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首页> 外文会议>2011 IEEE International Conference on Quality and Reliability >Software reliability growth models based on Marshall-Olkin generalized exponential families of distributions
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Software reliability growth models based on Marshall-Olkin generalized exponential families of distributions

机译：基于Marshall-Olkin的广义指数分布族的软件可靠性增长模型

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Software has been becoming an important and inevitable tool in our modern day to day life. It finds numerous applications such as space, telecommunications technology, military, nuclear plants, air traffic and medical monitoring control. To meet the continuing demand for high quality software, an enormous multitude of Software reliability Growth models have been proposed and adopted in recent years. A new family of distributions has been introduced by incorporating an additional parameter and applied to yield a new two parameter extension of exponential distribution [1]. Parikh et al. [2] call such a family of distributions as Marshall and Olkin Generalized Exponential (MOGE) distributions and studied its inferential problems. In this paper we propose NHPP software reliability Growth models based on MOGE and validate them through different metrics using real data sets.
机译：在我们的现代生活中，软件已成为一种重要且不可避免的工具。它发现了许多应用程序，例如太空，电信技术，军事，核电站，空中交通和医疗监控。为了满足对高质量软件的持续需求，近年来已经提出并采用了大量的软件可靠性增长模型。通过合并一个附加参数引入了一个新的分布族，并将其应用于产生指数分布的新的两个参数扩展[1]。 Parikh等。 [2]将这类分布族称为Marshall和Olkin广义指数（MOGE）分布，并研究了其推论问题。在本文中，我们提出了基于MOGE的NHPP软件可靠性增长模型，并使用实际数据集通过不同的指标对其进行了验证。

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