Sampling in Software Engineering Research: A Critical Review and Guidelines
This addresses a methodological crisis for software engineering researchers, but it is incremental as it synthesizes existing knowledge into guidelines.
The paper tackles the problem of poor sampling practices in empirical software engineering research, finding that random and sophisticated sampling are rare and often misunderstood, leading to a generalizability crisis, and it proposes guidelines to improve sampling conduct and evaluation.
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.