Demo Data from EDBT 2026 / reviewers in the wild / expert
Davin Win Kyi
dblp:415/4189
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Accessibility and assistive technology › mobile accessibility
mobile app accessibility |
1.0 | 1 | 2026 | TaskAudit: Detecting Functiona11ity Errors in Mobile Apps via Agentic Task Execution · CHI 2026 |
Software testing › automated testing
automated accessibility testing |
0.3 | 1 | 2026 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | TaskAudit: Detecting Functiona11ity Errors in Mobile Apps via Agentic Task ExecutionabstractAccessibility 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 |
CHI | 3 |