  Recent research has begun to examine the potential of automatically finding
and fixing accessibility issues that manifest in software. However, while
recent work makes important progress, it has generally been skewed toward
identifying issues that affect users with certain disabilities, such as those
with visual or hearing impairments. However, there are other groups of users
with different types of disabilities that also need software tooling support to
improve their experience. As such, this paper aims to automatically identify
accessibility issues that affect users with motor-impairments.
  To move toward this goal, this paper introduces a novel approach, called
MotorEase, capable of identifying accessibility issues in mobile app UIs that
impact motor-impaired users. Motor-impaired users often have limited ability to
interact with touch-based devices, and instead may make use of a switch or
other assistive mechanism -- hence UIs must be designed to support both limited
touch gestures and the use of assistive devices. MotorEase adapts computer
vision and text processing techniques to enable a semantic understanding of app
UI screens, enabling the detection of violations related to four popular,
previously unexplored UI design guidelines that support motor-impaired users,
including: (i) visual touch target size, (ii) expanding sections, (iii)
persisting elements, and (iv) adjacent icon visual distance. We evaluate
MotorEase on a newly derived benchmark, called MotorCheck, that contains 555
manually annotated examples of violations to the above accessibility
guidelines, across 1599 screens collected from 70 applications via a mobile app
testing tool. Our experiments illustrate that MotorEase is able to identify
violations with an average accuracy of ~90%, and a false positive rate of less
than 9%, outperforming baseline techniques.
