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analyzed in this article due to the scope of the appli-
cation and the intended comparison with the existing
approach. Moreover, we intend to use NLP (Natu-
ral Language Processing) to investigate the commit
text based on maintenance activities. Thus, we could
generate a classification approachable to classify the
commits automatically based on the labels discussed
in this article. Finally, we intend to use other cat-
egories (i.e., activities) proposed in the literature to
generalize the results.
ACKNOWLEDGEMENTS
The present work was carried out with the support
of the Coordenac¸
˜
ao de Aperfeic¸oamento de Pessoal
de N
´
ıvel Superior - Brazil (CAPES) - Financing
Code 001. The authors thank the partial support of
the CNPq (Brazilian National Council for Scientific
and Technological Development), FAPEMIG (Foun-
dation for Research and Scientific and Technological
Development of Minas Gerais), and PUC Minas.
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