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Reliability Growth Modeling and Optimal Release Policy Under Fuzzy Environment of an N-version Programming System Incorporating the Effect of Fault Removal Efficiency
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作者 p.k.kapur Anshu Gupta P.C.Jha 《International Journal of Automation and computing》 EI 2007年第4期369-379,共11页
Failure of a safety critical system can lead to big losses. Very high software reliability is required for automating the working of systems such as aircraft controller and nuclear reactor controller software systems.... Failure of a safety critical system can lead to big losses. Very high software reliability is required for automating the working of systems such as aircraft controller and nuclear reactor controller software systems. Fault-tolerant softwares are used to increase the overall reliability of software systems. Fault tolerance is achieved using the fault-tolerant schemes such as fault recovery (recovery block scheme), fault masking (N-version programming (NVP)) or a combination of both (Hybrid scheme). These softwares incorporate the ability of system survival even on a failure. Many researchers in the field of software engineering have done excellent work to study the reliability of fault-tolerant systems. Most of them consider the stable system reliability. Few attempts have been made in reliability modeling to study the reliability growth for an NVP system. Recently, a model was proposed to analyze the reliability growth of an NVP system incorporating the effect of fault removal efficiency. In this model, a proportion of the number of failures is assumed to be a measure of fault generation while an appropriate measure of fault generation should be the proportion of faults removed. In this paper, we first propose a testing efficiency model incorporating the effect of imperfect fault debugging and error generation. Using this model, a software reliability growth model (SRGM) is developed to model the reliability growth of an NVP system. The proposed model is useful for practical applications and can provide the measures of debugging effectiveness and additional workload or skilled professional required. It is very important for a developer to determine the optimal release time of the software to improve its performance in terms of competition and cost. In this paper, we also formulate the optimal software release time problem for a 3VP system under fuzzy environment and discuss a the fuzzy optimization technique for solving the problem with a numerical illustration. 展开更多
关键词 Fault tolerant software reliability growth model release time fuzzy optimization.
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An innovation diffusion model for consumer durables with three parameters 被引量:3
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作者 Nitin Sachdeva p.k.kapur Ompal Singh 《Journal of Management Analytics》 EI 2016年第3期240-265,共26页
Strategic innovation diffusion converts newly created knowledge into increasing a firm’s value primarily through innovative product offerings.In this paper,we present a time-based adoption pattern with pricing and pr... Strategic innovation diffusion converts newly created knowledge into increasing a firm’s value primarily through innovative product offerings.In this paper,we present a time-based adoption pattern with pricing and promotional expenditure as a three-dimensional innovation diffusion model(3D-IDM).In our proposed 3D-IDM,we assume that value of the product plays a crucial role of being the major driver of diffusion,and is classified into the following three main factors:(1)continuation time of the product in the market–representing goodwill of the product;(2)price of the product–indicating consumers’buying behaviour;and(3)marketing efforts of the firm.A special form of the Cobb–Douglas production function is used to design the three-dimensional framework.An empirical study is performed on number of consumer-durable sales data to validate and compare the proposed model.Various performance measures are treated uniquely using the Mahalanobis distance-based approach(DBA)to determine the relative strength of each model. 展开更多
关键词 innovation diffusion model three-dimensional innovation diffusion model Cobb-Douglas production function
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