Demo Data from VLDB 2026 / reviewers in the wild / expert
T. J. Wicinski
dblp:45/5120
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1990
—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 |
Empirical software engineering · 44% Software maintenance and evolution · 44% Requirements engineering and software design · 13% |
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
code change analysis |
0.0 | 1 | 1990 | Evaluating Software Design Processes by Analyzing Change Data Over Time · IEEE Trans. Software Eng. 1990 |
Empirical software engineering
mining software repositories |
0.0 | 1 | 1990 | Evaluating Software Design Processes by Analyzing Change Data Over Time · IEEE Trans. Software Eng. 1990 |
Requirements engineering and software design › software process
software design process |
0.0 | 1 | 1990 | Evaluating Software Design Processes by Analyzing Change Data Over Time · IEEE Trans. Software Eng. 1990 |
Methods — techniques the papers use, named apart from their topics
time-based analysis · 0.0correlation analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1990 | Evaluating Software Design Processes by Analyzing Change Data Over TimeabstractAn analysis is presented of early design and code change data from the software cost reduction (SCR) project, a well-reported effort conducted at the US Naval Research Laboratory from 1978 to 1988. The analyses are mostly time-based studies of the change data and relationships between the data and SCR personnel activity data. Some analyses of the change data show patterns consistent with a major goal of the SCR project: the design and development of easy-to-change software. Specifically, most changes took a day or less to uncover and resolve; the majority of changes updated at most one module. Moreover, these percentages remained fairly stable. No positive relationship appeared between error-correction effort and the number of days that an error remained in the SCR design documentation. Other analyses suggest that consistency may have been temporary. For example, the analyses suggest a stepwise growth in average change effort, and an increasing percentage of changes resulted in module interface updates. Certain specific ratios between SCR change data and personnel activity data may be possible indicators of design incompleteness.> L. J. Chmura, Anthony F. Norcio, T. J. Wicinski |
IEEE Trans. Software Eng. | 3 |