VLDB 2026 Research / reviewers in the wild / expert
Yuki Noyori
dblp:202/5073
· DBLP profile ↗
3ranked-venue papers
1as first author
2since 2021 · last 2024
0009-0003-1811-660XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 3 · 1 first-author · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Unraveling the Influences on Bug Fixing Time: A Comparative Analysis of Causal Inference ModelabstractIn this study, we employ causal inference models, specifically Bayesian Networks (BN) and Linear Non-Gaussian Acyclic Models (LiNGAM), to investigate the determinants of Bug Fixing Time (BFT) in software development. Moving beyond traditional statistical analyses, our approach aims to identify the true causal factors influencing BFT. Our findings indicate that ’Reporter Reputation’, ’Severity’, and ’Blocker’ status are significant determinants of BFT, with notable differences between bugs reported by users versus developers. This research challenges existing assumptions about the necessity of comprehensive bug reports and underscores the importance of understanding bug resolution’s complexity and organizational context. By applying causal inference models, we offer actionable insights for improving bug prioritization, operational efficiency, and predictive management of development bottlenecks, enhancing the software development lifecycle. Our study bridges the theoretical and practical aspects of software quality optimization and introduces a novel perspective on managing software development processes. Additionally, our analysis reveals counterintuitive results that further contribute to our understanding of the dynamics influencing BFT. Sien Reeve Ordonez Peralta, Hironori Washizaki, Yoshiaki Fukazawa, Yuki Noyori, Shuhei Nojiri, Hideyuki Kanuka |
EASE | 4 |
| 2023 | Analysis of Bug Report Qualities with Fixing Time using a Bayesian NetworkabstractMost client software employs a bug-tracking system, which utilizes user-submitted reports (bug reports) that contain information necessary for software developers to fix bugs. The quality of bug reports drastically differs. Bug reports can include severity, priority, and associated issues determined by researching the addressed bug. Herein we investigate the influence of bug report qualities on successfully fixing a bug and estimating the fixing time. We also examine the claim in previous studies that bias and differences in the treatment of bug reports exist due to broad expertness among the reporters. Our approach examines the relationship between the qualities within the bug-fixing cycle and modeling graphical causal dependencies through a Bayesian Network. Bug reports with attachments, dependencies on another bug, and frequent discussions are more likely to be fixed. In addition, bug reports with a high severity tend to be fixed faster. Moreover, the difficulty of the bug itself may influence the fixing rate such that a straightforward bug will be fixed easier and faster regardless of the bug report quality. Sien Reeve Ordonez Peralta, Hironori Washizaki, Yoshiaki Fukazawa, Yuki Noyori, Shuhei Nojiri, Hideyuki Kanuka |
EASE | 4 |
| 2019 | What are Good Discussions Within Bug Report Comments for Shortening Bug Fixing Time?abstractBugs must be resolved efficiently for developers' limited resources. Bug reports are necessary for the bug modification process. Service user reports a bug as a bug report. Developer read bug reports and fix bugs. The developer can make discussion by posting comments on reported bug reports. There are several researches on the initial report of the bug report so that bugs can be fixed efficiently. But there are few researches on bug report comments. We focus on comments on bug reports. Currently, everyone is free to comment, but the modification time may be affected by how to comment. We investigate the topic of comments of the bug report. As a result of the investigation, the fact that the topics are mixed does not affect the modification time, however we found a tendency to shorten the modification time when the topic of the solution started early. Yuki Noyori, Hironori Washizaki, Yoshiaki Fukazawa, Keishi Oshima, Hideyuki Kanuka, Shuhei Nojiri, Ryosuke Tsuchiya |
QRS | 1 |