VLDB 2026 Research / reviewers in the wild / expert
Guangzong Cai
dblp:329/0987
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0003-7346-2871ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Bug priority change: An empirical study on Apache projects
Zengyang Li, Guangzong Cai, Qinyi Yu, Peng Liang 0001, Ran Mo, Hui Liu 0004 |
J. Syst. Softw. | 2 |
| 2022 | A Preliminary Study on the Explicitness of Bug AssociationsabstractBugs are usually in associations with other bugs in a software system, e.g., a bug may result from another bug.However, such bug associations are implicit and usually cannot be traced without a significant amount of effort.Intuitively, if a bug association is easier to trace, the involved bugs can be fixed in a cleaner way.However, there is little evidence on the explicitness of bug associations.In this paper, we aim to evaluate the explicitness of bug associations, so as to get a basic understanding on such associations.To this end, we defined a metric to quantify the explicitness of a bug association, and conducted an empirical study on 11 non-trivial Apache open source software systems.The main findings are summarized as follows: (1) From the perspective of code change history, around 29% of bug pairs are not explicitly associated, and about 71% are explicitly associated to some extent; (2) Bugs in the association of Container have relatively strong association explicitness, while bugs in the association of Blocked or Blocker, Cloners, and Dependent have relatively weak association explicitness.These findings provide insights on software analyzability to practitioners and researchers. Zengyang Li, Jieling Xu, Guangzong Cai, Peng Liang 0001, Ran Mo |
SEKE | 3 |