Assessing the Reusability of Source Code Components

In the context of reusing components from online repositories, assessing the quality and specifically the reusability of source code before reusing it poses a major challenge for the research community. Although several quality assessment systems have been proposed, most of them do not focus on reusability. In this chapter, we design a reusability score using as ground truth information from GitHub stars and forks, which indicate the extent to which software components are adopted/preferred by developers. Our methodology includes applying different machine learning algorithms in order to produce reusability estimation models at both class and package levels. Finally, evaluating our methodology indicates that it can be effective for assessing reusability as perceived by developers.