Introduction: Taxonomies capture knowledge about a particular domain in a succinct manner and establish a common understanding among peers. Researchers use taxonomies to convey information about a particular knowledge area or to support automation tasks, and practitioners use them to enable communication beyond organizational boundaries. Aims: Despite this important role of taxonomies in software engineering, their quality is seldom evaluated. Our aim is to identify and define taxonomy quality attributes that provide practical measurements, helping researchers and practitioners to compare taxonomies and choose the one most adequate for the task at hand. Methods: We reviewed 324 publications from software engineering and information systems research and synthesized, when provided, the definitions of quality attributes and measurements. We evaluated the usefulness of the measurements on six taxonomies from three domains. Results: We propose the definition of seven quality attributes and suggest internal and external measurements that can be used to assess a taxonomy's quality. For two measurements we provide implementations in Python. We found the measurements useful for deciding which taxonomy is best suited for a particular purpose. Conclusion: While there exist several guidelines for creating taxonomies, there is a lack of actionable criteria to compare taxonomies. In this paper, we fill this gap by synthesizing from a wealth of literature seven, non-overlapping taxonomy quality attributes and corresponding measurements. Future work encompasses their further evaluation of usefulness and empirical validation.

翻译：引言：分类法以简洁的方式捕获特定领域的知识，并建立同行间的共同理解。研究人员利用分类法传达特定知识领域的信息或支持自动化任务，实践者则借助它们实现跨组织边界的沟通。目标：尽管分类法在软件工程中扮演重要角色，但其质量很少被评估。我们的目标是识别并定义能提供实用度量的分类法质量属性，帮助研究人员和实践者比较分类法，并选择最适合当前任务的那一个。方法：我们回顾了软件工程和信息系统的324篇出版物，综合其中提供的质量属性定义和度量方法。我们还基于三个领域的六个分类法评估了这些度量的实用性。结果：我们提出了七个质量属性的定义，并建议了可用于评估分类法质量的内部和外部度量方法。其中有两个度量方法提供了Python实现。我们发现这些度量方法有助于确定特定目的下最合适的分类法。结论：虽然存在若干分类法创建指南，但缺乏可操作的准则来比较分类法。本文通过综合大量文献，提出了七个互不重叠的分类法质量属性及其对应度量，填补了这一空白。未来工作包括进一步评估这些度量的实用性并进行实证验证。