使用测试跟踪进行自动用户分类

J. J. Li, D. Weiss
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引用次数: 0

摘要

测试一直是软件开发中不可或缺的一部分。随着测试量的增加,测试产生的数据和信息的数量也在大幅增长。除了传统的覆盖和调试之外,还出现了如何利用测试数据的问题。本文提出了一种利用软件应用程序的测试跟踪数据对其运行时用户进行分类的方法。它收集软件工具所研究的程序的测试执行跟踪,并从跟踪信息中派生出不同类别的内部度量。在运行期间,我们查看用户的工件以及用户的行为,将它们分类到预定的组中,并相应地为它们提供服务。我们正在进行的工作是将此方法应用于软件产品线PolyFlow,包括生成、运行和分析所研究程序的测试用例的web服务。我们的方法的一个好处是它不需要存储用户配置文件。
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Using testing trace for automatic user categorization
Testing has always been an indispensable part of software development. With the increasing amount of testing, the volume of data and information generated from testing grows substantially. The question arises on how to take advantage of the testing data, besides traditional coverage and debugging. In this paper, we propose an approach of using test trace data of a software application to its run-time user categorization. It collects test execution trace of programs studied by the software tool, and derives internal metrics of different categories from the trace information. During run time, we look at the user's artifacts as well as the user's behavior to categorize them into predetermined groups and serve them accordingly. Our work in-progress is to apply this method to a software product line, PolyFlow, including a web service that generates, runs, and analyzes test cases of programs under study. One benefit of our method is that it does not require storage of user profiles.
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