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A Domain Analysis to Specify Design Defects and Generate Detection Algorithms. Naouel Moha, Yann-Gaël Guéhéneuc, Anne-Françoise {Le Meur} and Laurence Duchien. In Proceedings of the $11^{th}$ International Conference on Fundamental Approaches to Software Engineering (FASE), 2008. (Acceptance rate : 26\%, Rank (CORE) : B).
Quality experts often need to identify in software systems design defects, which are recurring design problems, that hinder development and maintenance. Consequently, several defect detection approaches and tools have been proposed in the literature. However, we are not aware of any approach that defines and reifies the process of generating detection algorithms from the existing textual descriptions of defects. In this paper, we introduce an approach to automate the generation of detection algorithms from specifications written using a domain-specific language. The domain-specific is defined from a thorough domain analysis. We specify several design defects, generate automatically detection algorithms using templates, and validate the generated detection algorithms in terms of precision and recall on Xerces v2.7.0, an open-source object-oriented system.
@INPROCEEDINGS { Moha08-FASE-Language,
AUTHOR = { Naouel Moha and Yann-Ga\"el Gu\'eh\'eneuc and Anne-Fran\c{c}oise {Le Meur} and Laurence Duchien },
YEAR = { 2008 },
TITLE = { {A Domain Analysis to Specify Design Defects and Generate Detection Algorithms} },
BOOKTITLE = { Proceedings of the $11^{th}$ International Conference on Fundamental Approaches to Software Engineering (FASE) },
PUBLISHER = { Springer-Verlag },
EDITOR = { Jos\'e Fiadeiro and Paola Inverardi },
LANGUAGE = { english },
SELECTIF = { oui },
ABSTRACT = { Quality experts often need to identify in software systems design defects, which are recurring design problems, that hinder development and maintenance. Consequently, several defect detection approaches and tools have been proposed in the literature. However, we are not aware of any approach that defines and reifies the process of generating detection algorithms from the existing textual descriptions of defects. In this paper, we introduce an approach to automate the generation of detection algorithms from specifications written using a domain-specific language. The domain-specific is defined from a thorough domain analysis. We specify several design defects, generate automatically detection algorithms using templates, and validate the generated detection algorithms in terms of precision and recall on Xerces v2.7.0, an open-source object-oriented system. },
LASTNAME = { Moha },
DATEADDED = { 2008-01-21 },
LASTDATEMODIFIED = { 2008-01-21 },
LABO = { dans },
INRIA = { ADAM },
AERES = { ACT },
RATE = { 26\% },
NOTE = { Acceptance rate : 26\%, Rank (CORE) : B },
BOARD = { yes },
PROCEEDINGS = { yes },
AUDIENCE = { yes },
}
Adam