an apparent tradeoff between testing the software further to improve its reliability, and releasing it for operational use to decrease the costs. We propose and analyze in depth a new dynamic model with sufficient generality. After each failure, a debugging activity, possibly imperfect, is undertaken and a decision is made regarding the duration of additional testing. If no failure is observed during this time, then the software is released. Otherwise, the failure is debugged and the decision process is repeated in a dynamic fashion. The problem is formulated using dynamic programming and interesting characterizations of the optimal release policy are presented. The dynamic solution procedure is demonstrated by some numerical illustrations.

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Section: Numerical Illustrationssupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

A dynamic software release model

Özekıcı

Catkan

1993

Comput Econ

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“…. , τ (1) K ). This process of testing and revising the uncertainties and testing continue until the software is tested for all operations.…”

Section: Optimal Testing Strategymentioning

confidence: 97%

“…There is a vast amount of literature on the subject as referenced in the survey byÖzekici and Ç atkan [11]. The reader is referred to Forman and Singpurwalla [4], Koch and Kubat [6], Yamada and Osaki [20], Ross [15], Bai and Yun [1], and Brown, Maghsoodloo, and Deason [2] for some examples.…”

Section: Optimal Testing Strategymentioning

confidence: 99%

Bayesian testing strategies for software with an operational profile

Özekıcı

Soyer

2001

Naval Research Logistics

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Abstract:We consider a software reliability model where the failure rate of each fault depends on the specific operation performed. The software is tested in a given sequence of test cases for fixed durations of time to collect data on failure times. We present a Bayesian analysis of software failure data by treating the initial number of faults as a random variable. Our analysis relies on the Markov Chain Monte Carlo methods and is used for developing optimal testing strategies in an adaptive manner. Two different models involving individual and common faults are analyzed. We illustrate an implementation of our approach by using some simulated failure data.

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“…Koch and Kubat [3] assumed the Jelinski and Moranda model [4] for the software fault detection process and discussed a similar problem. Bai and Yun [5] proposed a control-limited optimal release measure by deriving the optimal number of faults that should be detected and removed before release for the Jelinski and Moranda model. Other papers disclosed many research results related to the optimal release problem of software that considered different testing environments [6,7].…”

Section: Introductionmentioning

confidence: 99%

Optimal testing/maintenance design in a software development project

Rinsaka

2006

Electron. Comm. Jpn. Pt. III

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SUMMARYIn this paper, we consider the problem of determining the optimal testing period and the optimal maintenance limit for software. Software debugging in the testing phase and the operation stage is described by a software reliability model based on a nonhomogeneous Poisson process and models the difference between the software execution environments in both stages as the operational profile. Furthermore, the time when continued maintenance by the project team ends is defined as the planned maintenance limit. Each of the optimal testing period (release time) and the optimal planned maintenance limit that minimize the total expected software cost is determined. Finally, we present an algorithm that determines the joint optimal policies for both, and perform the optimal testing/maintenance design through numerical examples.

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Optimum number of errors corrected before releasing a software system

Cited by 18 publications

References 9 publications

A dynamic software release model

A dynamic software release model

Bayesian testing strategies for software with an operational profile

Optimal testing/maintenance design in a software development project

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