Investigating probabilistic sampling approaches for large-scale surveys in software engineering
Establishing representative samples for Software Engineering surveys is still considered a challenge. Specialized literature often presents limitations on interpreting surveys results, mainly due to the use of sampling frames established by convenience and non-probabilistic criteria for sampling from them. In this sense, we argue that a strategy to support the systematic establishment of sampling frames from an adequate source of sampling can contribute to improve this scenario.
survey sampling frame population experimental software engineering hierarchical clustering analysis stratified sampling multivariate analysis graph theory strongly connected components