The DOI matches its Crossref record; 81 of the 81 references it cites were found in a registry or an index.
Sampling in software engineering research: a critical review and guidelines
Open accessAbstract
Representative sampling appears rare in empirical software engineering research. Not all studies need representative samples, but a general lack of representative sampling undermines a scientific field. This article therefore reports a critical review of the state of sampling in recent, high-quality software engineering research. The key findings are: (1) random sampling is rare; (2) sophisticated sampling strategies are very rare; (3) sampling, representativeness and randomness often appear misunderstood. These findings suggest that software engineering research has a generalizability crisis. To address these problems, this paper synthesizes existing knowledge of sampling into a succinct primer and proposes extensive guidelines for improving the conduct, presentation and evaluation of sampling in software engineering research. It is further recommended that while researchers should strive for more representative samples, disparaging non-probability sampling is generally capricious and particularly misguided for predominately qualitative research.
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Cited by
Navigating the Complexity of Generative AI Adoption in Software Engineering
Russo, D. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3652154 · Cited by 217
“” This time efficiency can be attributed to the NLP capabilities of LLMs, which enable users to communicate their needs more effectively and rapidly obtain tailored solutions [14].”
BackgroundWyrich, M., Preikschat, A., Graziotin, D., & Wagner, S. (2021) · 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) · doi:10.1109/icse43902.2021.00055 · Cited by 24
Practitioners’ expectations on log anomaly detection
Ma, X., Li, Y., Keung, J., Yu, X., Zou, H., Yang, Z., Sarro, F., & Barr, E. T. (2025) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2025.3586700 · Cited by 21
“For interviews, we employ expert sampling, a subtype of purposive sampling [14], to target professionals with relevant expertise in log analysis to gather valuable insights.”
Accountability in Code Review: The Role of Intrinsic Drivers and the Impact of LLMs
Alami, A., Jensen, V., & Ernst, N. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3721127 · Cited by 11
On the Need to Rethink Trust in AI Assistants for Software Development: A Critical Review
Baltes, S., Speith, T., Chiteri, B., Mohsenimofidi, S., Chakraborty, S., & Buschek, D. (2026) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2026.3659804 · Cited by 5
Self-citation
Metadata
- Authors
- Baltes, S., & Ralph, P.
- Venue
- Empirical Software Engineering
- Published
- 2022-04-28
- Volume
- 27
- Issue
- 4
- ISSN
- 1382-3256 (ISSN-L)
- 1573-7616
- OpenAlex
- W3006568433
- Cited by
- 382
- References
- 81
- FWCI
- 73.69
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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