Feature Selections for Effectively Localizing Faulty Events in GUI Applications

Feature Selections for Effectively Localizing Faulty Events in GUI Applications
复制标题

用于有效定位 GUI 应用程序中的故障事件的功能选择

DOI:
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发表时间:
2014
期刊:
International Conference on Machine Learning and Applications
影响因子:
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通讯作者:
A. Namin
A. Namin
中科院分区:
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文献类型:
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作者:
Xiaozhen Xue;Yulei Pang;A. Namin

文献摘要

被引文献

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由于故障因果关系复杂以及测试用例的特殊性,GUI(图形用户界面)应用程序中的故障很难定位。本文采用特征选择算法来定位给定程序中与 GUI 相关的故障。特征被定义为所执行事件的子序列。通过采用统计特征排名技术,可以根据负责表现出错误行为的事件的可疑性对事件进行排名。然后,在实现(事件处理)底层事件的给定源代码中定义的功能按可疑性顺序进行排名。基于一些开源Java项目对所提出的技术的评估验证了这种基于特征选择的故障定位技术对于GUI应用程序的有效性。
Due to the complex causality of failure and the special characteristics of test cases, the faults in GUI (Graphic User Interface) applications are difficult to localize. This paper adapts feature selection algorithms to localize GUI-related faults in a given program. Features are defined as the subsequences of events executed. By employing statistical feature ranking techniques, the events can be ranked by the suspiciousness of events being responsible to exhibit faulty behavior. The features defined in a given source code implementing (event handle) the underlying event are then ranked in suspiciousness order. The evaluation of the proposed technique based on some open source Java projects verified the effectiveness of this feature selection based fault localization technique for GUI applications.