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Laura L. E. Cowen

dblp:224/3635 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0002-0853-1450ORCID · reported

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 · 77% Software maintenance and evolution · 23%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution
code review
0.212014
Peer Review on Open-Source Software Projects: Parameters, Statistical Models, and Theory · ACM Trans. Softw. Eng. Methodol. 2014
Empirical software engineering
mining software repositories
0.212014
Peer Review on Open-Source Software Projects: Parameters, Statistical Models, and Theory · ACM Trans. Softw. Eng. Methodol. 2014
Empirical software engineering › mining software repositories
open source software peer review
0.212014
Peer Review on Open-Source Software Projects: Parameters, Statistical Models, and Theory · ACM Trans. Softw. Eng. Methodol. 2014
Empirical software engineering
peer review
0.212014
Peer Review on Open-Source Software Projects: Parameters, Statistical Models, and Theory · ACM Trans. Softw. Eng. Methodol. 2014

Methods — techniques the papers use, named apart from their topics

statistical modeling · 0.2
YearPublicationVenuePosition
2014 Peer Review on Open-Source Software Projects: Parameters, Statistical Models, and Theory
abstract
Peer review is seen as an important quality-assurance mechanism in both industrial development and the open-source software (OSS) community. The techniques for performing inspections have been well studied in industry; in OSS development, software peer reviews are not as well understood. To develop an empirical understanding of OSS peer review, we examine the review policies of 25 OSS projects and study the archival records of six large, mature, successful OSS projects. We extract a series of measures based on those used in traditional inspection experiments. We measure the frequency of review, the size of the contribution under review, the level of participation during review, the experience and expertise of the individuals involved in the review, the review interval, and the number of issues discussed during review. We create statistical models of the review efficiency, review interval, and effectiveness, the issues discussed during review, to determine which measures have the largest impact on review efficacy. We find that OSS peer reviews are conducted asynchronously by empowered experts who focus on changes that are in their area of expertise. Reviewers provide timely, regular feedback on small changes. The descriptive statistics clearly show that OSS review is drastically different from traditional inspection.
Peter C. Rigby, Daniel M. Germán, Laura L. E. Cowen, Margaret-Anne D. Storey
ACM Trans. Softw. Eng. Methodol.3