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Ripple: A Test-Aware Architecture Modeling Framework

机译:Ripple:一种可感知测试的架构建模框架

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摘要

Different architecture views can be used to address concerns of different stakeholders. While architecture models have been used to guide software detailed design, development, and maintenance, no existing work has incorporated information generated in testing activities into architecture models for providing testing guidance. In this paper, we present Ripple, the framework for constructing test-aware DRSpace modeling to simultaneously reveal dynamic test coupling and static structural dependencies among source files in a software system. Ripple first mines from dynamic test coverage reports to extract traceability links between source files and test cases. It then encodes testing information into DRSpaces and leverages the DRH algorithm to cluster source files into independent test modules. To evaluate Ripple, we conducted a pilot study on a component of Hadoop. The study shows that Ripple has the potential to provide guidance for various stakeholders in making test-related decisions.
机译:可以使用不同的体系结构视图来解决不同利益相关者的关注。虽然已经使用体系结构模型来指导软件的详细设计,开发和维护,但是现有的工作都没有将测试活动中生成的信息合并到体系结构模型中以提供测试指导。在本文中,我们介绍了Ripple,该框架用于构建可感知测试的DRSpace建模,以同时揭示软件系统中源文件之间的动态测试耦合和静态结构依赖性。 Ripple首先从动态测试覆盖率报告中挖掘信息,以提取源文件和测试用例之间的可追溯性链接。然后,它将测试信息编码到DRSpaces中,并利用DRH算法将源文件群集到独立的测试模块中。为了评估Ripple,我们对Hadoop组件进行了初步研究。该研究表明,Ripple有潜力在与测试相关的决策中为各种利益相关者提供指导。

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