Mining reading patterns from eye-tracking data: method and demonstration

Constantina Ioannou, Indira Nurdiani, Andrea Burattin, Barbara Weber

Research output: Contribution to journalJournal articleResearchpeer-review

228 Downloads (Pure)


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.

Original languageEnglish
JournalSoftware and Systems Modeling
Pages (from-to)345–369
Publication statusPublished - 2020


  • Process mining
  • Eye-tracking
  • Reading patterns
  • Source code
  • Behavior driven development


Dive into the research topics of 'Mining reading patterns from eye-tracking data: method and demonstration'. Together they form a unique fingerprint.

Cite this