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Code Bad Smells: a review of current knowledge

Published: 01 April 2011 Publication History

Abstract

Fowler et al. identified 22 Code Bad Smells to direct the effective refactoring of code. These are increasingly being taken up by software engineers. However, the empirical basis of using Code Bad Smells to direct refactoring and to address ‘trouble’ in code is not clear, i.e., we do not know whether using Code Bad Smells to target code improvement is effective. This paper aims to identify what is currently known about Code Bad Smells. We have performed a systematic literature review of 319 papers published since Fowler et al. identified Code Bad Smells (2000 to June 2009). We analysed in detail 39 of the most relevant papers. Our findings indicate that Duplicated Code receives most research attention, whereas some Code Bad Smells, e.g., Message Chains, receive little. This suggests that our knowledge of some Code Bad Smells remains insufficient. Our findings also show that very few studies report on the impact of using Code Bad Smells, with most studies instead focused on developing tools and methods to automatically detect Code Bad Smells. This indicates an important gap in the current knowledge of Code Bad Smells. Overall this review suggests that there is little evidence currently available to justify using Code Bad Smells. Copyright © 2010 John Wiley & Sons, Ltd.

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Published In

cover image Journal of Software Maintenance and Evolution: Research and Practice
Journal of Software Maintenance and Evolution: Research and Practice  Volume 23, Issue 3
April 2011
66 pages

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John Wiley & Sons, Inc.

United States

Publication History

Published: 01 April 2011

Author Tags

  1. Code Bad Smells
  2. Systematic Literature Review
  3. empirical software engi-neering
  4. refactoring

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  • (2023)Examining deep learning’s capability to spot code smells: a systematic literature reviewCluster Computing10.1007/s10586-023-04144-126:6(3473-3501)Online publication date: 3-Oct-2023
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  • (2022)On preserving the behavior in software refactoringInformation and Software Technology10.1016/j.infsof.2021.106675140:COnline publication date: 22-Apr-2022
  • (2022)Code smells detection via modern code review: a study of the OpenStack and Qt communitiesEmpirical Software Engineering10.1007/s10664-022-10178-727:6Online publication date: 1-Nov-2022
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