The technical debt metaphor describes the effect of immature artifacts on software maintenance that bring a short-term benefit to the project in terms of increased productivity and lower cost, but that may have to be paid off with interest later on. Much research has been performed to propose mechanisms to identify debt and decide the most appropriate moment to pay it off. It is important to investigate the current state of the art in order to provide both researchers and practitioners with information that enables further research activities as well as technical debt management in practice (Alves et al., 2018).

Software visualization is the field of software engineering that aims to help people to understand software through the use of visual resources. It can be effectively used to analyze and understand the large amount of data produced during software evolution. (Novais et al., 2013)

Software engineering is by nature an experimental science. ESE aims to build knowledge on software engineering throught the use of experimental methods such as controlled experiments, case studies, surveys, action research, and systematic reviews, combined with solid quantitative and qualitative analysis techniques.

MSR refers to the use of data mining techniques on software repositories such as project mailing lists, source code, version control systems, issues trackers, among many other data sources, to characterize, understand and improve software products and processes.