Software reliability analysis

Misra, P.

doi:10.1147/sj.223.0262

Cited by 126 publications

(43 citation statements)

References 5 publications

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“…Let D 1 and D 2 be the number of observed (and corrected) unrelated design faults in, respectively, each version, and D r the number of observed (and corrected) related design faults. "Software science" (see, for instance, [11]) can be used to estimate the number of unrelated design faults in each version before the "face-to-face" debugging started. Let N 1 and N 2 be the number of those faults, N u = N 1 + N 2 and D u = D 1 + D 2 .…”

Section: Model Parameter Estimationmentioning

confidence: 99%

Evaluation of safety-oriented two-version architectures

Carrasco

Figueras

Kuntzman

1991

Journal of Systems and Software

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A Markov model taking into account physical and design faults for a two-version architecture oriented to safety-related applications is developed. Only a probabilistic knowledge of the initial state of the versions in relation to the presence of design faults is assumed. The model can be split into two submodels accounting separately for physical and design faults, and a closed form expression for the unsafety of the system is obtained. The parameter estimation problem is discussed and a method to predict the probability distribution of the number of related design faults at the beginning of the operational life of the system is proposed. The method uses a pool model to process fault-occurrence data collected during a "face-to-face" debugging of the two versions. It has by nature a limited capability for proving version diversity, but it is shown that the limit is of the order of the diversity reported by recent experiments on real software. Finally, the impact of version correction during operation is shown to be negligible for critical applications.

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Section: Model Parameter Estimationmentioning

confidence: 99%

Evaluation of safety-oriented two-version architectures

Carrasco

Figueras

Kuntzman

1991

Journal of Systems and Software

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“…Numerical example: Using â = 424.36, £ x =0.3983 x 10~3, £ 2 = 0.1370 x 10' 3 and j? 1 = 0.8, p 2~0 .6 (r 1~Q .64, r 2 = 0.36) we discuss optimal release policy for the software System described in [3]. We assume C n = 2.…”

Section: Optimal Release Policymentioning

confidence: 99%

Optimal sofware release policies for software reliability growth models under imperfect debugging

Kapur¹,

Garg²

1990

RAIRO-Oper. Res.

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“…Especially, such Open Source Software (OSS) systems which serve as key components of critical infrastructures in the society are still ever-expanding now (E-Soft Inc.). Software reliability growth models (SRGM's) (Misra, 1983;Musa et al 1987;Yamada & Osaki, 1989;Yamada, 1991;Yamada 1994) have been applied to assess the reliability for quality management and testing-progress control of software development. On the other hand, the effective method of testing management for the new distributed development paradigm as typified by the open source project has only a few presented (Kuk, 2006;Li et al 2004;MacCormack et al 2006;Zhoum & Davis, 2005).…”

mentioning

confidence: 99%