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Journal of Systems and Software
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Article . 2022 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2019
License: CC BY NC SA
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Are architectural smells independent from code smells? An empirical study

Authors: Arcelli Fontana F.; Lenarduzzi V.; Roveda R.; Taibi D.;

Are architectural smells independent from code smells? An empirical study

Abstract

Background. Architectural smells and code smells are symptoms of bad code or design that can cause different quality problems, such as faults, technical debt, or difficulties with maintenance and evolution. Some studies show that code smells and architectural smells often appear together in the same file. The correlation between code smells and architectural smells, however, is not clear yet; some studies on a limited set of projects have claimed that architectural smells can be derived from code smells, while other studies claim the opposite. Objective. The goal of this work is to understand whether architectural smells are independent from code smells or can be derived from a code smell or from one category of them. Method. We conducted a case study analyzing the correlations among 19 code smells, six categories of code smells, and four architectural smells. Results. The results show that architectural smells are correlated with code smells only in a very low number of occurrences and therefore cannot be derived from code smells. Conclusion. Architectural smells are independent from code smells, and therefore deserve special attention by researchers, who should investigate their actual harmfulness, and practitioners, who should consider whether and when to remove them.

(in press)

Countries
Italy, Finland
Keywords

Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, 005, 113 Computer and information sciences, 113, Architectural smells; Code smells; Empirical analysis; Technical debt;, Architectural smells; Code smells; Empirical analysis; Technical debt

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    36
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
36
Top 10%
Top 10%
Top 10%
Green
bronze