Inference of Code Familiarity by Mining Software Repositories

• Irvayne Matheus de Sousa Ibiapina UFPI
• Francisco Vanderson de Moura Alves UFPI
• Werney Ayala Luz Lira UFPI
• Gleison de Andrade e Silva UFPI
• Pedro de Alcântara dos Santos Neto UFPI

DOI: https://doi.org/10.5753/sbqs.2017.15095

Abstract

The software development process is complex and, for this reason, it is common to execute it as a team. But teamwork can generate problems for an organization. One of these problems is the presence of portions of code known only by a single developer (or a small group). This fact can cause great difficulty in software maintenance. This paper presents a set of metrics and a tool called CoDiVision, that performs a data mining of code repositories to infer the familiarity that each developer has with the project. The CoDiVision was evaluated through the analysis of medium and large projects and the results indicate that the metrics and the tool can be an important support in software development.

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