  Trust in digital systems depends on secure hardware, often assured through
Hardware Reverse Engineering (HRE). This work develops methods for
investigating human problem-solving processes in HRE, an underexplored yet
critical aspect. Since reverse engineers rely heavily on visual information,
eye tracking holds promise for studying their cognitive processes. To gain
further insights, we additionally employ verbal thought protocols during and
immediately after HRE tasks: Concurrent and Retrospective Think Aloud. We
evaluate the combination of eye tracking and Think Aloud with 41 participants
in an HRE simulation. Eye tracking accurately identifies fixations on
individual circuit elements and highlights critical components. Based on two
use cases, we demonstrate that eye tracking and Think Aloud can complement each
other to improve data quality. Our methodological insights can inform future
studies in HRE, a specific setting of human-computer interaction, and in other
problem-solving settings involving misleading or missing information.
