A comparative evaluation of using genetic programming for predicting fault count data
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- @InProceedings{Afzal08d,
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author = "Wasif Afzal and Richard Torkar",
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title = "A comparative evaluation of using genetic programming
for predicting fault count data",
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booktitle = "Proceedings of the Third International Conference on
Software Engineering Advances (ICSEA'08)",
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year = "2008",
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pages = "407--414",
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address = "Sliema, Malta",
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month = "26-31",
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keywords = "genetic algorithms, genetic programming, prediction,
software reliability growth modeling, SBSE",
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isbn13 = "978-1-4244-3218-9",
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DOI = "doi:10.1109/ICSEA.2008.9",
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abstract = "There have been a number of software reliability
growth models (SRGMs) proposed in literature. Due to
several reasons, such as violation of models'
assumptions and complexity of models, the practitioners
face difficulties in knowing which models to apply in
practice. This paper presents a comparative evaluation
of traditional models and use of genetic programming
(GP) for modeling software reliability growth based on
weekly fault count data of three different industrial
projects. The motivation of using a GP approach is its
ability to evolve a model based entirely on prior data
without the need of making underlying assumptions. The
results show the strengths of using GP for predicting
fault count data.",
-
notes = "Also known as \cite{4668139}
",
- }
Genetic Programming entries for
Wasif Afzal
Richard Torkar
Citations