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Massachusetts Institute of Technology

Bility : automated accessibility testing for mobile applications

Abstract

dc:description.abstract

In this thesis, I designed and implemented a testing framework, called Bility, to assess the accessibility of mobile applications. Implemented in Java and Kotlin, this framework automatically navigates through an application, finding both dynamic and static accessibility issues. I developed techniques for unique view detection, automatically building a representation of the dynamic behavior of an application, and making navigation decisions based on application state and history in order to find these accessibility issues. I compared Bility's ability to detect issues against existing tools such as the Google Accessibility Scanner. I found that Bility performs significantly better and is able to detect additional static issues, as well as discover dynamic accessibility issues that current tools do not detect.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Vontell, Aaron Richard.
Advisor dc:contributor.advisor
  • Lalana Kagal.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/121685
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/121685

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Vontell, Aaron Richard.. Bility : automated accessibility testing for mobile applications. Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121685