Sampling in software engineering research: a critical review and guidelines

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...

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Veröffentlicht in:Empirical software engineering : an international journal Jg. 27; H. 4
Hauptverfasser: Baltes, Sebastian, Ralph, Paul
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.07.2022
Springer Nature B.V
Schlagworte:
Compilers
Computer Science
Engineering research
Guidelines
Interpreters
Programming Languages
Qualitative research
Random sampling
Software engineering
Software Engineering/Programming and Operating Systems
Representative sampling
Random sampling
Purposive sampling
Sampling
Probability sampling
Research methodology
ISSN:1382-3256, 1573-7616
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Zusammenfassung: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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ISSN:1382-3256
1573-7616
DOI:10.1007/s10664-021-10072-8