Identification of Web Service Refactoring Opportunities as a Multi-objective Problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Wang:2016:ICWS,
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author = "Hanzhang Wang and Ali Ouni and Marouane Kessentini and
Bruce Maxim and William I. Grosky",
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booktitle = "2016 IEEE International Conference on Web Services
(ICWS)",
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title = "Identification of Web Service Refactoring
Opportunities as a Multi-objective Problem",
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year = "2016",
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pages = "586--593",
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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.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/ICWS.2016.81",
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month = jun,
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notes = "Also known as \cite{7558051}",
- }
Genetic Programming entries for
Hanzhang Wang
Ali Ouni
Marouane Kessentini
Bruce R Maxim
William I Grosky
Citations