Mining performance specifications

Marc Brünink, David S. Rosenblum
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引用次数: 23

Abstract

Functional testing is widespread and supported by a multitude of tools, including tools to mine functional specifications. In contrast, non-functional attributes like performance are often less well understood and tested. While many profiling tools are available to gather raw performance data, interpreting this raw data requires expert knowledge and a thorough understanding of the underlying software and hardware infrastructure. In this work we present an approach that mines performance specifications from running systems autonomously. The tool creates performance models during runtime. The mined models are analyzed further to create compact and comprehensive performance assertions. The resulting assertions can be used as an evidence-based performance specification for performance regression testing, performance monitoring, or as a foundation for more formal performance specifications.
采矿性能规范
功能测试得到了广泛的应用,并得到了许多工具的支持,包括挖掘功能规范的工具。相比之下,非功能属性(如性能)通常没有得到很好的理解和测试。虽然有许多分析工具可用于收集原始性能数据,但解释这些原始数据需要专业知识和对底层软件和硬件基础设施的全面了解。在这项工作中,我们提出了一种从自主运行的系统中挖掘性能规范的方法。该工具在运行时创建性能模型。进一步分析挖掘的模型,以创建紧凑和全面的性能断言。由此产生的断言可以用作性能回归测试、性能监视的基于证据的性能规范,或者作为更正式的性能规范的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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