US 12,229,390 B2
Detecting keyboard accessibility issues in web applications
Paul Chiou, Los Angeles, CA (US); Ali Alotaibi, Los Angeles, CA (US); and William Halfond, Los Angeles, CA (US)
Assigned to UNIVERSITY OF SOUTHERN CALIFORNIA, Los Angeles, CA (US)
Filed by University of Southern California, Los Angeles, CA (US)
Filed on Jan. 29, 2024, as Appl. No. 18/425,743.
Application 18/425,743 is a continuation in part of application No. 17/891,695, filed on Aug. 19, 2022, granted, now 11,886,648, issued on Jan. 30, 2024.
Claims priority of provisional application 63/235,559, filed on Aug. 20, 2021.
Prior Publication US 2024/0192837 A1, Jun. 13, 2024
Int. Cl. G06F 3/0484 (2022.01); G06F 3/023 (2006.01); G06F 16/957 (2019.01)
CPC G06F 3/0484 (2013.01) [G06F 3/023 (2013.01); G06F 16/9577 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for detecting keyboard accessibility failures (KAFs), the method comprising:
reading a document object model of a web page;
generating, via a processor of a computing system, a keyboard navigation flow model from the document object model of the web page based on interactions of a user with the web page, wherein the keyboard navigation flow model includes states representing user interfaces displayed by the web page, nodes representing keyboard inputs in the states, and edges representing transitions that occur in the web page between the nodes;
detecting one or more KAFs based on an analysis of the keyboard navigation flow model; and
producing a report of the detected one or more KAFs on the web page.