VLDB 2026 Research / reviewers in the wild / expert
Yuki Fushihara
dblp:365/6185
· DBLP profile ↗
2ranked-venue papers
2as first author
2since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 2 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 2 first-author · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Fault-Proneness of Python Programs Tested By Smelled Test CodeabstractSoftware testing is one of the most crucial quality assurance activities, and test results are of great concern to software developers. However, the quality assurance of the test code (test case) itself also becomes critical because a poor-quality test case may fail to detect latent faults and give developers false comfort regarding the test result. A code smell threatening test code quality has been studied as “test smell.” This paper conducts an investigation of test smells in 775 Python open-source programs and reports the results of a quantitative analysis regarding whether test smells impact the fault-proneness of the product code under test. The analysis results show the following two findings. (1) When a test code has one of the reported ten kinds of test smells, the production code under test is more fault- prone than the others. (2) The fault-proneness of a production code tends to get higher when the corresponding test code has two or more different kinds of test smells-over 75% of test smell combinations showed such a trend of increasing the risk of being faulty production code. Yuki Fushihara, Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, Minoru Kawahara |
SEAA | 1 |
| 2023 | A Trend Analysis of Test Smells in Python Test Code Over Commit HistoryabstractSoftware testing is an essential activity for developing and maintaining high-quality software. Unit testing with test code (test cases) is a fundamental testing activity, and developers can test their production code whenever they create or modify the code. However, such quality assurance relies on the correctness of the test code. If a test code had a flaw, it would mislead the developers about the hidden faults and prevent early detection of the faults. This paper focuses on "test smells," which may cause test code flaws in Python programs, and analyzes their changing trends over commit history (code changes) toward better Python test code management. Through an empirical data analysis of 100 open-source projects, the paper reports the following findings: (1) a few kinds of test smells constitute the majority of smells detected in the studied projects, and (2) most kinds of smells tend to increase over commits, i.e., many test smells are likely to have remained in test code as technical debt. Yuki Fushihara, Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, Minoru Kawahara |
SEAA | 1 |