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Jeffrey A. Roberts

dblp:84/6767 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Programming languages and type systems
functional programming
0.112009
Software Dependencies, Work Dependencies, and Their Impact on Failures · IEEE Trans. Software Eng. 2009
Empirical software engineering
mining software repositories
0.112009
Software Dependencies, Work Dependencies, and Their Impact on Failures · IEEE Trans. Software Eng. 2009
Software maintenance and evolution
software dependencies
0.112009
Software Dependencies, Work Dependencies, and Their Impact on Failures · IEEE Trans. Software Eng. 2009
Requirements engineering and software design
software architecture
0.012009
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
YearPublicationVenuePosition
2009 Software Dependencies, Work Dependencies, and Their Impact on Failures
abstract
Prior 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