Identification of Web Service Refactoring Opportunities as a Multi-objective Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.7642

@InProceedings{Wang:2016:ICWS,

• author = "Hanzhang Wang and Ali Ouni and Marouane Kessentini and Bruce Maxim and William I. Grosky",
• booktitle = "2016 IEEE International Conference on Web Services (ICWS)",
• title = "Identification of Web Service Refactoring Opportunities as a Multi-objective Problem",
• year = "2016",
• pages = "586--593",
• abstract = "We propose, in this paper, to consider the problem of Web service anti-patterns detection as a multi-objective problem where examples of Web service anti patterns and well-designed code are used to generate detection rules. To this end, we use multi-objective genetic programming (MOGP) to find the best combination of metrics that maximizes the detection of Web service antipattern examples and minimises the detection of well-designed Web service design examples. We report the results of an empirical study using 8 different types of common Web service antipatterns. We compared our multi-objective formulation with random search, one existing mono-objective approach, and one state-of-the-art detection technique not based on heuristic search. Statistical analysis of the obtained results demonstrates that our approach is efficient in antipattern detection, on average, with a precision score of 94percent and a recall score of 92percent.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICWS.2016.81",
• month = jun,
• notes = "Also known as \cite{7558051}",

}

Genetic Programming entries for Hanzhang Wang Ali Ouni Marouane Kessentini Bruce R Maxim William I Grosky

Citations