Many investigations in empirical software engineering look at sequences of data resulting from development or management processes. In this paper, we propose an analytical approach called the Gandhi-Washington Method (GWM) to investigate the impact of recurring events in software projects. GWM takes an encoding of events and activities provided by a software analyst as input. It uses regular expressions to automatically condense and summarize information and infer treatments. Relating the treatments to the outcome through statistical tests, treatment-outcome constructs are automatically mined from the data. The output of GWM is a set of treatment-outcome constructs. Each treatment in the set of mined constructs is significantly different from the other treatments considering the impact on the outcome and/or is structurally different from other treatments considering the sequence of events. We describe GWM and classes of problems to which GWM can be applied. We demonstrate the applicability of this method for empirical studies on sequences of file editing, code ownership, and release cycle time.

中文翻译：

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从顺序软件工程数据挖掘处理结果构造

经验软件工程中的许多研究着眼于开发或管理过程产生的数据序列。在本文中，我们提出了一种称为 Gandhi-Washington 方法 (GWM) 的分析方法来调查软件项目中重复发生的事件的影响。GWM 将软件分析师提供的事件和活动编码作为输入。它使用正则表达式自动压缩和汇总信息并推断处理。通过统计测试将治疗与结果相关联，自动从数据中挖掘治疗结果结构。GWM 的输出是一组治疗结果结构。考虑到对结果的影响，挖掘构造集中的每个处理都与其他处理显着不同，和/或考虑到事件的顺序，在结构上与其他处理不同。我们描述了 GWM 和可以应用 GWM 的问题类别。我们证明了这种方法对文件编辑序列、代码所有权和发布周期时间的实证研究的适用性。