Statistical Inference of Software Performance Models for Parametric Performance Completions
Statistical Inference of Software Performance Models for Parametric Performance Completions
复制标题
用于参数化性能完成的软件性能模型的统计推断
DOI：
10.1007/978-3-642-13821-8_4
复制
发表时间：
2010
影响因子：
5.8
通讯作者：
Lucia Happe
中科院分区：
文献类型：
--
作者：
J. Happe;D. Westermann;Kai Sachs;Lucia Happe
软件性能工程（SPE）使软件架构师能够确保其应用程序的高性能标准。然而，SPE在实践中的应用仍然具有挑战性。大多数企业应用程序都包括一个大型软件基础，例如中间件和遗留系统。在许多情况下，软件基础是系统的总体时序行为、吞吐量和资源利用率的决定因素。为了捕捉这些对整个系统的性能的影响，建立的性能预测方法（基于模型和分析）依赖于模型，描述的性能相关方面的研究中的系统。创建这样的模型需要对系统的结构和行为有详细的了解，而在大多数情况下，这是不可能的。在本文中，我们抽象出所研究的系统的内部结构。我们专注于面向消息的中间件（中间件），并分析中间件的使用和它的性能之间的依赖关系。我们使用统计推断从观察中得出这些依赖关系。对于ActiveMQ 5.3，结果函数预测性能的相对均方误差为0.1。
Software performance engineering (SPE) enables software architects to ensure high performance standards for their applications. However, applying SPE in practice is still challenging. Most enterprise applications include a large software basis, such as middleware and legacy systems. In many cases, the software basis is the determining factor of the system’s overall timing behavior, throughput, and resource utilization. To capture these influences on the overall system’s performance, established performance prediction methods (model-based and analytical) rely on models that describe the performance-relevant aspects of the system under study. Creating such models requires detailed knowledge on the system’s structure and behavior that, in most cases, is not available. In this paper, we abstract from the internal structure of the system under study. We focus on message-oriented middleware (MOM) and analyze the dependency between the MOM’s usage and its performance. We use statistical inference to conclude these dependencies from observations. For ActiveMQ 5.3, the resulting functions predict the performance with a relative mean square error 0.1.