CSR: SMALL: Robust Algorithms for an Open Source Software Reliability Tool

所有软件成功的关键是它的可靠性。这个项目将开发一个开源软件可靠性工具，它将允许软件工程师自动应用软件可靠性模型，以帮助组织确保他们开发的软件应用程序可以无故障地运行。传统算法在数值上是不稳定的，这意味着如果初始估计不准确，它们可能会失败。算法的失败使得无法应用软件可靠性模型来做出有用的预测，例如为了达到期望的可靠性水平，软件应用程序应该测试的额外时间。这项研究的目标是开发数字稳定的算法，即使最初的估计是不准确的，也能成功。针对故障率和非齐次泊松过程（NHPP）软件可靠性模型，提出了期望最大化和期望条件最大化算法。传统的电磁算法施加了限制性的假设，限制了它们的应用仅限于最简单的模型，而ECM算法的潜力尚未得到充分的探索。因此，本研究挑战将消除现有电磁算法的限制，为软件可靠性模型设计高效的电磁算法。这些数值稳定的EM和ECM算法的实现将被纳入开源工具，以确保软件可靠性模型可以成功应用。算法的增强稳定性和工具的开放源代码性质可能促进定量软件可靠性模型的广泛使用，使公司和组织能够改进软件产品的上市时间或领域。

The key to the success of all software is its reliability. This project will develop an open source software reliability tool that will allow software engineers to automatically apply software reliability models to help organizations ensure that software applications they develop can operate free of failures. Traditional algorithms are numerically unstable, meaning that they can fail if initial estimates are inaccurate. Failure of an algorithm renders it impossible to apply a software reliability model to make useful predictions such as the amount of additional time a software application should be tested in order to achieve a desired level of reliability. The goal of this research is to develop numerically stable algorithms that will succeed even if the initial estimates are inaccurate. Expectation maximization (EM) and expectation conditional maximization (ECM) algorithms will be developed for failure rate and nonhomogeneous Poisson process (NHPP) software reliability models. Traditional EM algorithms impose restrictive assumptions that limit their application to only the simplest models, while the potential of the ECM algorithm has not been fully explored. Therefore, this research challenge will remove the restrictions of existing EM algorithms and design efficient ECM algorithms for software reliability models. Implementations of these numerically stable EM and ECM algorithms will be incorporated into the open source tool to ensure that software reliability models can be applied successfully. The enhanced stability of the algorithms and the open source nature of the tool may promote widespread use of quantitative software reliability models, enabling companies and organizations to improve time to market or field a software product.