From a Domain Analysis to the Specification and Detection of Topic: <b>Code and design smells</b>. Moha, N., Gu�h�neuc, Y., Le Meur, A., Duchien, L., & Tiberghien, A. Formal Aspects of Computing (FAC), 22(3):345–368, Springer, May, 2010. 23 pages.![From a Domain Analysis to the Specification and Detection of Topic: <b>Code and design smells</b> [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper abstract bibtex Topic: Code and design smells are recurring design problems in software systems that need to be identified to avoid their possible negative consequences in development and maintenance. Consequently, several smell detection approaches and tools have been proposed in the literature. However, so far, they allow the detection of predefined smells but the detection of new smells or smells adapted to the context of the analysed systems is possible only by implementing new detection algorithms manually. Moreover, previous approaches do not explain the transition from specifications of smells to their detection. Finally, the validation of the existing detection approaches and tools has been limited on few proprietary systems and on a reduced number of smells. In this paper, we introduce an approach to automate the generation of detection algorithms from specifications written using a domain-specific language. This language is defined from a thorough domain analysis. It allows the specification of smells using high-level domain-related abstractions. It allows the adaptation of the specifications of smells to the context of the analysed systems. We specify 10 smells, generate automatically their detection algorithms using templates, and validate the algorithms in terms of precision and recall on \ygg@productXerces v2.7.0 and \ygg@productGanttProject v1.10.2, two open-source object-oriented systems.
@ARTICLE{Moha09-FAC-DDDomainAnalysis,
AUTHOR = {Naouel Moha and Yann-Ga�l Gu�h�neuc and
Le Meur, Anne-Fran�oise and Laurence Duchien and Alban Tiberghien},
JOURNAL = {Formal Aspects of Computing (FAC)},
TITLE = {From a Domain Analysis to the Specification and
Detection of Topic: <b>Code and design smells</b>},
YEAR = {2010},
MONTH = {May},
NOTE = {23 pages.},
NUMBER = {3},
PAGES = {345--368},
VOLUME = {22},
EDITOR = {Jos� Luiz Fiadeiro},
KEYWORDS = {Topic: <b>Code and design smells</b>, Venue: <b>FAC</b>},
PUBLISHER = {Springer},
URL = {http://www.ptidej.net/publications/documents/FAC09.doc.pdf},
ABSTRACT = {Topic: <b>Code and design smells</b> are recurring
design problems in software systems that need to be identified to
avoid their possible negative consequences in development and
maintenance. Consequently, several smell detection approaches and
tools have been proposed in the literature. However, so far, they
allow the detection of predefined smells but the detection of new
smells or smells adapted to the context of the analysed systems is
possible only by implementing new detection algorithms manually.
Moreover, previous approaches do not explain the transition from
specifications of smells to their detection. Finally, the validation
of the existing detection approaches and tools has been limited on
few proprietary systems and on a reduced number of smells. In this
paper, we introduce an approach to automate the generation of
detection algorithms from specifications written using a
domain-specific language. This language is defined from a thorough
domain analysis. It allows the specification of smells using
high-level domain-related abstractions. It allows the adaptation of
the specifications of smells to the context of the analysed systems.
We specify 10 smells, generate automatically their detection
algorithms using templates, and validate the algorithms in terms of
precision and recall on \ygg@product{Xerces} v2.7.0 and
\ygg@product{GanttProject} v1.10.2, two open-source object-oriented
systems.}
}
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