Klaus Hartjes

dblp:13/8164 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—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
Empirical software engineering · 50% Compilers and program optimization · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Compilers and program optimization
dead code elimination
0.112010
Transparent combination of expert and measurement data for defect prediction: an industrial case study · ICSE (2) 2010
Empirical software engineering › mining software repositories
defect prediction
0.112010
Transparent combination of expert and measurement data for defect prediction: an industrial case study · ICSE (2) 2010

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

measurement-based estimation · 0.1expert opinion elicitation · 0.1
YearPublicationVenuePosition
2010 Transparent combination of expert and measurement data for defect prediction: an industrial case study
abstract
Defining strategies on how to perform quality assurance (QA) and how to control such activities is a challenging task for organizations developing or maintaining software and software-intensive systems. Planning and adjusting QA activities could benefit from accurate estimations of the expected defect content of relevant artifacts and the effectiveness of important quality assurance activities. Combining expert opinion with commonly available measurement data in a hybrid way promises to overcome the weaknesses of purely data-driven or purely expert-based estimation methods. This article presents a case study of the hybrid estimation method HyDEEP for estimating defect content and QA effectiveness in the telecommunication domain. The specific focus of this case study is the use of the method for gaining quantitative predictions. This aspect has not been empirically analyzed in previous work. Among other things, the results show that for defect content estimation, the method performs significantly better statistically than purely data-based methods, with a relative error of 0.3 on average (MMRE).
Michael Kläs, Frank Elberzhager, Jürgen Münch, Klaus Hartjes, Olaf von Graevemeyer
ICSE (2)4