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Research artifacts in secondary studies: A systematic mapping in software engineering

Huotala, Aleksi, Kuutila, Miikka, Mäntylä, Mika·2025·Information and Software Technology

Abstract

Context: Systematic reviews (SRs) summarize state-of-the-art evidence in science, including software engineering (SE). Objective: Our objective is to evaluate how SRs report research artifacts and to provide a comprehensive list of these artifacts. Method: We examined 537 secondary studies published between 2013 and 2023 to analyze the availability and reporting of research artifacts. Results: Our findings indicate that only 31.5% of the reviewed studies include research artifacts. Encouragingly, the situation is gradually improving, as our regression analysis shows a significant increase in the availability of research artifacts over time. However, in 2023, just 62.0% of secondary studies provide a research artifact while an even lower percentage, 30.4% use a permanent repository with a digital object identifier (DOI) for storage. Conclusion: To enhance transparency and reproducibility in SE research, we advocate for the mandatory publication of research artifacts in secondary studies.

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Metadata

Authors
Huotala, A., Kuutila, M., & Mäntylä, M.
Venue
Information and Software Technology
Publisher
Elsevier BV
Published
2025-11
Volume
187
Pages
107830
ISSN
0950-5849
Cited by
1
References
10
Language
en
Licence
Funders
  • Research Council of Finland (358471)
  • Dalhousie University

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CoChat. (2026). Citation check: Research artifacts in secondary studies: A systematic mapping in software engineering. https://app.cochat.ai/papers/10.1016/j.infsof.2025.107830
The paper
Huotala, A., Kuutila, M., & Mäntylä, M. (2025). Research artifacts in secondary studies: A systematic mapping in software engineering. Information and Software Technology. https://doi.org/10.1016/j.infsof.2025.107830

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.