Authors:
Mário André de Freitas Farias
1
;
José Amancio Santos
2
;
André Batista da Silva
3
;
Marcos Kalinowski
4
;
Manoel Mendonça
5
and
Rodrigo Oliveira Spínola
6
Affiliations:
1
Federal Institute of Sergipe and Federal University of Bahia, Brazil
;
2
State University of Feira de Santana, Brazil
;
3
Federal University of Sergipe, Brazil
;
4
Fluminense Federal University, Brazil
;
5
Federal University of Bahia, Brazil
;
6
Fraunhofer Proj. Center at UFBA and Salvador University, Brazil
Keyword(s):
Contextualized Vocabulary, Technical Debt, Code Comment, Controlled Experiment.
Related
Ontology
Subjects/Areas/Topics:
Enterprise Information Systems
;
Human Factors
;
Human-Computer Interaction
;
Information Systems Analysis and Specification
;
Physiological Computing Systems
;
Software Engineering
Abstract:
In order to effectively manage technical debt (TD), a set of indicators has been used by automated approaches to identify TD items. However, some debt may not be directly identified using only metrics collected from the source code. CVM-TD is a model to support the identification of technical debt by considering the developer point of view when identifying TD through code comment analysis. In this paper, we analyze the use of CVM-TD with the purpose of characterizing factors that affect the accuracy of the identification of TD. We performed a controlled experiment investigating the accuracy of CVM-TD and the influence of English skills and developer experience factors. The results indicated that CVM-TD provided promising results considering the accuracy values. English reading skills have an impact on the TD detection process. We could not conclude that the experience level affects this process. Finally, we also observed that many comments suggested by CVM-TD were considered good ind
icators of TD. The results motivate us continuing to explore code comments in the context of TD identification process in order to improve CVM-TD.
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