Feature Model Synthesis with Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Linsbauer:2014:SSBSE,
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author = "Lukas Linsbauer and Roberto Erick Lopez-Herrejon and
Alexander Egyed",
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title = "Feature Model Synthesis with Genetic Programming",
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booktitle = "Proceedings of the 6th International Symposium, on
Search-Based Software Engineering, SSBSE 2014",
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year = "2014",
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editor = "Claire {Le Goues} and Shin Yoo",
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volume = "8636",
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series = "LNCS",
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pages = "153--167",
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address = "Fortaleza, Brazil",
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month = "26-29 " # aug,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, SBSE, Feature
Models, Feature Set, Reverse Engineering, Software
Product Lines, Variability Modelling",
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isbn13 = "978-3-319-09939-2",
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URL = "http://www.springer.com/computer/swe/book/978-3-319-09939-2",
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DOI = "doi:10.1007/978-3-319-09940-8_11",
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size = "15 pages",
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abstract = "Search-Based Software Engineering (SBSE) is successful
on several stages of the software development life
cycle. It has also been applied to different challenges
in the context of Software Product Lines (SPLs) like
generating minimal test suites. When reverse
engineering SPLs from legacy software an important
challenge is the reverse engineering of variability,
often expressed in the form of Feature Models (FMs).
The synthesis of FMs has been studied with techniques
such as Genetic Algorithms. In this paper we explore
the use of Genetic Programming for this task. We sketch
our general workflow, the GP pipeline employed, and its
evolutionary operators. We report our experience in
synthesising feature models from sets of feature
combinations for 17 representative feature models, and
analyse the results using standard information
retrieval metrics.",
- }
Genetic Programming entries for
Lukas Linsbauer
Roberto E Lopez-Herrejon
Alexander Egyed
Citations