  Background: The use of gray literature (GL) has grown in software engineering
research, especially in studies that consider Questions and Answers (Q&A)
sites, since software development professionals widely use them. Though
snowballing (SB) techniques are standard in systematic literature reviews,
little is known about how to apply them to gray literature reviews. Aims: This
paper investigates how to use SB approaches on Q&A sites during gray literature
reviews to identify new valid discussions for analysis. Method: In previous
studies, we compiled and analyzed a set of Stack Exchange Project Management
(SEPM) discussions related to software engineering technical debt (TD). Those
studies used a data set consisting of 108 valid discussions extracted from
SEPM. Based on this start data set, we perform forward and backward SB using
two different approaches: link-based and similarity-based SB. We then compare
the precision and recall of those two SB approaches against the search-based
approach of the original study. Results: In just one snowballing iteration, the
approaches yielded 291 new discussions for analysis, 130 of which were
considered valid for our study. That is an increase of about 120% over the
original data set (recall). The SB process also yielded a similar rate of valid
discussion retrieval when compared to the search-based approach (precision).
Conclusion: This paper provides guidelines on how to apply two SB approaches to
find new valid discussions for review. To our knowledge, this is the first
study that analyzes the use of SB on Q&A websites. By applying SB, it was
possible to identify new discussions, significantly increasing the relevant
data set for a gray literature review.
