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Davin Win Kyi

dblp:415/4189 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0006-8030-5024ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Accessibility and assistive technology · 100%
Software engineering, system software, and programming languages
1 paper
Software testing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Accessibility and assistive technology › mobile accessibility
mobile app accessibility
1.012026
TaskAudit: Detecting Functiona11ity Errors in Mobile Apps via Agentic Task Execution · CHI 2026
Software testing › automated testing
automated accessibility testing
0.312026
TaskAudit: Detecting Functiona11ity Errors in Mobile Apps via Agentic Task Execution · CHI 2026

Methods — techniques the papers use, named apart from their topics

screen reader proxy · 2.0agentic task execution · 2.0
YearPublicationVenuePosition
2026 TaskAudit: Detecting Functiona11ity Errors in Mobile Apps via Agentic Task Execution
abstract
Accessibility checkers are tools in support of accessible app development, and their use is encouraged by accessibility best practices. However, most current checkers evaluate static or mechanically-generated contexts, failing to capture common accessibility errors impacting mobile app functionality. In this work, we define functiona11ity errors as accessibility barriers that only manifest through interaction (i.e., named according to a blend of "functionality" and "accessibility"). We introduce TaskAudit, which comprises three components: a Task Generator that constructs interactive tasks from app screens, a Task Executor that uses agents with a screen reader proxy to perform these tasks, and an Accessibility Analyzer that detects and reports accessibility errors by examining interaction traces. Our evaluation on real-world apps shows that TaskAudit detects 48 functiona11ity errors from 54 app screens, compared to between 4 and 20 with existing checkers. Our analysis demonstrates common error patterns that TaskAudit can detect in addition to those from prior work, including label-functionality mismatch, cluttered navigation, and inappropriate feedback.
Mingyuan Zhong 0001, Davin Win Kyi, James Fogarty, Jacob O. Wobbrock
CHI3