Software Reliability Growth Model (SRGM) with Imperfect Debugging, Fault Reduction Factor and Multiple Change-Point

Jain, Madhu; Manjula, T.; Gulati, T. R.

doi:10.1007/978-81-322-0491-6_95

Cited by 19 publications

(6 citation statements)

References 11 publications

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“…Recently, several SRGMs with multiple CPs have been proposed [21][22][23]. In general, these models estimate the CPs only by using failure data.…”

Section: Web Software Reliability Model With Multiple Cpsmentioning

confidence: 99%

“…Zhao [20] suggested that, before the software is delivered to users, a CP may occur when the testing strategy and resource allocation change. Some reliability CP models have been published in the past, such as the Weibull CP model, the Jelinski Moranda de-eutrophication model with one CP, the Littlewood model with one CP [20], and the reliability model with multiple CPs [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

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Web software reliability modeling with random impulsive shocks

Yang

Zhao

2014

J. of Syst. Eng. Electron.

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As the web-server based business is rapidly developed and popularized, how to evaluate and improve the reliability of web-servers has been extremely important. Although a large number of software reliability growth models (SRGMs), including those combined with multiple change-points (CPs), have been available, these conventional SRGMs cannot be directly applied to web software reliability analysis because of the complex web operational profile. To characterize the web operational profile precisely, it should be realized that the workload of a web server is normally non-homogeneous and often observed with the pattern of random impulsive shocks. A web software reliability model with random impulsive shocks and its statistical analysis method are developed. In the proposed model, the web server workload is characterized by a geometric Brownian motion process. Based on a real data set from IIS server logs of ICRMS website (www.icrms.cn), the proposed model is demonstrated to be powerful for estimating impulsive shocks and web software reliability.

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“…Recently, several SRGMs with multiple CPs have been proposed [21][22][23]. In general, these models estimate the CPs only by using failure data.…”

Section: Web Software Reliability Model With Multiple Cpsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Web software reliability modeling with random impulsive shocks

Yang

Zhao

2014

J. of Syst. Eng. Electron.

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“…Among these definitions, Musa's version of FRF became very popular in the research community. After Realizing the importance of FRF in affecting the failure behavior, several NHPP based SRGMs were proposed considering FRF as one of the key component [6,8,9,18,19,48]. These studies also captured the FRF trend.…”

Section: Frfmentioning

confidence: 99%

Testing Resource based Optimal Release Policy for Software System Incorporating Fault Reduction Factor and Change point

Arora,

Tandon,

Aggarwal

et al. 2019

IJRTE

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In today’s competitive scenario, it is essential for software developers to perform rigorous testing. It helps them to satisfy the demand for reliable software systems. Various external and internal factors like human expertise, fault dependency, code complexity, dynamic approaches etc. affect the process of fault removal. Hence, along the time-line fault removal rate may change. The point on time-line beyond which rates are altered is termed as the change point. Also in many practical situations, the number of failures experienced may not coincide with the number of faults removed from the system. This ratio is computed by Fault Reduction Factor (FRF). Here, we have proposed testing effort based model considering effort-dependent FRF with and without change point for gauging the failure pattern of a software system. The FRF has been modelled by logistic curve. The developed models have been verified using real-life software fault datasets. Model parameters are estimated and various performance criteria are employed to check the goodness of fit. Later, we have developed a software cost model to determine the optimal Release testing effort that minimizes total expected cost of fault removal during testing phase and operational phase of software life cycle subject to a reliability constraint. A numerical study has been also taken to demonstrate the results. Cost sensitivity analysis has been carried out to identify the crucial cost component and role of each cost component on optimal testing effort and overall cost of development.

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“…Wang et al (2002) discussed lifetime estimation problems when date-specific sales amounts are not available for products whose lifetime is measured in usage time. Jain et al (2012) predicted reliability growth and warranty cost of software with fault reduction factor, imperfect debugging, and multiple change point. Akbarov and Wu (2012) used the weighted maximum likelihood estimation for estimating model parameters which might, therefore, lead to better performance of warranty forecasting models than maximum likelihood estimation.…”

Section: Literature Reviewmentioning

confidence: 99%

Investigating the effects of operators on warranty cost under sales delay conditions

Dorabati

Hamadani²,

Fazlollahtabar³

2018

JQME

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Purpose Due to the fact that the non-standard products, being used by customers, may cause failures in products with sales delays, which naturally affect the warranty policy. Thus, it seems to be necessary to study these two concepts simultaneously. The paper aims to discuss these issues. Design/methodology/approach In this paper, a model is developed for estimating the expected warranty costs under sales delay conditions when two operator costs (failing but not reported and non-failing but reported) are included. Findings The proposed model is validated using a numerical example for a two types of intermittent and fatal failures occur under a non-renewing warranty policy. Originality/value Sales delay is the time interval between the date of production and the date of sale. Most reported literature on warranty claims data analysis related to sales delay have mainly focussed on estimating the probability distribution of the sales delay.

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Software Reliability Growth Model (SRGM) with Imperfect Debugging, Fault Reduction Factor and Multiple Change-Point

Cited by 19 publications

References 11 publications

Web software reliability modeling with random impulsive shocks

Web software reliability modeling with random impulsive shocks

Testing Resource based Optimal Release Policy for Software System Incorporating Fault Reduction Factor and Change point

Investigating the effects of operators on warranty cost under sales delay conditions

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