Demo Data from EDBT 2026 / reviewers in the wild / expert
Xinyue Lv
dblp:273/5454
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2025
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 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 |
Empirical software engineering · 77% Software maintenance and evolution · 23% | |
| Human-computer interaction and pervasive computing
1 paper |
Collaborative and social computing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › computer-supported cooperative work › developer collaboration
collaborative programming |
0.8 | 1 | 2024 | Understanding Real-Time Collaborative Programming: A Study of Visual Studio Live Share · ACM Trans. Softw. Eng. Methodol. 2024 |
Empirical software engineering
developer studies |
0.8 | 1 | 2024 | Understanding Real-Time Collaborative Programming: A Study of Visual Studio Live Share · ACM Trans. Softw. Eng. Methodol. 2024 |
Software maintenance and evolution
code review |
0.2 | 1 | 2024 | Understanding Real-Time Collaborative Programming: A Study of Visual Studio Live Share · ACM Trans. Softw. Eng. Methodol. 2024 |
Methods — techniques the papers use, named apart from their topics
survey · 1.5interview study · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Enhanced quantum long short-term memory by using bidirectional ring variational quantum circuit
Xinyue Lv, Abdullah Gani |
J. Supercomput. | 2 |
| 2024 | Understanding Real-Time Collaborative Programming: A Study of Visual Studio Live ShareabstractReal-time collaborative programming (RCP) entails developers working simultaneously, regardless of their geographic locations. RCP differs from traditional asynchronous online programming methods, such as Git or SVN, where developers work independently and update the codebase at separate times. Although various real-time code collaboration tools (e.g., Visual Studio Live Share , Code with Me , and Replit ) have kept emerging in recent years, none of the existing studies explicitly focus on a deep understanding of the processes or experiences associated with RCP. To this end, we combine interviews and an e-mail survey with the users of Visual Studio Live Share , aiming to understand (i) the scenarios, (ii) the requirements, and (iii) the challenges when developers participate in RCP. We find that developers participate in RCP in 18 different scenarios belonging to six categories, e.g., pair programming , group debugging , and code review . However, existing users’ attitudes toward the usefulness of the current RCP tools in these scenarios were significantly more negative than the expectations of potential users. As for the requirements, the most critical category is live editing , followed by the need for sharing terminals to enable hosts and guests to run commands and see the results, as well as focusing and following , which involves “following” the host’s edit location and “focusing” the guests’ attention on the host with a notification. Under these categories, we identify 17 requirements, but most of them are not well supported by current tools. In terms of challenges, we identify 19 challenges belonging to seven categories. The most severe category of challenges is lagging followed by permissions and conflicts . The above findings indicate that the current RCP tools and even collaborative environment need to be improved greatly and urgently. Based on these findings, we discuss the recommendations for different stakeholders, including practitioners, tool designers, and researchers. Xin Tan 0003, Xinyue Lv, Jing Jiang 0005, Li Zhang 0029 |
ACM Trans. Softw. Eng. Methodol. | 2 |
| 2023 | UAV image object recognition method based on small sample learning
Xinyue Lv, Ge Wang 0001, Xiaofeng Lian |
Multim. Tools Appl. | 2 |