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David Friberg

dblp:393/9697 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2025
0009-0007-6706-7321ORCID · corroborated

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

Software engineering, systems software and programming languages · 2 · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

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 · 100%

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

TopicWeightPapersLastEvidence papers
Software testing
mutation testing
0.812024
Integrating Mutation Testing Into Developer Workflow: An Industrial Case Study · ASE 2024
Software testing › test adequacy
test suite adequacy
0.812024
Integrating Mutation Testing Into Developer Workflow: An Industrial Case Study · ASE 2024

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

industrial case study · 0.8dashboard visualization · 0.8
YearPublicationVenuePosition
2025 "Good" and "Bad" Failures in Industrial CI/CD-Balancing Cost and Quality Assurance
Simin Sun, David Friberg, Miroslaw Staron
SEAA (3)2
2024 Integrating Mutation Testing Into Developer Workflow: An Industrial Case Study
abstract
Mutation testing is a potentially effective method to assess test suite adequacy. Researchers have made mutation testing more computationally efficient, and new frameworks are regularly emerging. However, there is still limited adoption of mutation testing in industry. We hypothesize that such adoption is hindered by a lack of guidance on how to effectively and efficiently utilize mutation testing in a development workflow. To that end, we have conducted an industrial case study exploring the technical challenges of implementing mutation testing in continuous integration, what information from mutation testing is of use to developers, and how that information should be presented (in textual and visual form). Our results reveal five technical challenges of integrating mutation testing and nine key findings regarding how the results of mutation testing are used and presented. We also offer a dashboard to visualize mutation testing results, as well as 16 recommendations for making effective use of mutation testing in practice1.
Stefan Alexander van Heijningen, Theo Wiik, Francisco Gomes de Oliveira Neto, Gregory Gay 0002, Kim Viggedal, David Friberg
ASE6