Demo Data from VLDB 2026 / reviewers in the wild / expert
Guoyao Wen
dblp:360/7436
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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.
| 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 |
|---|---|---|---|---|
Software testing
test maintenance |
0.7 | 1 | 2023 | Automated Fixing of Web UI Tests via Iterative Element Matching · ASE 2023 |
Software testing
test repair |
0.7 | 1 | 2023 | Automated Fixing of Web UI Tests via Iterative Element Matching · ASE 2023 |
Methods — techniques the papers use, named apart from their topics
iterative matching algorithm · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Automated Fixing of Web UI Tests via Iterative Element MatchingabstractWeb UI test cases are used for the automatic testing of web applications. When a web application is updated, these UI tests should also be updated for regression testing of the new version of web application. With the rapid evolution, updating UI tests is a tedious and time-consuming task. To solve these problems, automatically repairing web UI tests has gained increasing attention recently. To repair web UI tests, the most important step is to match the UI elements before and after the web page update. Existing work matches UI elements according to visual information, attributes value, or Document Object Model (DOM) structures. However, they either achieve low element matching accuracy or only work on simple UI tests. To solve these problems, we proposed UITestFix, an approach based on a novel iterative matching algorithm for improving the accuracy of matching UI elements. UITestFix is designed based on two main insights: (1) beyond attribute and DOM structures, the relations between different elements can also guide the matching process, and (2) the matching results of previous iterations could guide the matching of the current iteration. Our evaluation of publicly available datasets and two industrial apps shows that UITestFix outperforms four existing approaches by achieving more accurate element matching and producing more correct fixes. Yuanzhang Lin, Guoyao Wen, Xiang Gao 0012 |
ASE | 2 |