Reliability analysis and optimal version-updating for open source software

Li, Xiang; Li, Yan Fu; Xie, Min; Ng, Szu Hui

doi:10.1016/j.infsof.2011.04.005

Cited by 106 publications

(53 citation statements)

References 30 publications

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“…Yamada and Yamaguchi [8] discussed a statistical process control method for OSS to determine the stability and thus getting estimation of development time needed to attain desired level of reliability. Li et al [9] proposed reliability analysis model and used the model to predict optimal version-updating for OSS. Tamura and Yamada [10] combined software growth modeling with neural network approaches to estimate the reliability of OSS.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Reliability Modeling of OSS Systems based on Innovation-Diffusion Theory and Imperfect Debugging

Gandhi¹,

Gondwal²,

Tandon³

2018

Annals of Computer Science and Information Systems

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Section: Literature Reviewmentioning

confidence: 99%

“…GNOME 2.0 provided by Li et al (2011) as given in Table 1. Estimation of proposed models is performed with the Least Squares Principle.…”

Section: Numerical Studymentioning

confidence: 99%

Reliability Modeling of OSS Systems based on Innovation-Diffusion Theory and Imperfect Debugging

Gandhi¹,

Gondwal²,

Tandon³

2018

Annals of Computer Science and Information Systems

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“…On the other hand, only a few effective methods assisting dynamic testing management for a new distributed development paradigm, as typified by the open source projects, have been presented [8][9][10]. Furthermore, several research works [11][12][13][14][15] are based on the area of cloud computing and mobile clouds.…”

Section: Related Researchmentioning

confidence: 99%

Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

Tamura

Yamada

2015

Entropy

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At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud computing changes depending on many external factors. We propose a jump diffusion model with two-dimensional Wiener processes in order to consider the interesting aspects of the network traffic and big data on cloud computing. In particular, we assess the stability of cloud software by using the sample paths obtained from the jump diffusion model with two-dimensional Wiener processes. Moreover, we discuss the optimal maintenance problem based on the proposed jump diffusion model. Furthermore, we analyze actual data to show numerical examples of dependability optimization based on the software maintenance cost considering big data on cloud computing.

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“…Motivated from [33,42], the optimal release time problem has been discussed using multi-attribute utility theory (MAUT). MAUT is a classical multi-objective optimization technique, which solves the optimization problem by using weights and the utility functions [43].…”

Section: Solution Of Release Time Problem Using Multi-attribute Utilimentioning

confidence: 99%

“…. n and w 0 i s are the corresponding weights [33,42]. By maximizing this multi-attribute function, the optimal solution is obtained.…”

Section: Solution Of Release Time Problem Using Multi-attribute Utilimentioning

confidence: 99%

Software reliability growth modeling with dynamic faults and release time optimization using GA and MAUT

Pachauri

Kumar

Dhar

2014

Applied Mathematics and Computation

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Reliability analysis and optimal version-updating for open source software

Cited by 106 publications

References 30 publications

Reliability Modeling of OSS Systems based on Innovation-Diffusion Theory and Imperfect Debugging

Reliability Modeling of OSS Systems based on Innovation-Diffusion Theory and Imperfect Debugging

Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

Software reliability growth modeling with dynamic faults and release time optimization using GA and MAUT

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