Evaluating the reliability of component-based software systems from their architecture is of great importance. This paper proposes metrics to assess the reliability of software systems considering the self-healing effect of components on software reliability. A self-healing component when being broken, heals itself with a probability and returns to normal conditions. Because designing a self-healing component is complex and costly, it is not possible to add self-healing operations to all components. Identifying effective components on the overall reliability of a software system, for adding self-healing operations to them, especially in the early stages of Software Development Life Cycle (SDLC) can have a great impact on reliability. In the literature, considering design models, many methods are presented for assessing the reliability of the software systems, but there exists no method to evaluate the impact of self-healing on reliability and also to identify candidate components to perform self-healing. In this paper, first, using the Markov chain, a method for modeling the self-healing behavior of a component is proposed. Then, by different combinations of Taylor series expansion and self-healing, several metrics are proposed to evaluate the reliability of a software system. Finally, we will present relationships that help a software engineer to identify the influential and bottleneck components for self-healing.

从它们的体系结构评估基于组件的软件系统的可靠性非常重要。考虑到组件对软件可靠性的自我修复作用，本文提出了评估软件系统可靠性的指标。破裂时会自我修复，有可能自我修复并恢复正常状态。因为设计自修复组件很复杂且成本很高，所以不可能对所有组件添加自修复操作。确定软件系统总体可靠性上的有效组件，以便为它们添加自我修复操作，尤其是在软件开发生命周期（SDLC）的早期阶段，可能会对可靠性产生重大影响。在文献中，考虑设计模型，提出了许多方法来评估软件系统的可靠性，但是没有方法可以评估自我修复对可靠性的影响，也无法识别执行自我修复的候选组件。在本文中，首先，使用马尔可夫链，提出了一种对组件的自愈行为建模的方法。然后，通过泰勒级数展开和自愈的不同组合，提出了几种度量标准来评估软件系统的可靠性。最后，我们将介绍一些关系，以帮助软件工程师识别具有影响力和瓶颈的组件以进行自我修复。提出了一种建模组件自愈行为的方法。然后，通过泰勒级数展开和自愈的不同组合，提出了几种度量标准来评估软件系统的可靠性。最后，我们将介绍一些关系，以帮助软件工程师识别具有影响力和瓶颈的组件以进行自我修复。提出了一种建模组件自愈行为的方法。然后，通过泰勒级数展开和自愈的不同组合，提出了几种度量标准来评估软件系统的可靠性。最后，我们将介绍一些关系，以帮助软件工程师识别具有影响力和瓶颈的组件以进行自我修复。