Detecting the presence of project management anti-patterns (AP) currently requires experts on the matter and is an expensive endeavor. Worse, experts may introduce their individual subjectivity or bias. Using the Fire Drill AP, we first introduce a novel way to translate descriptions into detectable AP that are comprised of arbitrary metrics and events such as logged time or maintenance activities, which are mined from the underlying source code or issue-tracking data, thus making the description objective as it becomes data-based. Secondly, we demonstrate a novel method to quantify and score the deviations of real-world projects to data-based AP descriptions. Using nine real-world projects that exhibit a Fire Drill to some degree, we show how to further enhance the translated AP. The ground truth in these projects was extracted from two individual experts and consensus was found between them. Our evaluation spans four kinds of patterns, where the first is purely derived from description, the second type is enhanced by data, and the third kind is derived from data only. The fourth type then is a derivative meta-process pattern. The Fire Drill AP as translated from description only for either, source code- or issue-tracking-based detection, shows weak potential of confidently detecting the presence of the anti-pattern in a project. Enriching the AP with data from real-world projects significantly improves detection. Using patterns derived from data only leads to almost perfect correlations of the scores with the ground truth. Some APs share symptoms with the Fire Drill AP, and we conclude that the presence of similar patterns is most certainly detectable. Furthermore, any pattern that can be characteristically modeled using the proposed approach is potentially well detectable.
翻译:检测项目管理反模式(AP)的存在,目前需要这方面的专家,这是一项昂贵的工作。更糟糕的是,专家可能会引入他们个人的主观性或偏向性。我们首先采用一种新颖的方法,将描述转化为可探测的AP,由任意的计量和事件组成,如记录的时间或维护活动,这些活动来自源代码或问题跟踪数据,因此描述的目标成为基于数据的数据。第二,我们展示了一种新颖的方法来量化真实世界项目与基于数据的AP描述的偏差并分。使用9个显示某种程度的 Fire Drill 的真实世界项目,我们展示了如何进一步加强翻译的AP。这些项目的地面真相来自两名专家,并且他们之间也取得了共识。我们的评估范围有四种模式,其中第一个纯粹来自描述,第二个类型由数据增强,而第三个类型仅来自数据。第四类是衍生的元程序模式。然后是衍生出来的Fireal Drill AP,从描述中翻译出的一种模式, 仅用于几乎源代码共享的代码共享,或者问题跟踪项目中发现了一种潜在的真实性。我们从源代码检测中可以很好地探测到精确的路径项目。