This paper presents eye2vec, an infrastructure for analyzing software developers' eye movements while reading source code. In common eye-tracking studies in program comprehension, researchers must preselect analysis targets such as control flow or syntactic elements, and then develop analysis methods to extract appropriate metrics from the fixation for source code. Here, researchers can define various levels of AOIs like words, lines, or code blocks, and the difference leads to different results. Moreover, the interpretation of fixation for word/line can vary across the purposes of the analyses. Hence, the eye-tracking analysis is a difficult task that depends on the time-consuming manual work of the researchers. eye2vec represents continuous two fixations as transitions between syntactic elements using distributed representations. The distributed representation facilitates the adoption of diverse data analysis methods with rich semantic interpretations.

翻译：本文提出eye2vec，一种用于分析软件开发人员阅读源代码时眼动行为的基础框架。在程序理解领域的常规眼追踪研究中，研究者需要预先选定分析目标（如控制流或句法元素），并开发相应分析方法从注视数据中提取针对源代码的度量指标。在此过程中，研究者可定义不同层级的兴趣区域（如单词、代码行或代码块），而不同定义方式会导致相异的研究结果。此外，针对单词/代码行的注视数据解释也会因分析目的的不同而产生差异。因此，眼动分析是一项依赖研究者耗时性人工操作的困难任务。eye2vec通过分布式表示将连续两次注视点转化为句法元素间的转移关系。这种分布式表示有助于采用具有丰富语义解释的多样化数据分析方法。