Quality Improvement in Annotated Code

In order to customize their behavior at runtime, a wide sort of modern frameworks do use code annotations at the applications‟ classes as metadata configuration. However, despite its popularity, this type of metadata definition inserts complexity and semantic coupling that is ignored by traditional...

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Main Authors: Diego A. A. Correia, Eduardo M. Guerra, Fabio F. Silveira, Clovis T. Fernandes
Format: Article
Language:English
Published: Centro Latinoamericano de Estudios en Informática 2010-08-01
Series:CLEI Electronic Journal
Online Access:http://www.clei.org/cleiej-beta/index.php/cleiej/article/view/192
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author Diego A. A. Correia
Eduardo M. Guerra
Fabio F. Silveira
Clovis T. Fernandes
author_facet Diego A. A. Correia
Eduardo M. Guerra
Fabio F. Silveira
Clovis T. Fernandes
author_sort Diego A. A. Correia
collection DOAJ
description In order to customize their behavior at runtime, a wide sort of modern frameworks do use code annotations at the applications‟ classes as metadata configuration. However, despite its popularity, this type of metadata definition inserts complexity and semantic coupling that is ignored by traditional software metrics. This paper presents identified bad smells in annotated code and defines new metrics that help in their detection by enabling a quantitative assessment of complexity and coupling in this type of code. Moreover, it proposes some strategies to detect those bad smells by using the defined metrics and introduces an open-source tool created to automate the process of bad smell discovery on annotated code.
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spelling doaj.art-67c0f9c53edb4e9f91567830f8c404952022-12-21T20:56:29ZengCentro Latinoamericano de Estudios en InformáticaCLEI Electronic Journal0717-50002010-08-0113210.19153/cleiej.13.2.7Quality Improvement in Annotated CodeDiego A. A. CorreiaEduardo M. GuerraFabio F. SilveiraClovis T. FernandesIn order to customize their behavior at runtime, a wide sort of modern frameworks do use code annotations at the applications‟ classes as metadata configuration. However, despite its popularity, this type of metadata definition inserts complexity and semantic coupling that is ignored by traditional software metrics. This paper presents identified bad smells in annotated code and defines new metrics that help in their detection by enabling a quantitative assessment of complexity and coupling in this type of code. Moreover, it proposes some strategies to detect those bad smells by using the defined metrics and introduces an open-source tool created to automate the process of bad smell discovery on annotated code.http://www.clei.org/cleiej-beta/index.php/cleiej/article/view/192
spellingShingle Diego A. A. Correia
Eduardo M. Guerra
Fabio F. Silveira
Clovis T. Fernandes
Quality Improvement in Annotated Code
CLEI Electronic Journal
title Quality Improvement in Annotated Code
title_full Quality Improvement in Annotated Code
title_fullStr Quality Improvement in Annotated Code
title_full_unstemmed Quality Improvement in Annotated Code
title_short Quality Improvement in Annotated Code
title_sort quality improvement in annotated code
url http://www.clei.org/cleiej-beta/index.php/cleiej/article/view/192
work_keys_str_mv AT diegoaacorreia qualityimprovementinannotatedcode
AT eduardomguerra qualityimprovementinannotatedcode
AT fabiofsilveira qualityimprovementinannotatedcode
AT clovistfernandes qualityimprovementinannotatedcode