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Investigating the relation between lexical smells and change- and fault-proneness: an empirical study

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Abstract

Past and recent studies have shown that design smells which are poor solutions to recurrent design problems make object-oriented systems difficult to maintain, and that they negatively impact the class change- and fault-proneness. More recently, lexical smells have been introduced to capture recurring poor practices in the naming, documentation, and choice of identifiers during the implementation of an entity. Although recent studies show that developers perceive lexical smells as impairing program understanding, no study has actually evaluated the relationship between lexical smells and software quality as well as their interaction with design smells. In this paper, we detect 29 smells consisting of 13 design smells and 16 lexical smells in 30 releases of three projects: ANT, ArgoUML, and Hibernate. We analyze to what extent classes containing lexical smells have higher (or lower) odds to change or to be subject to fault fixing than other classes containing design smells. Our results show and bring empirical evidence on the fact that lexical smells can make, in some cases, classes with design smells more fault-prone. In addition, we empirically demonstrate that classes containing design smells only are more change- and fault-prone than classes with lexical smells only.

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Notes

  1. http://argouml.tigris.org/.

  2. http://hibernate.org/.

  3. http://ant.apache.org/.

  4. http://git-scm.com/.

  5. http://argouml.tigris.org/issues.

  6. https://www.bugzilla.org/.

  7. https://www.atlassian.com/software/jira.

  8. https://www.bugzilla.org/.

  9. https://www.atlassian.com/software/jira.

  10. http://swat.polymtl.ca/data/Replication-Package-Smells-SQJ-2015.zip.

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Authors and Affiliations

  1. École de Technologie Supérieure, Montreal, Canada

    Latifa Guerrouj

  2. École Polytechnique de Montréal, Montreal, Canada

    Zeinab Kermansaravi, Foutse Khomh, Giuliano Antoniol & Yann-Gaël Guéhéneuc

  3. Washington State University, Pullman, WA, USA

    Venera Arnaoudova

  4. McGill University, Montreal, Canada

    Benjamin C. M. Fung

Authors
  1. Latifa Guerrouj
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  2. Zeinab Kermansaravi
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  3. Venera Arnaoudova
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  4. Benjamin C. M. Fung
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  5. Foutse Khomh
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  6. Giuliano Antoniol
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  7. Yann-Gaël Guéhéneuc
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Correspondence to Latifa Guerrouj.

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Guerrouj, L., Kermansaravi, Z., Arnaoudova, V. et al. Investigating the relation between lexical smells and change- and fault-proneness: an empirical study. Software Qual J 25, 641–670 (2017). https://doi.org/10.1007/s11219-016-9318-6

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