A Systematic Literature Review on Bad Smells-5 W's: Which, When, What, Who, Where
Bad smells are sub-optimal code structures that may represent problems needing attention. We conduct an extensive literature review on bad smells relying on a large body of knowledge from 1990 to 2017. We show that some smells are much more studied in the literature than others, and also that some o...
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| Published in | IEEE transactions on software engineering Vol. 47; no. 1; pp. 17 - 66 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.01.2021
IEEE Computer Society |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0098-5589 1939-3520 |
| DOI | 10.1109/TSE.2018.2880977 |
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| Abstract | Bad smells are sub-optimal code structures that may represent problems needing attention. We conduct an extensive literature review on bad smells relying on a large body of knowledge from 1990 to 2017. We show that some smells are much more studied in the literature than others, and also that some of them are intrinsically inter-related (which). We give a perspective on how the research has been driven across time (when). In particular, while the interest in duplicated code emerged before the reference publications by Fowler and Beck and by Brown et al., other types of bad smells only started to be studied after these seminal publications, with an increasing trend in the last decade. We analyzed aims, findings, and respective experimental settings, and observed that the variability of these elements may be responsible for some apparently contradictory findings on bad smells (what). Moreover, we could observe that, in general, papers tend to study different types of smells at once. However, only a small percentage of those papers actually investigate possible relations between the respective smells (co-studies), i.e., each smell tends to be studied in isolation. Despite of a few relations between some types of bad smells have been investigated, there are other possible relations for further investigation. We also report that authors have different levels of interest in the subject, some of them publishing sporadically and others continuously (who). We observed that scientific connections are ruled by a large "small world" connected graph among researchers and several small disconnected graphs. We also found that the communities studying duplicated code and other types of bad smells are largely separated. Finally, we observed that some venues are more likely to disseminate knowledge on Duplicate Code (which often is listed as a conference topic on its own), while others have a more balanced distribution among other smells (where). Finally, we provide a discussion on future directions for bad smell research. |
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| AbstractList | Bad smells are sub-optimal code structures that may represent problems needing attention. We conduct an extensive literature review on bad smells relying on a large body of knowledge from 1990 to 2017. We show that some smells are much more studied in the literature than others, and also that some of them are intrinsically inter-related ( which ). We give a perspective on how the research has been driven across time ( when ). In particular, while the interest in duplicated code emerged before the reference publications by Fowler and Beck and by Brown et al., other types of bad smells only started to be studied after these seminal publications, with an increasing trend in the last decade. We analyzed aims, findings, and respective experimental settings, and observed that the variability of these elements may be responsible for some apparently contradictory findings on bad smells ( what ). Moreover, we could observe that, in general, papers tend to study different types of smells at once. However, only a small percentage of those papers actually investigate possible relations between the respective smells (co-studies), i.e., each smell tends to be studied in isolation. Despite of a few relations between some types of bad smells have been investigated, there are other possible relations for further investigation. We also report that authors have different levels of interest in the subject, some of them publishing sporadically and others continuously ( who ). We observed that scientific connections are ruled by a large “small world” connected graph among researchers and several small disconnected graphs. We also found that the communities studying duplicated code and other types of bad smells are largely separated. Finally, we observed that some venues are more likely to disseminate knowledge on Duplicate Code (which often is listed as a conference topic on its own), while others have a more balanced distribution among other smells ( where ). Finally, we provide a discussion on future directions for bad smell research. |
| Author | Maia, Marcelo de Almeida Sobrinho, Elder Vicente de Paulo De Lucia, Andrea |
| Author_xml | – sequence: 1 givenname: Elder Vicente de Paulo orcidid: 0000-0001-7735-6732 surname: Sobrinho fullname: Sobrinho, Elder Vicente de Paulo email: eldereng@hotmail.com organization: Department of Electrical Engineering, Federal University of Triângulo Mineiro, Uberaba, Brazil – sequence: 2 givenname: Andrea orcidid: 0000-0002-4238-1425 surname: De Lucia fullname: De Lucia, Andrea email: adelucia@unisa.it organization: University of Salerno, Fisciano, (SA), Italy – sequence: 3 givenname: Marcelo de Almeida orcidid: 0000-0003-3578-1380 surname: Maia fullname: Maia, Marcelo de Almeida email: marcelo.maia@ufu.br organization: Faculty of Computing, Federal University of Uberlândia, Uberlândia, Brazil |
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| Snippet | Bad smells are sub-optimal code structures that may represent problems needing attention. We conduct an extensive literature review on bad smells relying on a... |
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| SubjectTerms | bad smell Bibliographies Cloning Documents Investigations Literature reviews Measurement Organizations reengineering Reproduction (copying) Smell Software Software maintenance Systematic review Systematics |
| Title | A Systematic Literature Review on Bad Smells-5 W's: Which, When, What, Who, Where |
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