基于CharmFL的Python交互式故障定位

Attila Szatmári, Q. Sarhan, Árpád Beszédes
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引用次数: 3

摘要

我们为PyCharm IDE提供了一个名为“CharmFL”的插件。它采用基于谱的故障定位(Spectrum-based Fault Localization)来自动分析Python程序,并生成潜在故障程序元素(即语句、函数等)的排序列表。我们的工具提供了先进的功能,例如,它允许用户对可疑元素给出反馈,以帮助重新排列它们,从而改进故障定位过程。该工具利用了与频谱数据互补的程序元素的上下文信息。用户可以在失败的测试期间浏览函数调用图。因此,他们可以调查任何失败测试用例的数据流轨迹,或者为故障的位置构建因果推理模型。该工具已与一组实验性用例一起使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive fault localization for Python with CharmFL
We present a plug-in called “CharmFL” for the PyCharm IDE. It employs Spectrum-based Fault Localization to automatically analyze Python programs and produces a ranked list of potentially faulty program elements (i.e., statements, functions, etc.). Our tool offers advanced features, e.g., it enables the users to give their feedback on the suspicious elements to help re-rank them, thus improving the fault localization process. The tool utilizes contextual information about program elements complementary to the spectrum data. The users can explore function call graphs during a failed test. Thus they can investigate the data flow traces of any failed test case or construct a causal inference model for the location of the fault. The tool has been used with a set of experimental use cases.
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