EDBT 2026 Demo / reviewers in the wild / expert
Jiale Amber Wang
dblp:391/0972
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 first-author · 2 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 · 91% Software maintenance and evolution · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › test coverage
code coverage |
0.8 | 1 | 2024 | Efficient Incremental Code Coverage Analysis for Regression Test Suites · ASE 2024 |
Software testing
regression testing |
0.8 | 1 | 2024 | Efficient Incremental Code Coverage Analysis for Regression Test Suites · ASE 2024 |
Software testing › regression testing
regression test selection |
0.8 | 1 | 2024 | Efficient Incremental Code Coverage Analysis for Regression Test Suites · ASE 2024 |
Software maintenance and evolution › release engineering
continuous integration |
0.2 | 1 | 2024 | Efficient Incremental Code Coverage Analysis for Regression Test Suites · ASE 2024 |
Methods — techniques the papers use, named apart from their topics
incremental analysis · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | An empirical study of developers' challenges in implementing Workflows as Code: A case study on Apache Airflow
Jerin Yasmin, Jiale Amber Wang, Yuan Tian 0008, Bram Adams |
J. Syst. Softw. | 2 |
| 2024 | Efficient Incremental Code Coverage Analysis for Regression Test SuitesabstractCode coverage analysis has been widely adopted in the continuous integration of open-source and industry software repositories to monitor the adequacy of regression test suites. However, computing code coverage can be costly, introducing significant overhead during test execution. Plus, re-collecting code coverage for the entire test suite is usually unnecessary when only a part of the coverage data is affected by code changes. While regression test selection (RTS) techniques exist to select a subset of tests whose behaviors may be affected by code changes, they are not compatible with code coverage analysis techniques---that is, simply executing RTS-selected tests leads to incorrect code coverage results. Jiale Amber Wang, Pengyu Nie 0001 |
ASE | 1 |