Modeling Software Reliability Growth with Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{conf/issre/CostaVPS05,
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title = "Modeling Software Reliability Growth with Genetic
Programming",
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author = "Eduardo Oliveira Costa and Silvia Regina Vergilio and
Aurora Trinidad Ramirez Pozo and
Gustavo A. {de Souza}",
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year = "2005",
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pages = "171--180",
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booktitle = "16th International Symposium on Software Reliability
Engineering (ISSRE 2005)",
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address = "Chicago, IL, USA",
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month = "8-11 " # nov,
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publisher = "IEEE Computer Society",
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bibdate = "2006-01-03",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/issre/issre2005.html#CostaVPS05",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-7695-2482-6",
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DOI = "doi:10.1109/ISSRE.2005.29",
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abstract = "Reliability Models are very useful to estimate the
probability of the software fail along the time.
Several different models have been proposed to estimate
the reliability growth, however, none of them has
proven to perform well considering different project
characteristics. In this work, we explore Genetic
Programming (GP) as an alternative approach to derive
these models. GP is a powerful machine learning
technique based on the idea of genetic algorithms and
has been acknowledged as a very suitable technique for
regression problems. The main motivation to choose GP
for this task is its capability of learning from
historical data, discovering an equation with different
variables and operators. experiment were conducted to
confirm this hypotheses and the results were compared
with traditional and Neural Network models.",
- }
Genetic Programming entries for
Eduardo Oliveira Costa
Silvia Regina Vergilio
Aurora Trinidad Ramirez Pozo
Gustavo Antonio de Souza Goll
Citations