  Background. Software Engineering (SE) researchers extensively perform
experiments with human subjects. Well-defined samples are required to ensure
external validity. Samples are selected \textit{purposely} or by
\textit{convenience}, limiting the generalizability of results. Objective. We
aim to depict the current status of participants selection in empirical SE,
identifying the main threats and how they are mitigated. We draft a robust
approach to participants' selection. Method. We reviewed existing participants'
selection guidelines in SE, and performed a preliminary literature review to
find out how participants' selection is conducted in SE in practice. % and 3)
we summarized the main issues identified. Results. We outline a new selection
methodology, by 1) defining the characteristics of the desired population, 2)
locating possible sources of sampling available for researchers, and 3)
identifying and reducing the "distance" between the selected sample and its
corresponding population. Conclusion. We propose a roadmap to develop and
empirically validate the selection methodology.
