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Assessing the Reusability of Source Code Components

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Mining Software Engineering Data for Software Reuse

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

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Abstract

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.

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Notes

  1. 1.

    According to this method, the optimal degree is the one for which there is no significant decrease in the square sum of residuals when increasing the order by one.

  2. 2.

    http://s-case.github.io/.

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Authors and Affiliations

  1. Thessaloniki, Greece

    Themistoklis Diamantopoulos & Andreas L. Symeonidis

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  1. Themistoklis Diamantopoulos
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  2. Andreas L. Symeonidis
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Correspondence to Themistoklis Diamantopoulos .

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Diamantopoulos, T., Symeonidis, A.L. (2020). Assessing the Reusability of Source Code Components. In: Mining Software Engineering Data for Software Reuse. Advanced Information and Knowledge Processing. Springer, Cham. https://doi.org/10.1007/978-3-030-30106-4_10

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  • DOI: https://doi.org/10.1007/978-3-030-30106-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30105-7

  • Online ISBN: 978-3-030-30106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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