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EDBT 2026 Demo / reviewers in the wild / expert

Bo Lennselius

dblp:86/5664 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1990
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-author

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
Software testing · 93% Empirical software engineering · 7%

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

TopicWeightPapersLastEvidence papers
Software testing › software reliability
fault estimation		 0.011990
Software Fault Content and Reliability Estimations for Telecommunication Systems · IEEE J. Sel. Areas Commun. 1990
Software testing › software reliability
software fault content estimation		 0.011990
Software Fault Content and Reliability Estimations for Telecommunication Systems · IEEE J. Sel. Areas Commun. 1990
Software testing
software reliability		 0.011990
Software Fault Content and Reliability Estimations for Telecommunication Systems · IEEE J. Sel. Areas Commun. 1990
Software testing › software reliability › software reliability modeling
software reliability growth model		 0.011990
Software Fault Content and Reliability Estimations for Telecommunication Systems · IEEE J. Sel. Areas Commun. 1990
Empirical software engineering
software project management		 0.011990
Software Fault Content and Reliability Estimations for Telecommunication Systems · IEEE J. Sel. Areas Commun. 1990

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

reliability growth modeling · 0.0
YearPublicationVenuePosition
1990 Software Fault Content and Reliability Estimations for Telecommunication Systems
abstract
The problem of software fault content and reliability estimations is considered. Estimations that can be used to improve the control of a software projects are emphasized. A model of how to estimate the number of software faults is presented, which takes into account both the development process and the developed software product. A model of how to predict, before the testing has started, the occurrences of faults during the testing stage is also presented. These models, together with software reliability growth models, have been evaluated on a number of software projects.>
Bo Lennselius, Lars Rydström
 IEEE J. Sel. Areas Commun.1