利用软件遥测技术实现日常软件的可靠性

K. Gross, S. McMaster, A. Porter, A. Urmanov, L. Votta
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引用次数: 14

摘要

应用程序级软件的可靠性很难保证。因此,它通常只在定制系统中使用,并且使用独一无二的手工解决方案来实现。我们感兴趣的是了解这些技术是否以及如何应用于更常见的低端系统。为此,我们采用了一种基于状态的维护(CBM)方法,称为多变量状态估计技术(MSET)。这种方法可以自动创建复杂的统计模型,在故障发生之前很好地预测系统故障,从而实现更简单、更成功的恢复。我们在软件可靠性框架(SDF)中打包了这种方法。SDF由仪器和数据管理库、CBM模块、性能可视化工具和支持系统设计人员的软件体系结构组成。最后,我们在一个简单的视频游戏应用程序上评估了我们的框架。我们的结果表明,我们可以便宜而可靠地预测即将发生的运行时故障,并及时响应,以提高系统的可靠性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Dependability in Everyday Software Using Software Telemetry
Application-level software dependability is difficult to ensure. Thus it's typically used only in custom systems and is achieved using one-of-a-kind, handcrafted solutions. We are interested in understanding whether and how these techniques can be applied to more common, lower-end systems. To this end, we have adapted a condition-based maintenance (CBM) approach called the multivariate state estimation technique (MSET). This approach automatically creates sophisticated statistical models that predict system failure well before failures occur, leading to simpler and more successful recoveries. We have packaged this approach in the Software Dependability Framework (SDF). The SDF consists of instrumentation and data management libraries, a CBM module, performance visualization tools, and a software architecture that supports system designers. Finally, we evaluated our framework on a simple video game application. Our results suggest that we can cheaply and reliably predict impending runtime failures and respond to them in time to improve the system's dependability
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