research-article

On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation

Authors:

Gabriele Bavota,

Massimiliano Di Penta,

Andrea De LuciaAuthors Info & Claims

Volume 23, Issue 3

Pages 1188 - 1221

https://doi.org/10.1007/s10664-017-9535-z

Published: 01 June 2018 Publication History

Abstract

Code smells are symptoms of poor design and implementation choices that may hinder code comprehensibility and maintainability. Despite the effort devoted by the research community in studying code smells, the extent to which code smells in software systems affect software maintainability remains still unclear. In this paper we present a large scale empirical investigation on the diffuseness of code smells and their impact on code change- and fault-proneness. The study was conducted across a total of 395 releases of 30 open source projects and considering 17,350 manually validated instances of 13 different code smell kinds. The results show that smells characterized by long and/or complex code (e.g., Complex Class) are highly diffused, and that smelly classes have a higher change- and fault-proneness than smell-free classes.

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cover image Empirical Software Engineering

Empirical Software Engineering Volume 23, Issue 3

Jun 2018

717 pages

ISSN:1382-3256

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Copyright © 2018 Springer Science+Business Media, LLC, part of Springer Nature.

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Kluwer Academic Publishers

United States

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Published: 01 June 2018

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https://dl.acm.org/doi/10.1007/s10664-024-10568-z
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