Understanding how developers interact with different software artifacts when performing comprehension tasks has a potential to improve developers’ productivity. In this paper, we propose a method to analyze eye-tracking data using process mining to find distinct reading patterns of how developers interacted with the different artifacts. To validate our approach, we conducted an exploratory study using eye-tracking involving 11 participants. We applied our method to investigate how developers interact with different artifacts during domain and code understanding tasks. To contextualize the reading patterns and to better understand the perceived benefits and challenges participants associated with the different artifacts and their choice of reading patterns, we complemented the eye-tracking data with the data obtained from think aloud. The study used behavior-driven development, a development practice that is increasingly used in Agile software development contexts, as a setting. The study shows that our method can be used to explore developers’ behavior at an aggregated level and identify behavioral patterns at varying levels of granularity.

中文翻译：

---

从眼动数据中挖掘阅读模式：方法和演示

在执行理解任务时了解开发人员如何与不同的软件工件进行交互可能会提高开发人员的生产力。在本文中，我们提出了一种使用过程挖掘来分析眼动数据的方法，以发现开发人员如何与不同工件交互的独特阅读模式。为了验证我们的方法，我们使用11名参与者的眼动追踪进行了探索性研究。我们应用了我们的方法来研究开发人员在域和代码理解任务期间如何与不同工件交互。为了对阅读模式进行语境化并更好地理解与不同工件相关的参与者的感知收益和挑战以及他们对阅读模式的选择，我们用从大声思考中获得的数据对眼动数据进行了补充。这项研究使用了行为驱动的开发作为背景，这种行为开发是一种在敏捷软件开发环境中越来越多地使用的开发实践。研究表明，我们的方法可用于探索开发人员在聚合级别上的行为，并识别不同粒度级别的行为模式。