Investigating probabilistic sampling approaches for large-scale surveys in software engineering

Authors

  • Rafael Maiani de Mello PESC/COPPE-Federal University of Rio de Janeiro Brazil, Rio de Janeiro, P.O. Box 68511, Brazil
  • Pedro Corrêa da Silva PESC/COPPE-Federal University of Rio de Janeiro Brazil, Rio de Janeiro, P.O. Box 68511, Brazil
  • Guilherme Horta Travassos PESC/COPPE-Federal University of Rio de Janeiro Brazil, Rio de Janeiro, P.O. Box 68511, Brazil

Keywords:

Population, Sampling frame, Experimental software engineering, Hierarchical clustering analysis, Stratified sampling, Survey, Multivariate analysis, Graph theory, Strongly connected components

Abstract

Background

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.;

Method

A conceptual framework for supporting large scale sampling in Software Engineering surveys has been organized after performing a set of experiences on designing such strategies and gathering evidence regarding their benefits. The use of this conceptual framework based on a sampling strategy developed for supporting the replication of a survey on characteristics of agility and agile practices in software processes is depicted in this paper.;

Result

A professional social network (Linkedln; Conclusion

The heterogeneity and number of participants in this replication contributed to improve the strength of original surveys results. Therefore, we believe the sharing of this experience, the instruments and plan can be helpful for those researchers and practitioners interested on executing large scale surveys in Software Engineering.;

 

Downloads

Download data is not yet available.

Downloads

Published

2015-05-10

How to Cite

de Mello, R. M. ., da Silva, P. C., & Travassos, G. H. (2015). Investigating probabilistic sampling approaches for large-scale surveys in software engineering. Journal of Software Engineering Research and Development, 3, 8:1 – 8:26. Retrieved from https://journals-sol.sbc.org.br/index.php/jserd/article/view/414

Issue

Section

Research Article