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Estimating Software Reliability with Static Project Data in Incremental Development Processes

机译：估算增量开发过程中静态项目数据的软件可靠性

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摘要

Incremental development of software becomes much popular and enables to reduce the development cost effectively. On the other hand, it has not been known yet that the incremental development can really contribute to guarantee the software reliability more than the waterfall development paradigm. In this paper we estimate quantitative software reliability with both of static fault count data and static metrics data for incremental development processes. Since the measurement of software development project data is often expensive, we encounter the situation where the time series data are not always available. We develop metrics-based software reliability models based on the non-homogeneous Poisson processes for the purpose of reliability assessment in the incremental development, and compare them with an elementary approach with multiple linear regression model. Numerical examples are given with real software project data to show that our proposed methods outperform the common multiple linear regression model under the assumption on independent incremental testing phases.
机译：软件的增量开发变得很受欢迎，并使能够有效地降低开发成本。另一方面，尚未知道，但增量开发可以真正有助于保证软件可靠性超过瀑布开发范式。在本文中，我们估算了具有用于增量开发过程的静态故障计数数据和静态度量数据的定量软件可靠性。由于软件开发项目数据的测量往往是昂贵的，因此我们遇到了时间序列数据并不总是可用的情况。我们基于非同质泊松过程开发基于度量的软件可靠性模型，以便在增量开发中的可靠性评估，并将它们与具有多元线性回归模型的基本方法进行比较。具有实际软件项目数据的数值示例，以表明我们所提出的方法在独立增量测试阶段的假设下优于共同的多个线性回归模型。

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