VITALSE: visualizing eye tracking and biometric data
VITALSE: visualizing eye tracking and biometric data
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VITALSE：可视化眼动追踪和生物识别数据
DOI：
10.1145/3377812.3382154
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Arnaoudova, Venera
中科院分区：
文献类型：
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作者：
Roy, Devjeet;Fakhoury, Sarah;Arnaoudova, Venera
经验软件工程的最新研究正在应用神经认知科学的技术，并在研究人员可以建模和分析开发人员与软件工件交互时的认知过程的方式上开辟了新的领域。然而，鉴于这一研究领域的新奇，只有一种工具可以帮助研究人员表示和分析这种多模态生物特征数据。虽然该工具确实有助于可视化时间眼动追踪和生理数据，但它不允许将生理数据映射到源代码元素，而是将信息投影到代码图像上。这样做的一个缺点是，研究人员仍然无法有意义地联合收割机并将生理和眼睛跟踪数据映射到源代码工件。图像的使用也禁止了对长或多个代码文件的支持，这阻止了研究人员分析在现实环境中进行的实验数据。为了解决这些缺点，我们提出了VITALSE，软件工程任务相结合的多模态生物特征数据的交互式可视化工具。VITALSE提供交互式和可定制的时间热图，这些热图是通过同步的眼动追踪和生物特征数据创建的。该工具支持对多个文件进行分析，用户定义源代码元素上的兴趣点注释，以及提供数据集的高级可定制指标摘要。VITALSE是一个视频演示，演示其功能的样本数据可以在http://www.vitalse.app上找到。
Recent research in empirical software engineering is applying techniques from neurocognitive science and breaking new grounds in the ways that researchers can model and analyze the cognitive processes of developers as they interact with software artifacts. However, given the novelty of this line of research, only one tool exists to help researchers represent and analyze this kind of multi-modal biometric data. While this tool does help with visualizing temporal eyetracking and physiological data, it does not allow for the mapping of physiological data to source code elements, instead projecting information over images of code. One drawback of this is that researchers are still unable to meaningfully combine and map physiological and eye tracking data to source code artifacts. The use of images also bars the support of long or multiple code files, which prevents researchers from analyzing data from experiments conducted in realistic settings. To address these drawbacks, we propose VITALSE, a tool for the interactive visualization of combined multi-modal biometric data for software engineering tasks. VITALSE provides interactive and customizable temporal heatmaps created with synchronized eyetracking and biometric data. The tool supports analysis on multiple files, user defined annotations for points of interest over source code elements, and high level customizable metric summaries for the provided dataset. VITALSE, a video demonstration, and sample data to demonstrate its capabilities can be found at http://www.vitalse.app.