CSR-SMA: Engineering Reliability Into Hybrid Systems via Rich Design Models

计算机系统正在变得普遍，并且在规模、复杂性、分布和异构性方面快速增长。由于这些原因，工程师对各种感兴趣的系统属性进行定量推理并控制其设计，开发和部署成本变得越来越重要。在理想的情况下，重要的系统特性，如性能和可靠性，将在系统设计时进行评估，然后才投入大量的时间和成本的项目。然而，使有用由于许多相关因素之间的相互作用，例如软件组件的复杂属性、固件对软件的潜在影响、固件对软件的影响、固件对软件的影响、固件的影响、固件对软件的影响、固件对软件的影响、固件的影响、固件对软件的影响、固件的影响、固件对软件的影响、固件的影响、固件对软件的影响、固件对软件的影响（硬件、操作系统、设备驱动程序），以及潜在冲突的期望系统属性。攻击这些问题的一小部分是具有挑战性的，并将导致重大的在复杂系统工程中的先进技术。因此，该项目建议将重点放在设计时评估的架构方面的一个关键属性-可靠性。在这里，可靠性被定义为系统在规定的设计限制下执行其预期功能的概率。所提出的方法将使工程师能够建立一个多方面的，层次化的系统模型，并评估其可靠性在一个增量，可扩展的方式。虽然存在一些软件可靠性技术，但它们是不够的。 为了解决这些缺陷，该项目将开发一种耦合软件架构模型的技术（系统设计人员很好地理解）与增强隐马尔可夫模型（这使我们能够对早期设计阶段存在的许多不确定性进行推理），并将用固件的相关属性来增强这种方法，以支持更完整和更有意义的可靠性模型。该项目将评估结果该方法沿着沿着两个感兴趣的测量发展：处理性（旨在解决真实的复杂系统中存在的可扩展性问题）和敏感性（旨在解决在设计时存在的众多不确定性下研究人员预测的置信度问题），并将结果应用于移动的机器人领域的真实的问题，这是一个代表许多复杂，分布式和嵌入式系统。

Computer systems are becoming pervasive as well as growing rapidly in scale, complexity, distribution, and heterogeneity. For these reasons, it is becoming increasingly important for engineers to reason quantitatively about the various systems' properties of interest and curb their design, development, and deployment costs. In an ideal situation important system characteristics, such as performance and reliability, would be assessed at system design time, before significant time and cost have been devoted to a project. However, making useful (quantitative) predictions in early design stages is difficult at best, due ti the interplay between many relevant factors, such as complex properties of software components, the potential effects on software of the firmware (hardware, OS, device drivers), as well as the potentially conflicting desired system attributes.Attacking even a small subset of these problems is challenging enough and would result in significant advances to the state of the art in complex systems engineering. Hence, this project proposes to focus efforts on design-time evaluation of architectures with respect to one key attribute - reliability. Here, reliability is defined as the probability that the system will perform its intended functionality under specified design limits. The proposed approach will enable an engineer to build a multi-faceted, hierarchical model of a system and assess its reliability in an incremental, scalable fashion. Although several software reliability techniques exist, they are insufficient. To address these deficiencies, the project will develop a technique that will couple software architectural models (well understood by system designers) with augmented Hidden Markov Models (which allow us to reason about numerous uncertainties existing in early design phases), and will augment this methodology with the relevant attributes of the firmware in support of more complete and meaningful reliability models.The project will evaluate the results the methods developed along two measures of interest: tractability (intended to address scalability issues existing in real, complex systems) and sensitivity (intended to address issues of confidence in the researchers predictions under numerous uncertainties existing at design time) and will apply the results to real problems from the domain of mobile robotics, a problem domain that is representative of many complex, distributed, and embedded systems.