Demo Data from VLDB 2026 / reviewers in the wild / expert
Stefan Alexander van Heijningen
dblp:393/9389
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
0009-0002-2589-6336ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author · 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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing
mutation testing |
0.8 | 1 | 2024 | Integrating Mutation Testing Into Developer Workflow: An Industrial Case Study · ASE 2024 |
Software testing › test adequacy
test suite adequacy |
0.8 | 1 | 2024 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Integrating Mutation Testing Into Developer Workflow: An Industrial Case StudyabstractMutation 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 |
ASE | 1 |