Demo Data from VLDB 2026 / reviewers in the wild / expert
Jeffrey A. Roberts
dblp:84/6767
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · unresolved
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 · 30% Software maintenance and evolution · 30% Programming languages and type systems · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Programming languages and type systems
functional programming |
0.1 | 1 | 2009 | Software Dependencies, Work Dependencies, and Their Impact on Failures · IEEE Trans. Software Eng. 2009 |
Empirical software engineering
mining software repositories |
0.1 | 1 | 2009 | Software Dependencies, Work Dependencies, and Their Impact on Failures · IEEE Trans. Software Eng. 2009 |
Software maintenance and evolution
software dependencies |
0.1 | 1 | 2009 | Software Dependencies, Work Dependencies, and Their Impact on Failures · IEEE Trans. Software Eng. 2009 |
Requirements engineering and software design
software architecture |
0.0 | 1 | 2009 | Software Dependencies, Work Dependencies, and Their Impact on Failures · IEEE Trans. Software Eng. 2009 |
Methods — techniques the papers use, named apart from their topics
empirical study · 0.1dependency measure comparison · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Software Dependencies, Work Dependencies, and Their Impact on FailuresabstractPrior research has shown that customer-reported software faults are often the result of violated dependencies that are not recognized by developers implementing software. Many types of dependencies and corresponding measures have been proposed to help address this problem. The objective of this research is to compare the relative performance of several of these dependency measures as they relate to customer-reported defects. Our analysis is based on data collected from two projects from two independent companies. Combined, our data set encompasses eight years of development activity involving 154 developers. The principal contribution of this study is the examination of the relative impact that syntactic, logical, and work dependencies have on the failure proneness of a software system. While all dependencies increase the fault proneness, the logical dependencies explained most of the variance in fault proneness, while workflow dependencies had more impact than syntactic dependencies. These results suggest that practices such as rearchitecting, guided by the network structure of logical dependencies, hold promise for reducing defects. Marcelo Cataldo, Audris Mockus, Jeffrey A. Roberts, James D. Herbsleb |
IEEE Trans. Software Eng. | 3 |