AI 中文总结
本研究通过众包与访谈实验发现，文本数据序列化格式的可用性更多由周边生态而非语法决定，HJSON、YAML的优势在实际复杂场景中消失。
AI 中文摘要
JSON、XML等文本数据序列化格式应用广泛，支撑软件配置、数据表格化等任务，但学界对其可用性知之甚少，不清楚何种因素决定格式优劣，是否存在认知效率最优的格式。本研究通过215人的众包实验与9人的半结构化访谈探究上述问题，发现缩进与大括号等格式差异未始终转化为显著可用性差异；HJSON、YAML在特定修改任务中表现优于其他格式，但在任务复杂度极低或极高的更贴近实际的场景中，该优势消失。研究还发现，可用性更多由社会技术生态系统驱动，格式周边的工具、文档与社区实践比语法更重要。
英文摘要
Textual data serialization formats, such as JSON or XML, are ubiquitous, supporting tasks like software configuration and data tabularization. Despite their prominence, little is known about their usability. What makes one good or bad? Is there a best one for cognitive efficiency? We explore these questions via a (N=215) crowd work study and a (N=9) semi-structured interview study. We find that format distinctions (like indentation versus curly braces) do not consistently translate into substantial usability differences. While HJSON and YAML performed better than other formats in certain modification tasks, these advantages disappeared in more realistic settings where task complexity was either trivial or highly demanding. Instead, usability appears driven by sociotechnical ecosystems: the tooling, documentation, and community practices surrounding a format matter more than syntax.
