A Genetic Programming Approach for Software Reliability Modeling
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- @Article{Costa:2010:ieeeTR,
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author = "Eduardo Oliveira Costa and
Aurora Trinidad Ramirez Pozo and Silvia Regina Vergilio",
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title = "A Genetic Programming Approach for Software
Reliability Modeling",
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journal = "IEEE Transactions on Reliability",
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year = "2010",
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keywords = "genetic algorithms, genetic programming, Fault
prediction, machine learning techniques, software
reliability models, SBSE",
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abstract = "Genetic Programming (GP) models adapt better to the
reliability curve when compared with other traditional,
and non-parametric models. In a previous work, we
conducted experiments with models based on time, and on
coverage. We introduced an approach, named Genetic
Programming and Boosting (GPB), that uses boosting
techniques to improve the performance of GP. This
approach presented better results than classical GP,
but required ten times the number of executions.
Therefore, we introduce in this paper a new GP based
approach, named $(mu+lambda)$ GP. To evaluate this new
approach, we repeated the same experiments conducted
before. The results obtained show that the
$(mu+lambda)$ GP approach presents the same cost of
classical GP, and that there is no significant
difference in the performance when compared with the
GPB approach. Hence, it is an excellent, less expensive
technique to model software reliability.",
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DOI = "doi:10.1109/TR.2010.2040759",
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ISSN = "0018-9529",
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notes = "Also known as \cite{5409534}",
- }
Genetic Programming entries for
Eduardo Oliveira Costa
Aurora Trinidad Ramirez Pozo
Silvia Regina Vergilio
Citations