Demo Data from SIGIR 2026 / reviewers in the wild / expert
Masayuki Taniguchi
dblp:311/8829
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2021
—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 · 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 · 50% Software maintenance and evolution · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing
test smell detection |
0.5 | 1 | 2021 | JTDog: a Gradle Plugin for Dynamic Test Smell Detection · ASE 2021 |
Methods — techniques the papers use, named apart from their topics
dynamic analysis · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | JTDog: a Gradle Plugin for Dynamic Test Smell DetectionabstractThe concept of the test smell represents potential problems with the readability and maintainability of the test code. Common test smells focus on static aspects of the source code, such as code length and complexity. These are easy to detect and do not cause problems in terms of test execution. On the other hand, dynamic smells, which are based on test runtime behavior, lead to misunderstanding of the test results. For example, rotten green tests give developers the false impression that the test was passed without any problems, even though the test was poorly executed. Therefore, we should detect dynamic smells and take countermeasures as early as possible through the development. In this paper, we introduce JTDog, a Gradle plugin for dynamic smell detection. JTDog has high portability due to its integration into the build tool. We applied JTDog to 150 projects on GitHub and confirmed that the JTDog plugin has high portability. In addition, JTDog detected 958 dynamic smells in 55 projects. JT-Dog is available at https://github.com/kusumotolab/JTDog, and the demo video is available at https://youtu.be/t374HYMCavI. Masayuki Taniguchi, Shinsuke Matsumoto, Shinji Kusumoto |
ASE | 1 |