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：分类法以简洁方式捕获特定领域的知识，并建立同行间的共同理解。研究者利用分类法传递特定知识领域信息或支持自动化任务，实践者则借助其实现跨组织边界的沟通。目的：尽管分类法在软件工程领域扮演重要角色，但其质量评估却鲜有涉及。本文旨在识别并定义可提供可量化指标的分类法质量属性，帮助研究者和实践者比较不同分类法，选择最适用于当前任务的方案。方法：我们梳理了软件工程与信息系统研究领域的324篇文献，综合提炼其中关于质量属性及其测量方法的定义。并在三个领域的六种分类法上评估了测量方法的有效性。结果：我们提出七项质量属性的定义，并建议采用内部与外部测量的方法来评估分类法质量。其中两项测量方法提供了Python实现。研究发现这些测量有助于判定何种分类法最适合特定场景。结论：尽管已有若干分类法创建指南，但缺乏可操作的标准来比较分类法。本文通过综合大量文献，提出七项互不重叠的分类法质量属性及对应测量方法，填补了这一空白。未来工作将包括对其实用性的进一步评估与实证验证。