Automatic Generation of Search-Based Algorithms Applied to the Feature Testing of Software Product Lines
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Filho:2017:AGS:3131151.3131152,
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author = "Helson L. {Jakubovski Filho} and
Jackson A. {Prado Lima} and Silvia R. Vergilio",
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title = "Automatic Generation of Search-Based Algorithms
Applied to the Feature Testing of Software Product
Lines",
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booktitle = "Proceedings of the 31st Brazilian Symposium on
Software Engineering, SBES-2017",
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year = "2017",
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editor = "Jose Carlos Maldonado and Fabiano {Cutigi Ferrari} and
Uira Kulesza and Tayana {Uchoa Conte}",
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pages = "114--123",
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address = "Fortaleza, CE, Brazil",
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month = sep # " 20-22",
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organisation = "Brazilian Computer Society",
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publisher = "ACM",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution, NSGA-II, SBSE, SPL, Hyper-Heuristics,
Search-Based Software Engineering, Software Product
Line Testing",
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isbn13 = "978-1-4503-5326-7",
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acmid = "3131152",
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DOI = "doi:10.1145/3131151.3131152",
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size = "10 pages",
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abstract = "The selection of products for the variability testing
of Feature Models (FMs) is a complex task impacted by
many factors. To solve this problem, Multi-Objective
Evolutionary Algorithms (MOEAs) have been successfully
used in the field known as Search-Based Software
Engineering (SBSE). However, the design of a
search-based approach is not an easy task for the
software engineer, who can find some difficulties such
as: the choice and configuration of the best MOEAs, the
choice of the best search operators to be implemented,
and so on. In addition to this, existing approaches are
dependent on the problem domain and do not allow reuse.
In this way the use of Hyper-Heuristic (HH) can help to
obtain more generic and reusable search-based
approaches, and because of this is considered a trend
in the SBSE field. Following this trend and to
contribute to reduce the software engineer's efforts,
this work explores the use of a hyper-heuristic for
automatic generation of MOEAs to select test products
from the FM",
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notes = "http://www.lia.ufc.br/~cbsoft2017/en/xxxi-sbes/sbes-cfp/
Department of Computer Science, Federal University of
Parana, Curitiba, Parana, Brazil",
- }
Genetic Programming entries for
Helson L Jakubovski Filho
Jackson A Prado Lima
Silvia Regina Vergilio
Citations