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Pattern and Spoiled Pattern Detection Through an Information Retrieval Approach

Nadia Bouassida1 and Hanêne Ben-Abdallah1
1. Institut Supérieur d’Informatique et de Multimédia, Université de Sfax, Tunisie
2. Faculté des Sciences Economiques et de Gestion, Université de Sfax, Tunisie
Abstract—Design patterns provide for a higher software quality and a reduced development cost. However, to reach these benefits, designers are expected to have a good understanding and experience with design patterns, which is not evident to acquire. Another way to benefit from design patterns is by assisting designers in their detection/identification within a given design in order to improve it. Since the exact structural instantiation of a pattern is less frequent to find within a design, the identification process should account for variations of the design with respect to the pattern. It assists the designer by showing the pattern elements in terms of the design which can be validated with respect to the classes, attributes, methods and relations of the pattern: the designer can add/remove some elements from the design in order to ensure a good instantiation of the identified pattern. However, not all structural variations of a pattern are tolerated; in fact, some variations may result in non-optimal instantiations of the pattern, a.k.a. spoiled patterns. In this case, the identification process can assist the designer by proposing corrections for an acceptable pattern instantiation. Within this design context, we propose a method that identifies design patterns and spoiled patterns through an XML document retrieval approach. This latter provides for the possibility of tolerating structural variations between the design and the searched pattern. In addition, our pattern identification method can be parameterized in order to delimit the degree of acceptable variations.

Index Terms—design pattern identification, pattern instantiation, XML document retrieval  

Cite: Nadia Bouassida and Hanêne Ben-Abdallah, "Pattern and Spoiled Pattern Detection Through an Information Retrieval Approach," Journal of Emerging Technologies in Web Intelligence, Vol. 2, No. 3, pp. 167-175, August 2010. doi:10.4304/jetwi.2.3.167-175
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