Crystalline: Lowering the Cost for Developers to Collect and Organize Information for Decision Making
Crystalline: Lowering the Cost for Developers to Collect and Organize Information for Decision Making
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DOI：
10.1145/3491102.3501968
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发表时间：
2022-02
期刊：
影响因子：
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通讯作者：
Michael Xieyang Liu;A. Kittur;B. Myers
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文献类型：
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作者：
Michael Xieyang Liu;A. Kittur;B. Myers
开发人员每天都要进行在线意义分析，比如研究和选择库和api。先前的研究引入了一些工具，帮助开发人员从各种来源获取信息，并将其组织成对后续决策有用的结构。然而，对于开发人员来说，手动识别和剪辑内容、维护其来源并将其与其他内容合成仍然是一个费力的过程。在这项工作中，我们引入了一个名为crystal的新系统，该系统可以在用户搜索和浏览网页时自动收集和组织信息到表格结构中。它利用自然语言处理自动将相似的标准分组在一起，以减少混乱，并使用被动行为信号（如鼠标移动和停留时间）来推断需要收集哪些信息，以及如何将其可视化并确定优先级。我们的用户研究表明，在不牺牲表质量的情况下，开发人员创建比较表的速度可以提高20%，操作成本可以降低60%。
Developers perform online sensemaking on a daily basis, such as researching and choosing libraries and APIs. Prior research has introduced tools that help developers capture information from various sources and organize it into structures useful for subsequent decision-making. However, it remains a laborious process for developers to manually identify and clip content, maintaining its provenance and synthesizing it with other content. In this work, we introduce a new system called Crystalline that automatically collects and organizes information into tabular structures as the user searches and browses the web. It leverages natural language processing to automatically group similar criteria together to reduce clutter, and uses passive behavioral signals such as mouse movement and dwell time to infer what information to collect and how to visualize and prioritize it. Our user study suggests that developers are able to create comparison tables about 20% faster with a 60% reduction in operational cost without sacrificing the quality of the tables.