Demo Data from VLDB 2026 / reviewers in the wild / expert
Chenqian Zhu
dblp:282/6661
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › test optimization
test recommendation |
0.4 | 1 | 2020 | HomoTR: Online Test Recommendation System Based on Homologous Code Matching · ASE 2020 |
Software testing
test reuse |
0.1 | 1 | 2020 | HomoTR: Online Test Recommendation System Based on Homologous Code Matching · ASE 2020 |
Software testing › test generation
unit test generation |
0.1 | 1 | 2020 | HomoTR: Online Test Recommendation System Based on Homologous Code Matching · ASE 2020 |
Methods — techniques the papers use, named apart from their topics
code homology measurement · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | HomoTR: Online Test Recommendation System Based on Homologous Code MatchingabstractA growing number of new technologies are used in test development. Among them, automatic test generation, a promising technology to improve the efficiency of unit testing, currently performs not satisfactory in practice. Test recommendation, like code recommendation, is another feasible technology for supporting efficient unit testing and gets increasing attention. In this paper, we develop a novel system, namely HomoTR, which implements online test recommendations by measuring the homology of two methods. If the new method under test shares homology with an existing method that has test cases, HomoTR will recommend the test cases to the new method. The preliminary experiments show that HomoTR can quickly and effectively recommend test cases to help the developers improve the testing efficiency. Besides, HomoTR has been integrated into the MoocTest platform successfully, so it can also execute the recommended test cases automatically and visualize the testing results (e.g., Branch Coverage) friendly to help developers understand the process of testing. The demo video of HomoTR can be found at https://youtu.be/_227EfcUbus. Chenqian Zhu, Weisong Sun, Qin Liu 0002, Yangyang Yuan, Chunrong Fang |
ASE | 1 |