VLDB 2026 Research / reviewers in the wild / expert
Zhouding Wang
dblp:168/2634
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1
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 maintenance and evolution · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › refactoring
identifier renaming |
0.2 | 1 | 2015 | Identifying Renaming Opportunities by Expanding Conducted Rename Refactorings · IEEE Trans. Software Eng. 2015 |
Software maintenance and evolution
refactoring |
0.2 | 1 | 2015 | Identifying Renaming Opportunities by Expanding Conducted Rename Refactorings · IEEE Trans. Software Eng. 2015 |
Software maintenance and evolution › refactoring
refactoring recommendation |
0.2 | 1 | 2015 | Identifying Renaming Opportunities by Expanding Conducted Rename Refactorings · IEEE Trans. Software Eng. 2015 |
Methods — techniques the papers use, named apart from their topics
entity similarity analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Identifying Renaming Opportunities by Expanding Conducted Rename RefactoringsabstractTo facilitate software refactoring, a number of approaches and tools have been proposed to suggest where refactorings should be conducted. However, identification of such refactoring opportunities is usually difficult because it often involves difficult semantic analysis and it is often influenced by many factors besides source code. For example, whether a software entity should be renamed depends on the meaning of its original name (natural language understanding), the semantics of the entity (source code semantics), experience and preference of developers, and culture of companies. As a result, it is difficult to identify renaming opportunities. To this end, in this paper we propose an approach to identify renaming opportunities by expanding conducted renamings. Once a rename refactoring is conducted manually or with tool support, the proposed approach recommends to rename closely related software entities whose names are similar to that of the renamed entity. The rationale is that if an engineer makes a mistake in naming a software entity it is likely for her to make the same mistake in naming similar and closely related software entities. The main advantage of the proposed approach is that it does not involve difficult semantic analysis of source code or complex natural language understanding. Another advantage of this approach is that it is less influenced by subjective factors, e.g., experience and preference of software engineers. The proposed approach has been evaluated on four open-source applications. Our evaluation results show that the proposed approach is accurate in recommending entities to be renamed (average precision 82 percent) and in recommending new names for such entities (average precision 93 percent). Evaluation results also suggest that a substantial percentage (varying from 20 to 23 percent) of rename refactorings are expansible. Hui Liu 0003, Qiurong Liu, Zhouding Wang |
IEEE Trans. Software Eng. | 4 |