Visual analytics no apoio à exploração visual de dívidas técnicas em repositórios de softwares

Abstract

The increasing access to digital technologies leads to a large-scale data production and consumption worldwide. Consequently, there is a high demand for computing analysis techniques that help users to obtain a better understanding of data. An inherent challenge in this context is to analyze large volume of complex and heterogeneous datasets, such as conceived by software repositories. Areas such as Software Visualization and Visual Software Analytics have become increasingly used to support developers in software comprehension by providing a visual panorama of the entire software development process. Those graphical representations enable useful information extraction, especially for system maintenance when analyzing technical debts. Although repositories are mostly composed of multidimensional datasets, there is a lack of works that apply multidimensional visualizations to identify and track distinct groups of technical debts, consisting of immature or inappropriate artifacts during the project lifecycle. In this sense, the proposal presents the Visual Debts Analytics tool, an approach based on Visual Analytics consisting of multiple coordinated multidimensional visualizations for the analysis of different groups of technical debts in software repositories. In particular, the proposed technique aims to identify and track the correlation, structure, evolution and similarities of technical debts in open-source software repositories. To evaluate our approach we presented use cases in two different repositories that demonstrate the a better comprehension in the project life cycle, enabling insights into the project quality.