Demo Data from VLDB 2026 / reviewers in the wild / expert
Vibhav Garg
dblp:11/5033
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—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 |
Requirements engineering and software design · 33% Software maintenance and evolution · 33% Empirical software engineering · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design › separation of concerns
crosscutting concerns |
0.1 | 1 | 2008 | Do Crosscutting Concerns Cause Defects? · IEEE Trans. Software Eng. 2008 |
Software maintenance and evolution › software quality assurance
defect analysis |
0.1 | 1 | 2008 | Do Crosscutting Concerns Cause Defects? · IEEE Trans. Software Eng. 2008 |
Empirical software engineering
software metrics |
0.1 | 1 | 2008 | Do Crosscutting Concerns Cause Defects? · IEEE Trans. Software Eng. 2008 |
Methods — techniques the papers use, named apart from their topics
correlation analysis · 0.1case study · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Do Crosscutting Concerns Cause Defects?abstractThere is a growing consensus that crosscutting concerns harm code quality. An example of a crosscutting concern is a functional requirement whose implementation is distributed across multiple software modules. We asked the question, "How much does the amount that a concern is crosscutting affect the number of defects in a program?" We conducted three extensive case studies to help answer this question. All three studies revealed a moderate to strong statistically significant correlation between the degree of scattering and the number of defects. This paper describes the experimental framework we developed to conduct the studies, the metrics we adopted and developed to measure the degree of scattering, the studies we performed, the efforts we undertook to remove experimental and other biases, and the results we obtained. In the process, we have formulated a theory that explains why increased scattering might lead to increased defects. Marc Eaddy, Thomas Zimmermann 0001, Kaitin D. Sherwood, Vibhav Garg, Gail C. Murphy, Nachiappan Nagappan, Alfred V. Aho |
IEEE Trans. Software Eng. | 4 |