Assessment of the code refactoring dataset regarding the maintainability of methods

István Kádár, Péter Hegedüs, R. Ferenc, T. Gyimóthy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Code refactoring has a solid theoretical background while being used in development practice at the same time. However, previous works found controversial results on the nature of code refactoring activities in practice. Both their application context and impact on code quality needs further examination. Our paper encourages the investigation of code refactorings in practice by providing an excessive open dataset of source code metrics and applied refactorings through several releases of 7 open-source systems. We already demonstrated the practical value of the dataset by analyzing the quality attributes of the refactored source code classes and the values of source code metrics improved by those refactorings. In this paper, we have gone one step deeper and explored the effect of code refactorings at the level of methods. We found that similarly to class level, lower maintainability indeed triggers more code refactorings in practice at the level of methods and these refactorings significantly decrease size, coupling and clone metrics.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings
PublisherSpringer Verlag
Pages610-624
Number of pages15
Volume9789
ISBN (Print)9783319420882
DOIs
Publication statusPublished - 2016
Event16th International Conference on Computational Science and Its Applications, ICCSA 2016 - Beijing, China
Duration: Jul 4 2016Jul 7 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9789
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other16th International Conference on Computational Science and Its Applications, ICCSA 2016
CountryChina
CityBeijing
Period7/4/167/7/16

Keywords

  • Code refactoring
  • Empirical study
  • Refactoring dataset
  • Software maintainability

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Kádár, I., Hegedüs, P., Ferenc, R., & Gyimóthy, T. (2016). Assessment of the code refactoring dataset regarding the maintainability of methods. In Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings (Vol. 9789, pp. 610-624). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9789). Springer Verlag. https://doi.org/10.1007/978-3-319-42089-9_43