Inadequate documentation of software design has been known to be a barrier for developers. Interestingly, several relevant object-oriented systems have their design documented using key classes, which are meant to represent key concepts of the systems. In order to fill the gap of under-documented design, we present Keecle, an approach for detecting a predefined number of key classes in a semi-automatic way. The main challenge is to reduce the space of potentially thousands of classes to just a few representatives of the main concepts of a system, while maintaining high precision. The approach is evaluated with 13 systems in order to assess its correctness. The ground-truth is obtained either from the original documentation, or from third-party, or from the respective developers. The results were analyzed in terms of precision and recall, and have shown to be superior compared to the state-of-the-art approach. In order to evaluate if key classes are more critical from the design point of view, we evaluated whether they are associated with cohesion and coupling metrics. We found that although key classes, in general, are critical from the point of view of design, there are other classes that are also critical, suggesting that being aware of key classes encompass information not available in structural metrics, and could be useful as a additional facet for design assessment.

中文翻译：

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面向对象系统中的关键类：检测和评估

众所周知，软件设计的文档不足是开发人员的障碍。有趣的是，一些相关的面向对象系统的设计使用关键类来记录，这些类旨在表示系统的关键概念。为了填补文档不足的设计空白，我们提出了 Keecle，这是一种以半自动方式检测预定义数量的关键类的方法。主要挑战是将潜在的数千个类的空间减少到仅代表系统主要概念的几个代表，同时保持高精度。该方法使用 13 个系统进行评估，以评估其正确性。基本事实可以从原始文档、第三方或各自的开发人员那里获得。对结果进行了准确率和召回率的分析，并且与最先进的方法相比已显示出优越性。为了从设计的角度评估关键类是否更关键，我们评估了它们是否与内聚和耦合指标相关联。我们发现，虽然从设计的角度来看，关键类通常是至关重要的，但还有其他类也很关键，这表明了解关键类包含结构度量中不可用的信息，并且可以作为有用的设计评估的附加方面。